Mobile application development process: A practical experience

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Mobile app development in health research: pitfalls and solutions

Aaron j. siegler.

1 Department of Behavioral Sciences and Health Education, Emory University, Atlanta, GA, USA;

Justin Knox

2 Department of Epidemiology, Columbia University, New York, NY, USA;

José A. Bauermeister

3 Department of Family & Community Health, University of Pennsylvania, Philadelphia, PA, USA;

Jesse Golinkoff

4 Department of Family & Community Health, University of Pennsylvania, Philadelphia, PA, USA;

Lisa Hightow-Weidman

5 Department of Medicine, University of North Carolina, Chapel Hill, NC, USA;

Hyman Scott

6 Bridge HIV, San Francisco Department of Public Health, San Francisco, CA, USA

Mobile app health research presents myriad opportunities to improve health, and simultaneously introduces a new set of challenges that are non-intuitive and extend beyond typical training received by researchers. Informed by our experiences with app development for health research, we discuss some of the most salient pitfalls when working with emerging technology as well as potential strategies to avoid or resolve these challenges. To address challenges at the project level, we suggest strategies that researchers can use to future-proof their research, such as using theory and involving those with app development expertise as part of a research team. At the structural level, we include a new model to characterize the relationship between technology- and research-timelines, and provide ideas regarding how to best address this challenge. Given that screen-based time now predominates our lived experiences, it is important that health researchers have the capacity and structural support to develop interventions that utilize these technologies, assess them rigorously, and ensure their timely and equitable dissemination.

Introduction

The use of mobile applications (apps) is pervasive across every aspect of daily life. Smartphones have been adopted faster than nearly any other technological innovation in history, such that it is now nearly universal in the United States (81% of all US adults, including 96% of adults ages 18–29) ( 1 - 3 ). This phenomenon has also occurred across the globe, with over 3.3 billion people using smartphones worldwide ( 4 ). Adults spend 2.5–5 hours per day on their phones, or 13–16% of their waking hours. This trend is even more pronounced among US adolescents, 95% of whom either own or have access to a smartphone, with nearly half reporting being online on a near-constant basis ( 5 ). Despite some health concerns, particularly related to excessive screen time, there is growing interest in leveraging smart phone technologies to promote health through mobile apps ( 6 - 8 ).

The development and use of mobile health apps is rapidly increasing, with a wide variety of functions such as self-monitoring of chronic health conditions, medication adherence reminders, and direct interactions with the health care system ( 9 - 12 ). Mobile health apps are increasingly being used even in situations when clinical care is provided in-person, as they can be used to help tailor patient-provider communication and support patient self-management and care engagement ( 9 ). Multiple systematic reviews, usually grouped by health condition or sub-population, have summarized the growing evidence base for the effectiveness of mobile health apps ( 10 , 11 ). For example, a recent meta-analysis of digital interventions that address alcohol consumption in community-dwelling populations, including many mobile health apps, found moderate-quality evidence that digital interventions decrease unhealthy alcohol consumption ( 13 ). A recent systematic review of the use of mobile health apps for substance use disorders concluded that the heterogeneity of mobile health apps made reaching a consensus about their overall effectiveness challenging ( 14 ). This review also noted that mobile health apps should fully capitalize on the technology’s capacity to tailor itself to meet the individual needs of users ( 14 ). Achieving this, however, will likely require a better understanding of how people incorporate technology into their everyday lives, as well as research into effective ways to disseminate efficacious interventions into more diverse clinical and community settings. Another review noted the great promise for mobile health apps to make an impact in low- and middle-income countries, where access to medical care is often limited but smartphone ownership is widespread ( 12 ).

A growing number of health research programs investigate app-based interventions, yet many research teams conduct their app research in isolation. There are substantial benefits to be gained by sharing knowledge across disciplines, particularly in navigating common challenges and leveraging areas of strength. In this article, we discuss opportunities and pitfalls for mobile health app research, and propose solutions to facilitate success and overcome challenges.

Opportunities

Leveraging device, operating system, and potential for scale.

Mobile apps are able to leverage the strengths of host device hardware and operating systems. A review by Harari and colleagues has documented the numerous sensors and data collected by research apps ( 15 ), including accelerometer (coordinates, duration of movement), GPS scan (geolocation), clock (time), light sensor (ambient light), and microphone (audio). These data sources can be used creatively to develop interventions. For instance, a sun protection trial combined GPS data with real-time forecasts and time of day information to provide guidance regarding risk of sunburn and time until needed reapplication of sunscreen ( 16 ). A number of physical activity trials have used smartphone accelerometer data to collect physical activity data, and display such data as part of the intervention to study participants ( 17 ). Operating systems also provide rich interactive and monitoring features, including alarms, notifications, call logs, text logs, and system usage information. Data generated by these features can be highly useful; one study validated an algorithm to predict the total amount of users’ sleep based on their smartphone screen being on or off, with an average error of only 7% ( 18 ). Alarms/notifications are a main feature of many app-based interventions, providing a way to communicate updated data-informed progress towards goals, motivational messages, and re-engagement messages ( 17 , 19 - 21 ). Another important benefit of the flexibility of app systems is their capacity to interface with a wide variety of other devices such as pedometers ( 17 ) and pill bottle cap sensors ( 22 ).

The ability to positively influence health at a large scale is an intriguing advantage of successful mobile apps. Traditionally, the gold standard for impactful individual-level behavioral interventions has been evidence-based, multi-session interventions that are delivered in person. This approach provides a high level of exposure to a potentially tailored intervention, although it comes at a high cost by requiring substantial staff time and materials for each person newly engaged. Such multi-session interventions are typically sequentially planned to control the order in which a participant is exposed to an intervention, potentially enhancing the intervention’s effect, but also challenging the logistics of delivery. Mobile health apps have the potential to provide users with a high level of exposure (smartphones are ubiquitous and heavily used), while only requiring staff time that is fixed to the development and monitoring of the sequentially-designed app intervention, with low additional cost per person reached. Other technology-based intervention modalities, such as text messaging and website-based interventions, may have similar benefits of scale.

Tailoring and measurement

Apps are a natural fit for providing tailored health information, with the potential to build in automated tailoring by user groups or by disease condition. Apps are created for a broad array of conditions that require tailored materials, ranging from tele-rehabilitation for people with multiple sclerosis ( 23 ) to interventions to address childhood obesity ( 24 ). App platforms allow for each user group to receive an intervention appropriate for and customized to their experiences. This has the additional benefit of facilitating more successful inclusion of groups experiencing health disparities such as youth, sexual, and racial minorities ( 25 , 26 ). Through tailoring, mobile apps have the potential to engage persons in their health promotion in new and innovate ways, which are moreover less dependent on existing healthcare structures. For instance, apps can help users collect and track data on a particular health behavior and can return information tailored to that individual, such as their stage in transtheoretical model ( 27 ), thereby optimally facilitating behavioral change.

Paradata, automated process data collected as users interact with a smartphone app, is an important additional tool to gain insight on how users engage with an app ( 28 , 29 ). Examples of paradata include log-in/log-out times; time spent in the app overall and by each app feature; and number of clicks through each app feature. Used in combination with the primary research outcomes data, paradata provides insight into user preferences and app use patterns. It can help app researchers to understand why an app feature may or may not have met expected outcomes, and provide direction for further tailoring or updates.

Technology versus research timelines

Technology product development is characterized by a period of ascent characterized by high innovation followed by a phase of maturity, and then a period of decline ( 30 ). There can be a mismatch between the timelines of NIH-funded research and technological products. NIH research grant cycles predominantly adhere to a 10-year timeline, yet technology cycles may occur more rapidly ( Figure 1 ). To elaborate: a typical NIH-funded research cycle begins with idea generation, seed funding and baseline data collection, and first grant application (2 years), and then proceeds to a planning grant (e.g., R34/R21) and its implementation (3 years), clinical trial phase (5 years), and results dissemination (1 year), totaling a more than 10-year cycle. It is worth noting that some of these research phases may be skipped, such as if sufficient baseline data exist to avoid the seed funding period. Yet other issues may extend research timelines, such as grant resubmissions. In contrast to the linear and timeline-based process of research, there is greater variability in technological uptake, which tends to ebb and flow based on development of technological breakthroughs such as new platforms and interfaces. These types of breakthroughs may challenge the 10-year NIH cycle. For instance, if an innovative product such as the Nintendo Wii or apps such as Pokemon Go entice researchers and they initiate the NIH-funded research cycle during ascent or maturity periods, it is possible for product sales to be (I) obsolete, ended prior to research completion, (II) simultaneous, ending at the same time as the research, or (III) continuing, with sales ongoing or even growing as the research ends. In the first two scenarios, the product platform has ended before research regarding a particular intervention can be brought to scale.

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Technology versus research cycles.

Given rapid changes in technology, it is difficult to predict when disruptive technology may break through and interrupt research plans, including those regarding app development or configuration. More subtle than disruptive innovations, but perhaps equally important, are changing norms in the design of technology interfaces. Design and user interface norms shift rapidly, with older fonts, icons, graphics, and functions quick to appear dated. Without updating, older interfaces may appear stale or nonintuitive, potentially impacting user willingness to engage with the technology. This is especially likely to impact apps grounded in gamification and graphics features, which are likely to require more frequent updating.

App development

There is an inherent information asymmetry between professional app developers’ expertise in coding and researchers possessing terminal degrees in unrelated fields. Information asymmetry is classically described as an imbalance of power that can lead to poor outcomes. Researchers with projects that involve app development either work with an app development agency, work with a free-lance app developer, or hire a full-time employee with app development experience. Due to limited experience and information, researchers are likely to have difficulty choosing the optimal approach. Moreover, any final contract may be insufficient to facilitate successful development required by the researcher ( 31 ). Once app development has begun, most researchers do not have the requisite information or experience to properly oversee the process. For example, an app developer may not be creating code of a sufficiently high quality, yet a researcher may not be able to detect this until the contract is finished and problems emerge with the app’s functioning. Moreover, researchers without app development experience may miss key areas during its design that can affect both users’ experience and interface with the app. Key areas of development include such things as coding architecture, common features (e.g., login with new technology such as fingerprint or face recognition), navigating institutional (e.g., university) and professional [e.g., Health Information Portability and Accountability Act (HIPAA)] security standards, and clarifying data export requirements. When challenges arise, any unplanned but desired app features are likely to result in substantial shifts in timelines and additions to development costs beyond the initially agreed fee.

Researchers should be particularly clear about the data export functionality of their app so that they can ensure data are being collected and exported in a way that facilitates its analysis. This area requires particular attention because it is foreign to most developers who usually focus on business-based outputs of ad clicks and sales. Even those developers accustomed to working with academics may struggle, especially as developers often code in teams, and research expertise may not be uniform across a technology team.

Technical challenges can be exacerbated by the high expenses required to create apps. Apps sufficiently nuanced to fulfill the needs of researchers, and that meet current HIPAA and other security standards, can be costly. The costs of app development range broadly, but even for a relatively low-feature health app, researchers should plan for costs over $150,000 US dollars if building from scratch (building from an existing platform can substantially change cost), a cost that may not fit into the budgets of NIH funding mechanisms typically used to fund pilot studies ( 32 ). An important component contributing to high costs are requisite security features for apps dealing with health information. Security concerns are not hypothetical; for example, in 2015, the health information of over 100 million individuals was breached ( 33 ). In other years between 2013 and 2017, more than 10 million individuals per year were impacted by health information breaches ( 33 ).

Translation and download problems

Once developed and tested in a clinical trial, apps demonstrated to be efficacious should be disseminated. Yet pathways to do so are relatively uncharted, and face two substantial problems. The translation problem is that health apps developed by researchers may never be translated into production models that can be downloaded by the public (and not just solely accessed by research subjects). In a search of NIH RePORTER conducted in late 2018, we identified 40 grants awarded to develop mobile apps relating to HIV, with 17 of these grants having completed their years of award. These grants represented a diverse portfolio of research, with target outcomes ranging from prevention (e.g., condom use) to treatment adherence, and target groups including general populations, racial/ethnic minorities, injection drugs users, men who have sex with men, and cis-gender women—indicating that any problems with performance were likely attributable to challenges spanning research domains and target populations. We performed a review of information for the 40 grants, both within RePORTER and within publications citing relevant grant numbers, to identify information such as a name or keyword that would allow us to search for resulting apps. We then searched the Google Play and iTunes App stores. We were unable to locate any apps from HIV grants in RePORTER that could be used by members of the public. We identified 2 apps that could be downloaded and used only by research participants.

The download problem is that even once made public, persons most in need of services are unlikely to download evidence-based apps unless they (I) are aware of the app, (II) believe the app provides substantial utility, and (III) believe it is better than existing apps. The app market is already inundated with non-evidence-based health apps. For instance, a review of mobile apps for HIV prevention identified 285 publicly available apps, but most (71%) were not developed by academic or public health entities, and none dealt with a key component of current prevention efforts: HIV pre-exposure prophylaxis ( 34 ). Similarly, a review of apps promulgated to support mental health found that only 10% offered support that was consistent with principles of evidence-based practice ( 35 ).

Sustainability

In addition to translation and download problems, apps that are disseminated require continual resources for updating and maintenance. Without this, apps quickly become dated and can stop functioning. This makes a post-research translation even more challenging. If not developed using a profit-seeking model, research funds are finite and tied to a specific set of proposed activities, putting most of this work beyond the scope of the vast majority of research proposals.

Conducting research informed by theory that applies rigorous methodologies

Research grounded in behavioral theory that uses rigorous and appropriate methodologies can produce findings that are generalizable beyond the life of the technology used in the research. There are multiple examples of this in research using the now defunct personal digital assistant (PDA). For instance, a recent PDA-based study used ecological momentary assessments (EMA), a method that involves repeated sampling of subjects experiences in their natural environments in real time, and found that side-effects and self-management among cancer survivors offer opportunities for tailored care programming ( 36 ). Another study used PDA and EMA, finding evidence that supports emotional regulation being measured as a trait ( 37 ). A study using the Technology Acceptance Model found that 71% of the variation of physicians intention to use a new device was explained by domains of perceived usefulness and perceived ease of use ( 38 ). Conversely, failure to base interventions on theory or functionality that can extend beyond a single technology leads to conclusions that are outdated by their time of publication. For example, the main conclusion of a 2013 article regarding PDAs (when such devices were off-market) was that PDA use should be scaled up among nursing students. This article could have benefitted from considering the benefits of incorporating changing technology into nursing education, in general, as well as the challenges with the changing pace of such technological solutions ( 39 ).

Leverage screen capture technology to document intervention

Technology change not only produces challenges for research, but also opportunities. Journals produce electronic supplements to publications, and those dedicated to protocol publication are an optimal venue for documentation of app-based interventions. Screenshots and verbal descriptions are useful to indicate functionality of websites, and are commonly used ( 40 ). The chief limitation of this approach is that it is challenging to describe interactive platforms with static images and text. We propose an alternative: to create screen recordings and voiceovers to provide a “walk-through” for each primary function of a study app. It is likely that such videos would be a valuable resource for future researchers and developers to adapt successful interventions for new platforms. Walk-throughs can be created, at no cost other than a limited amount of staff time, by using native screen recording functionality of a mobile phone. To our knowledge, this approach has not previously been used to document app-based interventions. For proprietary intervention components, video materials could be released alongside publication of trial results to facilitate future dissemination.

Short-circuit timelines and facilitate dissemination

To improve the responsiveness of the NIH funding cycle in order to more effectively conduct research on or using technology, a number of steps could be taken. One option is for researchers to consider alternative grant mechanisms within NIH, such as the Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs that are designed to support health products produced by small businesses in collaboration with research partners. The 2.5-year total research timeline for SBIR/STTR (a 6-month pilot, phase I and 2-year trial, phase II) allows it to be much more responsive to changes in technology, with a targeted goal of commercializing a product. Another option is to leverage NIH center grants and other mechanisms, such as U-level trials networks, to bring promising interventions to scale more quickly. For instance, the UNC/Emory Center for Innovative Technology (iTech), part of the Adolescent Medicine Trials Network for HIV/AIDS Interventions (ATN), creates an infrastructure to share and disseminate best practices in technology-based HIV interventions ( 41 ). Leveraging collective experiences in multiple app-based interventions facilitated development of the ePrEP platform after a 1-year pilot test ( 40 ). Researchers may also consider alternative funding venues, such as foundations, that may be more flexible and responsive to the needs of app development for health research.

A separate avenue is collaboration with private enterprises that have already achieved scale in the app space. Such an approach brings substantial benefits but also limitations. In favor of this model are the likely scalability and sustainability of the work. Additionally, by being on the cutting edge of what is in the marketplace, successful app businesses have access to the newest and most innovative tools that may benefit the research. This approach, however, requires meshing the business interests of the private enterprise with the research and public health interests of academic partners. Traditional research frameworks may need to be eschewed in favor of implementation science and monitoring/evaluation frameworks. Vested business interests may limit the scope of research, and issues of technology transfer and ownership may complicate relations. To the extent possible, these should be explored prior to commitment of the partnership.

Oversight of app technical development

Inclusion of an independent and research-versed developer to the research team can directly address the problem of information asymmetry. Many universities have technology-based app development groups that can provide such oversight through collaboration or trusted independent developers. Expertise is required early and periodically throughout the project. Early on in a project, an independent expert can ensure that the initial scope of work is sufficiently detailed to provide coverage of all program needs. The added costs of including an independent developer on the research team is often well worth the upfront cost because it can minimize potential problems regarding the scope of work and oversight of project development.

Independent expert oversight should extend to code architecture and development over the life of the project. Proper code architecture is essential for the performance of the basic tasks including (I) maintenance required due to phone operating system changes over time, (II) updates to address the appearance of unexpected issues as apps are used, and (III) addition of features demanded by users or researchers. Improper architecture can lead to results that confound and frustrate researchers unfamiliar with development: a simple bug fix can make seemingly unrelated parts of the app completely nonfunctional, requiring further fixes, a process that can spiral into cycles of dysfunctions and unexpected costs. These problems can also impact study outcomes if they occur during the course of a clinical trial. Moreover, an app designed with poor or highly stylized architecture may only be accessible for work by the original developers. This creates problems if the original developer either goes out of business or decides to substantially increase their prices. Proper planning and oversight can limit these pitfalls by ensuring that, as code is developed, it can be easily worked on and maintained by a coding team independent of the developer, with an architecture favorable to research data access and future app updates.

Structural changes

Structural changes could be made to capitalize on app-based research. NIH funds a number of center grants, and a future center could focus on expertise in health app development. Such a hub could anchor key contributions, such as (I) development of an open-source coding platform to address the most common research needs or (II) providing an at-cost service center model to provide expert oversight of code architecture for NIH-funded research projects. Adding a greater resource base could facilitate development of common functionality for open-source coding platforms that already exist, such as ResearchStack for Android, ResearchKit for iOS, or frameworks that allow simultaneous development of both Android and iOS such as React Native. Additional resources could include standardized consent or programming interfaces for commonly used external services such as survey platforms. Having these openly available to researchers could provide substantial resource savings for future app development. These efforts face challenges, however, such as staying current due to rapidly changing technology and norms of development. An alternative strategy could be to develop a model to facilitate app development for research across NIH. A hub where researchers share best practices could serve as a service model to provide key oversight or other functionality requested by NIH-funded researchers, and to document and disseminate best practices of and theory-based findings from app research.

To enhance the scale of evidence-based app interventions, it may be necessary to have privately or publicly funded dissemination programs. The US Center for Disease Control’s (CDC) Evidence-Based Interventions for HIV Prevention (EBI) is a useful example of such a program. The EBI program currently houses over 120 interventions that have been demonstrated to reduce HIV transmission or improve care outcomes for those living with HIV. Dedicated funding is used to disseminate these interventions, which for non-electronic programs has included development of intervention materials such as binders, pamphlets, videos, and other printed materials as well as ongoing provision of technical assistance. None of these EBI interventions are solely or even predominantly app-driven. A similar program for evidence-based apps could provide substantial utility, with translation and maintenance costs borne by the program. Such a program could be supported by CDC or alternate funding sources such as the National Institutes of Health or private foundations. Structured and dedicated funding would allow and empower health departments and community organizations to access evidence-based app programs, and would facilitate the visibility of app interventions via their inclusion in a publicly-funded, evidence-based compendium.

Conclusions

Mobile app health research is a promising avenue for health promotion, yet its implementation comes with many new challenges. We describe some of these and discuss strategies to address them. Investing resources in app research may facilitate its development, impact, and dissemination, allowing it to fulfill its substantial promise.

Acknowledgments

Funding: This work was supported by the National Institute of Mental Health (R01MH114692), the Adolescent Medicine Trials Network for HIV/AIDS Interventions (Protocol 159) from the National Institutes of Health (U19HD089881), and the National Institute of Allergy and Infectious Diseases (R01AI143875). The work was facilitated by the Emory Center for AIDS Research (P30AI050409). The contents are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/ .

Provenance and Peer Review: This article was commissioned by the Guest Editor (Lisa Hightow-Weidman) for the series “Technology-based Interventions in HIV Prevention and Care Continuum among American Youth” published in mHealth . The article has undergone external peer review.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/mhealth-19-263 ). The series “Technology-based Interventions in HIV Prevention and Care Continuum among American Youth” was commissioned by the editorial office without any funding or sponsorship. LHW served as the unpaid Guest Editor of the series. Dr. Hightow-Weidman reports grants from NICHD, during the conduct of the study. The authors have no other conflicts of interest to declare.

  • Open access
  • Published: 09 August 2021

The use of mobile applications in higher education classes: a comparative pilot study of the students’ perceptions and real usage

  • David Manuel Duarte Oliveira   ORCID: orcid.org/0000-0002-8763-6997 1 ,
  • Luís Pedro 1 &
  • Carlos Santos 1  

Smart Learning Environments volume  8 , Article number:  14 ( 2021 ) Cite this article

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This paper was developed within the scope of a PhD thesis that intends to characterize the use of mobile applications by the students of the University of Aveiro during class time. The main purpose of this paper is to present the results of an initial pilot study that aimed to fine-tune data collection methods in order to gather data that reflected the practices of the use of mobile applications by students in a higher education institution during classes. In this paper we present the context of the pilot, its technological settings, the analysed cases and the discussion and conclusions carried out to gather mobile applications usage data logs from students of an undergraduate degree on Communication Technologies.

Our study gathered data from 77 participants, taking theoretical classes in the Department of Communication and Arts at the University of Aveiro. The research was based on the Grounded Theory method approach aiming to analyse the logs from the access points of the University. With the collected data, a profile of the use of mobile devices during classes was drawn.

The preliminary findings suggest that the use of apps during the theoretical classes of the Department of Communication and Art is quite high and that the most used apps are Social networks like Facebook and Instagram. During this pilot the accesses during theoretical classes corresponded to approximately 11,177 accesses per student. We also concluded that the students agree that accessing applications can distract them during these classes and that they have a misperception about their use of online applications during classes, as the usage time is, in fact, more intensive than what participants reported.

Introduction

The use of mobile devices by higher education students has grown in the last years (GMI, 2019 ). Technological advancements are also pushing society with consequent rapidly changing environments. Higher Education Institutions (HEIs) are not exempted from these technological changes and advancements, and it is compulsory that they follow this technological evolution so that the teaching-learning process is improved and enriched.

HEI’s are trying to integrate digital devices such as mobile phones and tablets, and informal learning situations, assuming that the use of these technologies may result in a different learning approach and increase students’ motivation and proficiency (Aagaard, 2015 ).

In a study by Magda, & Aslanian ( 2018 ), students report that they access course documents and communicate with the faculty via their mobile devices, such as smartphones. Over 40% say they perform searches for reports and access institutions E-Learning systems via mobile devices (Magda, & Aslanian, 2018 ). The EDUCAUSE Horizon Report - 2019 Higher Education Edition (Alexander et al., 2019 ) also mentions M-Learning as the main development in the use of technology in higher education. However, teachers believe students use their gadgets less than they actually do, and mobile devices also challenge teaching practices. Students use devices for off-task (Jesse, 2015 ) or parallel activities and there may be inaccurate references to their actual use of mobile devices.

Mobile device users have very different usage habits of their devices and their applications, and it is important to study and characterize these behaviours in different contexts, as explained below. The reports that usually support these studies are made with questions directed to the users themselves asking them questions about the apps they have on the devices and the reasons for using them. However, Gerpott & Thomas ( 2014 ) argue that other types of studies are needed to properly support this type of research.

Studies are usually conducted in organizations, based on the opinion of the participants, and cannot be replicated and generalized, for example, regarding the use of the internet or mobile applications by the general public, because these devices, unlike desktop devices, can be used anywhere and at any time (Gerpott & Thomas, 2014 ).

Furthermore, in mobile contexts, it becomes difficult for people to remember what they have used, because mobile applications can be used for various tasks, in various contexts, whether professional or personal, and the variety of applications, the use made, the periods of use are usually so wide and differentiated, that it can become difficult for users to refer which services or applications they have used, under which circumstances and how often. (Boase & Ling, 2013 ).

Thus, it is relevant, for several areas and especially for this research area, to have studies that cross-reference reported usage with actual usage. One of the ways to achieve this is with the use of logs of the use of mobile devices and applications, as mentioned by De Reuver & Bouwman ( 2015 ):

Using this approach this pilot study aims to create and validate a methodology:

i) to show the profile of these users,

ii) to reveal the kind of applications they use in the classroom and when they are in the institutions,

iii) and also, to compare the users’ perceptions with the real use of mobile applications.

Knowing the real usage and the usage students mention may provide valuable insights to teachers and HEIs and use this data for decision making about institutional applications to support students and teachers in their teaching and learning activities. Such information can also bring insights on the integration of M-Learning strategies, promoting interaction, communication, access to courses and the completion of assignments using students’ devices.

The central focus of this study is, therefore, to show preliminary results of the use of applications by students in class time during theoretical classes, through logs collected during class time.

The paper is divided into five parts. In the first part, relevant theoretical considerations are addressed, having in mind the current state of the art in terms of the literature and empirical work in this field. The second part outlines the study methodology. In the third part, the technological setting is highlighted. The cases and the results of the data analysis are described in the fourth part. Lastly, the results are interpreted, connected and crossed with the preliminary considerations.

Literature review

The massive use of mobile devices has created new forms of social interaction, significantly reducing the spatial difficulties that could exist, and today people can be reached and connected anytime and anywhere (Monteiro et al., 2017 ). This also applies to the school environment, where students bring small devices (smartphones, tablets and e-book readers) with them, which, thanks to easy access to an Internet connection, keep them permanently connected, even during classes.

In HEIs there is also a growing tendency among members of the academic community to use mobile devices in their daily activities (Oliveira et al., 2017 ), and students expect these devices to be an integral part of their academic tasks, too (Dobbin et al., 2011 ). A great number of users take advantage of mobile devices to search information and, since they do not always have computers available, these devices allow them an easy access to academic and institutional information (Vicente, 2013 ).

One of the challenges educational institutions face today has to do with the ubiquitous character of these devices and with finding ways in which they can be useful for learning, thus approaching a new educational paradigm: Mobile Learning (M-Learning) (Ryu & Parsons, 2008 ).

M-learning allows learning to take place in multiple places, in several ways and when the learner wants to learn. As learning does not necessarily have to occur within school buildings and schedules, M-Learning reduces the limitations of learning confined to the classroom (Sharples, M., Corlett, D. & Westmancott,  2002 ), leading UNESCO to consider that M-Learning, in fact, increases the reach of education and may promote equality in education (UNESCO, 2013 ). The EDUCAUSE Horizon Report - 2019 Higher Education Edition (Alexander et al., 2019 ) also mentions M-Learning as the main development in the use of technology in higher education and, therefore, it becomes increasingly relevant to rethink learning spaces in a more open perspective, both physically and methodologically, namely through mobile learning that places the student at the centre of the learning process.

Quite often studies that intend to determine the use of mobile applications focus on general questions, but the most common ones are related to the frequency and duration of the use of these devices, for example, questions such as “how many SMS or calls are made?” or “how often do you use the device?”

In fact, instruments like questionnaires are widely used in this type of studies. However, since mobile devices are completely integrated in our daily life and we use them quite extensively, it is difficult to retain and define with plausible accuracy the actual use that we make of them.

It is therefore relevant to effectively understand how these students use these devices, more specifically the applications installed on them. To this end, most studies have been based on designs that are focused on the users’ perceptions and based are on these reports.

Thus, it was important to understand if what users report using corresponds to what they actually use, and if this use does not occur for distraction or entertainment, for example.

Considering the above, some studies have focused on the validity of the use of these instruments. One of these first studies, carried out by Parslow et al. ( 2003 ), aimed at determining the number of calls made and received in the days, weeks or months preceding the date of the questionnaire, and their duration. The answers were compared with the logs of the operators and it was concluded that self-report questionnaires do not always represent the actual pattern of use.

Finally, in self-report instruments, which refer to questions of daily activity on mobile devices, this activity may not represent a general pattern of activity, since from individual to individual the patterns of daily use may vary considerably and thus reflect a very irregular use.

In a study by Boase & Ling ( 2013 ), the authors mentioned that about 40% of studies on mobile device use, based on articles published in journals (41 articles between 2003 and 2010), are based on questionnaires.

The questions asked aim to estimate how long or what type of use they have made of their devices on a daily basis, and sometimes aim to know about time periods of several days. In most of these studies, 40% of papers use at least one measure of frequency of use and 27% a measure of duration of use that users make. Another factor that is mentioned is that users do not always report their usage completely accurately. On the other hand, the same study mentions that users may over or under report the use they make for reasons of sociability (Boase & Ling, 2013 ).

Given the moderate correlation between self-report instruments and data from records or logs (Boase & Ling, 2013 ), the author considers that researchers can significantly improve the results if they use, together with other instruments, data from logs to make their studies more accurate and rigorous. Another suggestion would be the use of mobile applications that record these usage behaviours (Raento et al., 2009 ).

Indeed, this kind of instrument is widely used in this type of studies. However, given that mobile devices are fully integrated into our daily lives and we use them quite extensively, it becomes difficult to retain and define with plausible accuracy the use we make of them. In addition to the factors mentioned in the previous paragraph, it is important that these types of studies are validated with other methods, such as the use of logs, as presented in this study. The logs in this study refer to the capture records of the mobile device traffic made by the students.

This article therefore aims to present preliminary results with an approach that uses cross-checking of log data with questionnaire results.

Methodology

This article intends to present and discuss preliminary results of a study that aims to characterize the use of mobile applications at the University of Aveiro through collected logs, crossing its results with questionnaires answered by students during the classes, and also with an observation grid with data from the analysed class and questions to teachers related to what teachers recommend regarding the use of mobile phones during class time.

The research question that motivated this article is: which digital applications/services are most frequently used on mobile devices by the students of the University of Aveiro during their classes?

The study was composed of 40 students, that answered the questionnaires.

The research was based on the Grounded Theory method aiming to analyse the logs from the access points of the University. With the collected data, a usage profile of mobile devices during classes was drawn.

Figure  1 presents a diagrammatic representation of the created methodological process.

figure 1

General diagram of the study

Therefore 3 instruments were used for the data collection: a questionnaire, an observation grid and logs collected through mobile traffic in the wi-fi network of the university.

The questionnaire allowed for a quantitative assessment of the profile of the participants and collected data on the use that participants claimed to make of their mobile devices. The observation grid served as a guide for the implementation of the study, allowing to record data on the classes where the collections took place and to verify whether certain items were present, such as permission to use mobile devices or planning to use them by teachers. The observation grid would also serve to make the link between use and content in class, but in this pilot, it was not possible to make this link between the class content and the usage of mobile applications, because the author could not observe the applications used by students.

The database containing the usage records enabled the analysis of the logs, resulting in the quantification and verification of the type of activity that each (anonymous) participant made of their device.

The 3 instruments used aimed to i) determine which application(s) students were really using during the classes, through the analysis of the data logs collected from the Wi-Fi network of the University; ii) identify the participants’ representations of their activities by means of several questions regarding mobile usage during class time; iii) observe students’ behaviour and focus via an observation grid that was used by the researcher/observer when he was attending the classes.

The group who participated in this pilot study was selected in accordance with the professors and classes available, so it is considered a convenience sample. The group was constituted by students of undergraduate classes from the Communication and Arts Department of the University of Aveiro.

Table  1 summarizes the schedule of the pilots carried out, the curricular units where they took place, their duration and the instruments used. For ease of management, all the pilots took place in the same department of the University.

The Table  2 summarizes the collected data from questionnaires and logs.

This pilot aimed to build an approach to data analysis, close to the Grounded Theory methodology, in which a provisional theory is built based on the observed and analysed data (Alves et al., 2017 ; Long et al., 1993 ). The data collected in this pilot will serve to define a more complete methodology to be used in a larger study.

This chapter is divided into three parts: context, technological setting and cases analysed. In the context part, the classes which are part of the study will be described, relating the answers from the questionnaires with the teachers’ recommendations about the use of mobile devices. In the technological scenario section, it is intended to describe the technological background underlying the collection process of the logs and in the last part, analysed cases, the objective was to validate if the data to be collected matched the outlined objectives.

In the questionnaire, the questions were divided into two main groups: aspects related to the participant’s profile and aspects directly related to the use of the applications. Aspects related to participants were intended to characterize them. Regarding the use of applications, we aimed to find out the students’ perception of the applications they use in their daily routine, inside and outside of the classroom, and how they do it. Data were collected using a Google Forms form and processed using Microsoft Excel.

In this subchapter, through the data collected from the students’ answers to the questionnaires, and by crossing this information with the data collected from the teachers in the observation grid, we try to describe the context of the pilot.

All of the teachers stated that they allowed their students to use mobile phones during class time, but that they did not plan that use. They also stated that in most part of the classes several students use their mobile phones and apps to search for class related materials. The teachers also showed curiosity about knowing, with more detail, the mobile phone use their students actually have.

In the three classes analysed (Aesthetics, Scriptwriting and Music in History and Culture), when asked about the possibility of using mobile applications as a pedagogical complementary resource 43%, 47% and 55% of students fully agreed that these should be used. In these three classes, 31%, 44%, and 67% of students showed a more moderate opinion: they agreed (but not in such an assertive way) that these should be used.

Another conclusion is that most of the students used a smartphone (88,9%, 75%, 52%) during class time, but many of them also used a computer (66,7%, 100%, 84%). The percentage use of tablets is much lower (11,1%, 0%, 15%).

In the analysed scenario, the majority of the students used the android operating system and 94% also agreed that mobile applications could help to manage the academic tasks, except in the case of the “Aesthetics Curricular Unit”.

When it comes to the time of use, per week, in classes, 53%, 58%, and 22% of the students answered they used these devices between 4 to 5 days a week and 15%, 40% and 70% said they used them between 1 to 3 days a week.

Students were also asked about how frequently they accessed mobile applications during class time and, in all, 77% of the respondents reported accessing apps at least between 1 to 5 times per class. About 20% referred they accessed apps from 6 to 10 times per class.

As for the purposes of accessing apps during classes, most students mentioned categories related i) to support the class / to research (70%, 100%, 77,8%), ii) to access institutional platforms (47.4%, 66.7%, 89, 9%), iii) to access to information (47.4%, 50%, 66.7%) and iv) to work (36.8%, 50%, 44.4%).

Interestingly, the categories communication (52.6%, 41.7%, 22.3%), collaboration (10.5%, 16.7%, 0%), access to institutional services (5.3%, 0% 0%) and “I do not use them” (10.5%, 0%, 0%) presented very low percentages, namely the last one.

When questioned about the use of mobile devices that did not include academic reasons, many students referred to the categories “to be linked/connected” or “to be updated” (42.1%, 66.7%, 33.3%), “to communicate” (57.7% 75.7%, 66.7%), “to share and access content” (31.6%, 58.3%, 33.3%), but few mentioned “for entertainment” (26.3%, 16.7%, 22.2%), “as a habit or routine” (10.5%, 41.7%, 11.1%) and “I do not use them” (10.5%, 0%, 11.1%).

When asked about which mobile applications are most used in an academic context, the most relevant category was “to research / to study” (73.7%, 58.3%, 89.9%), “to check the calendar” (31.6%, 25%, 66.7% %) and “to surf the web” (47.4%, 50%, 55.6%). Again, categories such as “to work” (36.8%, 33.3%, 33.3%), “to take notes” (26,2%, 33.3%, 55.6%) and “to create content” (31.6%, 25%, 11.1%) presented relatively low percentages. It should also be noted that the respondents presented answers that created categories which were not expected such as “to watch films” (10.5%, 8.3%, 0%), “to listen to music” (31.6%, 33.3%, 33.3%), “to take photos” (10.5%, 0%, 0%) and “to play games” (5.3%, 0%, 0%) All the students said that they used applications during classes in at least one of the categories. In fact, in the three courses no one stated “not to use them” (0% in all).

When asked about the teachers’ permission to use the mobile devices in the classroom, most of the students said that teachers allowed free use (52.6%, 100%, 77.8%). Only a few stated that teachers allowed using them specifically when planned (41, 1%, 0%, 22.2%). The respondents of one course stated that teachers did not allow the use of devices (Aesthetics - 5.3%). Finally, when asked about the usefulness of integrating mobile applications in class, there was an overwhelming majority of respondents (100%, 78,9%, 100%) saying they believed that such integration could be enriching and useful.

Below is presented a table describing the most used mobile apps during class activities. It should be noted that only the two answers with the greatest relevance for each category were considered.

Table  3 systematizes what the results have been showing until now: there is an important part of students that use mobile phones during their classes and, even when teachers advise them not to use them, they ignore the recommendations and use them anyway. The main purposes stated were: to be in contact with others through social networking but also to access different kinds of information in browsers. Moreover, the classes where the use of devices is not recommended by the teachers seems to be the one where some applications are most used.

Technological setting

In this section we intend to describe the technological background underlying the process of collecting the logs. The first goal was to register and capture logs from the wi-fi network of the university, which consists of a wireless network that users can access using their universal user credentials.

In order to do that a meeting was scheduled with the university’s technology services, as our main concern was the anonymization of the data collected in order (i) to confer more neutrality to the data treatment, and (ii) to comply with European data protection legislation. Another issue for discussion was the need of powerful machines so that they could process the large amount of data collected.

In this meeting the necessary steps were agreed in order to guarantee the users’ privacy, the authorization of the university’s central services to do the study and the registration method of the logs. The overall procedure demanded several experiences of data collection to fine-tune the final pilot, which works as the basis capture setting for all the main study.

The Wi-Fi traffic capture software (Wireshark) was selected to work both with Android and IOS devices and it was possible to understand the functionalities of the software.

The pilot also helped to understand and solve additional problems that appeared during the previous tests, related to the anonymization of the users’ data. It was necessary to ensure that the users’ personal data were not identifiable, which was a commitment: in fact, only HTTPS Footnote 1 traffic was captured, being all the other information encrypted.

After the first tests, an initial data collection pilot took place in a classroom context. A specific capture system was created to allow the capture of mobile application logs used only by a certain group of students, from a designated Curricular Unit. A specific scenario was set up to ensure that only those students communicating through the IP Footnote 2 defined for the scenario and during that class time were considered and treated under the scope of this study:

If the traffic of the concerned student is communicating through one of the APs (Access Points) covering the room, then the device will be assigned a “Room network” IP;

If the student’s traffic is not communicating through one of the APs covering the room, then the device will be assigned a “Non Room network” IP;

If the student traffic does not belong to the group to be analysed and the device in question is communicating through one of the APs covering the room, then the device will be assigned an IP from a “normal eduroam network”;

In the final steps we resolved the IP’s in Wireshark (software used for the capture) and the unsolved IP’s where filtered in a PHP Footnote 3 script, through the gethostbyaddr method where the unsolved ones are incrementally added.

Finally, using an IP list, we performed a comparison to resolve any unresolved names;

This step allowed to fine tune the process and to make the final test.

Analysed cases

After performing these tests, a scenario for this final pilot was set up to validate if the data to be collected matched the outlined objectives. In this final pilot, logs were collected in a classroom so that the scenario was as close to the desired collection as possible. In this pilot, it was possible to verify that the collected data fulfilled the requirements. At this point, in addition to the HTTPS traffic packets, the packets referring to DNS Footnote 4 traffic were also included. This option made the HTTPS traffic more easily understandable. Furthermore, the researcher could conclude that all authenticated devices belonged to separate accounts.

The results show that the pre-tests/pilots and the final pilot turned out very well and in a very reliable way since they allowed to verify the main problems that could occur and helped to certify that the traffic anonymity condition was respected. In fact, only the HTTPS was considered, and all other communication was encrypted with no risk of corruption of private data. Moreover, this option had an important justification: the fact that HTTPS traffic could be more easily understandable and the fact that it allowed certifying that all the authenticated devices of the wireless network belonged to separate accounts.

To process and create output visualization of the data, the choice was an integrated solution, both for the processing stage and for creating visualisations. Given the variety of tools available, several were tried out and Tableau Software® (Tableau Prep® and Tableau Desktop®) was chosen. Tableau Software is an interactive data processing and visualisation tool that belongs to the Salesforce company and, although it is paid software, it allows for an academic licence that was used in this project.

This solution, besides allowing working with a large amount of data, also allows for a very interactive data treatment and visualisation. This software also allows the importation of data from various sources, which in the case of this study was also an advantage.

This solution allowed us to work with large amounts of data but it also allowed for a very interactive data treatment and visualization. In the case of Tableau Prep, the file with the logs was imported in a CSV format Footnote 5 and treated iteratively in a dynamic way, being refined to the desired data in a second stage. As an example, we can mention the separation of the field “time duration” in hours, minutes and seconds fields; all the IPs were converted to a generic name “student”; all the destinations visited by the students were grouped in main categories, as for instance “Facebook”, as each application had numerous distinct destinations.

About 30 changes in data treatment and in data flow “cleaning” were performed, which were, later, exported to Tableau Desktop. Each file imported to Tableau Prep, in addition to the changes applied to the previous file, was refined with more changes, in an iterative process.

After treating the data on Tableau prep the generated data flow was imported to Tableau Desktop so that dynamic data visualizations were created. At this stage, dimensions, measurements, and filters were created according to the desired data visualization. The software has the big advantage of creating dynamic visualizations of the logs’ data which allows for a different and richer perspective on the data obtained, in order to deepen further studies about the same topic.

Discussion and conclusions

This paper aimed to describe the process of a pilot to carry out a larger study where we wanted to cross-reference actual usage data (logs) of mobile applications in the classroom with data from student questionnaires. In this article we also present the main results of this pilot, both from the point of view of the process of the pilot and from the point of view of the data of use of mobile applications by students in the classroom.

From the preliminary data analysis of this pilot, we can infer that the most used apps are Facebook, Google and Instagram, as we can see in Fig.  2 and Fig.  3 , although some variations between the attendees of the courses were registered when it comes to other apps. For example, in the case of the Design course, there are alternative apps being used such as YouTube or Vimeo.

figure 2

General use of applications in Scriptwriting class

figure 3

General use of applications in Aesthetics classe

Another noticeable preliminary result is that students use Facebook more at the beginning of classes and Instagram is used more at the end, as we can see in Fig.  4 and Fig.  5 .

figure 4

Use of Facebook per hour in Scriptwriting class

figure 5

Use of Instagram per hour in Scriptwriting class

In addition, the developed model was used in the main study with a bigger convenience sampling approach, which may provide a more accurate representation of the population of mobile-phone-users in the study field.

The visualizations created in a dynamic way during this study showed that the use of logs as a complementary data provider to other instruments, such as questionnaires, can be an added value for this research field.

On the other hand, this pilot contradicts (sometimes slightly, others considerably) the results of the questionnaires answered by the students and whose logs were collected and analysed. Logs show that:

there is a common use of mobile applications during the classes;

the purpose of the access is different: participants report that they use mobile applications mostly for academic reasons, but it can be noted that there is a general use of other mobile applications such as social networks and Youtube;

the usage time is much longer than what participants reported;

the frequency is also different: students stated that they use mobile applications in classes only 1–3 days a week, but we found that, in the analysed classes, there is an almost constant use of them, and finally

students report that they do not use social networks much in class, but the use is, in fact, massive.

The students’ perception of the “use of mobile devices and applications during lessons”, and as already mentioned, during a teaching activity - 70% of the students refer using the applications between 1 to 5 times, 22% between 6 to 10 times and 4% more than 10 times. It should also be noted, as previously mentioned, that only 4% mention not using them. With regards to the use during the week, 56% of the students refer using them between 4 to 5 days per week and 39% between 1 to 3 days per week. There is also a relatively low percentage of students mentioning that they use the devices during class more than ten times (4%).

However, analysis of the logs shows that this use appears to be much more intensive. We performed a calculation based on the average number of accesses, from which we removed 40% of potential automatic accesses and divided by the average number of accesses each application had in the initial test. The results present 6.6 accesses to the device per class/student in the class with the fewest accesses, and for the highest case, 313 accesses to the device per class/student.

This result is reinforced by results from other studies, such as the Mobile Survey Report, which states that students make regular use of laptops and smartphones during lessons (Seilhamer et al., 2018 ).

These conclusions lead us to some very serious insights on this subject. Apparently, even older students have a misperception of their use of online applications during classes. There is a serious discrepancy and incongruency between the behaviours that they claim to adopt and those they actually engage in during the classes. There are authors, who argue for the need for other types of studies that support this type of approach (Gerpott & Thomas, 2014 ), because the perception reported by users may not correspond to the actual use. It means that this gap deserves a deeper reflection. Why does it happen? Are students not motivated in higher education? Is the world offered online more interesting than the one in the physical campus? We will try to answer these questions in the main study.

Availability of data and materials

Some of the visualizations created are publicly available at https://public.tableau.com/profile/davidoliveiraua

HTTPS It is a protocol used for secure communication over a computer network, and is widely used on the Internet

IP is the s a numerical label assigned to each device connected to a computer network that uses the Internet Protocol for communication

PHP is a general-purpose scripting language especially suited to web development

DNS is naming system for computers, services, or other resources connected to the Internet

Unformatted file where values are separated by commas

Abbreviations

Higher Education Institutions

Access Points

Hypertext Transfer Protocol Secure

Internet Protocol

Hypertext Preprocessor

Domain Name System

Comma-separated values

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David Manuel Duarte Oliveira, Luís Pedro & Carlos Santos

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DO wrote the introduction and discussion, and saw to the article structure, wrote the method section and conducted the data analysis. LP and CS conducted the literature review. All authors contributed to the discussion and conclusion sections, and the overall flow of the article. All authors read and approved the final manuscript.

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Oliveira, D.M.D., Pedro, L. & Santos, C. The use of mobile applications in higher education classes: a comparative pilot study of the students’ perceptions and real usage. Smart Learn. Environ. 8 , 14 (2021). https://doi.org/10.1186/s40561-021-00159-6

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Creating video from text.

Sora is an AI model that can create realistic and imaginative scenes from text instructions.

We’re teaching AI to understand and simulate the physical world in motion, with the goal of training models that help people solve problems that require real-world interaction.

Introducing Sora, our text-to-video model. Sora can generate videos up to a minute long while maintaining visual quality and adherence to the user’s prompt.

Today, Sora is becoming available to red teamers to assess critical areas for harms or risks. We are also granting access to a number of visual artists, designers, and filmmakers to gain feedback on how to advance the model to be most helpful for creative professionals.

We’re sharing our research progress early to start working with and getting feedback from people outside of OpenAI and to give the public a sense of what AI capabilities are on the horizon.

Sora is able to generate complex scenes with multiple characters, specific types of motion, and accurate details of the subject and background. The model understands not only what the user has asked for in the prompt, but also how those things exist in the physical world.

The model has a deep understanding of language, enabling it to accurately interpret prompts and generate compelling characters that express vibrant emotions. Sora can also create multiple shots within a single generated video that accurately persist characters and visual style.

The current model has weaknesses. It may struggle with accurately simulating the physics of a complex scene, and may not understand specific instances of cause and effect. For example, a person might take a bite out of a cookie, but afterward, the cookie may not have a bite mark.

The model may also confuse spatial details of a prompt, for example, mixing up left and right, and may struggle with precise descriptions of events that take place over time, like following a specific camera trajectory.

We’ll be taking several important safety steps ahead of making Sora available in OpenAI’s products. We are working with red teamers — domain experts in areas like misinformation, hateful content, and bias — who will be adversarially testing the model.

We’re also building tools to help detect misleading content such as a detection classifier that can tell when a video was generated by Sora. We plan to include C2PA metadata in the future if we deploy the model in an OpenAI product.

In addition to us developing new techniques to prepare for deployment, we’re leveraging the existing safety methods that we built for our products that use DALL·E 3, which are applicable to Sora as well.

For example, once in an OpenAI product, our text classifier will check and reject text input prompts that are in violation of our usage policies, like those that request extreme violence, sexual content, hateful imagery, celebrity likeness, or the IP of others. We’ve also developed robust image classifiers that are used to review the frames of every video generated to help ensure that it adheres to our usage policies, before it’s shown to the user.

We’ll be engaging policymakers, educators and artists around the world to understand their concerns and to identify positive use cases for this new technology. Despite extensive research and testing, we cannot predict all of the beneficial ways people will use our technology, nor all the ways people will abuse it. That’s why we believe that learning from real-world use is a critical component of creating and releasing increasingly safe AI systems over time.

Research techniques

Sora is a diffusion model, which generates a video by starting off with one that looks like static noise and gradually transforms it by removing the noise over many steps.

Sora is capable of generating entire videos all at once or extending generated videos to make them longer. By giving the model foresight of many frames at a time, we’ve solved a challenging problem of making sure a subject stays the same even when it goes out of view temporarily.

Similar to GPT models, Sora uses a transformer architecture, unlocking superior scaling performance.

We represent videos and images as collections of smaller units of data called patches, each of which is akin to a token in GPT. By unifying how we represent data, we can train diffusion transformers on a wider range of visual data than was possible before, spanning different durations, resolutions and aspect ratios.

Sora builds on past research in DALL·E and GPT models. It uses the recaptioning technique from DALL·E 3, which involves generating highly descriptive captions for the visual training data. As a result, the model is able to follow the user’s text instructions in the generated video more faithfully.

In addition to being able to generate a video solely from text instructions, the model is able to take an existing still image and generate a video from it, animating the image’s contents with accuracy and attention to small detail. The model can also take an existing video and extend it or fill in missing frames. Learn more in our technical report .

Sora serves as a foundation for models that can understand and simulate the real world, a capability we believe will be an important milestone for achieving AGI.

All videos on this page were generated directly by Sora without modification.

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Mobile Application Development: Practice and Experience pp 1–9 Cite as

A Survey on Mobile Application Development Models

  • A. N. Shwetha 6 ,
  • R. Sumathi 6 &
  • C. P. Prabodh 6  
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Nowadays, due to the advancement in technology of mobile applications, smart phones/mobiles phones became part of our day-to-day life. People are using smart phones for their day-to-day activities like to read news, to play games, for shopping, browsing, etc. This increases demand for development of mobile applications. The developers have to choose appropriate application development model and develop high quality software’s on time with less budget. For this, knowledge of app development model plays an important role. The mobile applications are different from web applications in the amount of resource utilization, because the number of resources available in mobile phones will be less compared to computers. In this paper, a review is conducted to find, analyze, compare and contrast various mobile app development models and the software development methodology needs to be followed while developing mobile applications.

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Kaur, A., Kaur, K.: Systematic literature review of mobile application development and testing effort estimation. J. King Saud Univ. Comput. Inf. Sci. (2018)

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Shwetha, A.N., Sumathi, R., Prabodh, C.P. (2023). A Survey on Mobile Application Development Models. In: Singh, J., Das, D., Kumar, L., Krishna, A. (eds) Mobile Application Development: Practice and Experience. Studies in Systems, Decision and Control, vol 452. Springer, Singapore. https://doi.org/10.1007/978-981-19-6893-8_1

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Article Contents

Introduction, 1 installed capacity and application of solar energy worldwide, 2 the role of solar energy in sustainable development, 3 the perspective of solar energy, 4 conclusions, conflict of interest statement.

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Ali O M Maka, Jamal M Alabid, Solar energy technology and its roles in sustainable development, Clean Energy , Volume 6, Issue 3, June 2022, Pages 476–483, https://doi.org/10.1093/ce/zkac023

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Solar energy is environmentally friendly technology, a great energy supply and one of the most significant renewable and green energy sources. It plays a substantial role in achieving sustainable development energy solutions. Therefore, the massive amount of solar energy attainable daily makes it a very attractive resource for generating electricity. Both technologies, applications of concentrated solar power or solar photovoltaics, are always under continuous development to fulfil our energy needs. Hence, a large installed capacity of solar energy applications worldwide, in the same context, supports the energy sector and meets the employment market to gain sufficient development. This paper highlights solar energy applications and their role in sustainable development and considers renewable energy’s overall employment potential. Thus, it provides insights and analysis on solar energy sustainability, including environmental and economic development. Furthermore, it has identified the contributions of solar energy applications in sustainable development by providing energy needs, creating jobs opportunities and enhancing environmental protection. Finally, the perspective of solar energy technology is drawn up in the application of the energy sector and affords a vision of future development in this domain.

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With reference to the recommendations of the UN, the Climate Change Conference, COP26, was held in Glasgow , UK, in 2021. They reached an agreement through the representatives of the 197 countries, where they concurred to move towards reducing dependency on coal and fossil-fuel sources. Furthermore, the conference stated ‘the various opportunities for governments to prioritize health and equity in the international climate movement and sustainable development agenda’. Also, one of the testaments is the necessity to ‘create energy systems that protect and improve climate and health’ [ 1 , 2 ].

The Paris Climate Accords is a worldwide agreement on climate change signed in 2015, which addressed the mitigation of climate change, adaptation and finance. Consequently, the representatives of 196 countries concurred to decrease their greenhouse gas emissions [ 3 ]. The Paris Agreement is essential for present and future generations to attain a more secure and stable environment. In essence, the Paris Agreement has been about safeguarding people from such an uncertain and progressively dangerous environment and ensuring everyone can have the right to live in a healthy, pollutant-free environment without the negative impacts of climate change [ 3 , 4 ].

In recent decades, there has been an increase in demand for cleaner energy resources. Based on that, decision-makers of all countries have drawn up plans that depend on renewable sources through a long-term strategy. Thus, such plans reduce the reliance of dependence on traditional energy sources and substitute traditional energy sources with alternative energy technology. As a result, the global community is starting to shift towards utilizing sustainable energy sources and reducing dependence on traditional fossil fuels as a source of energy [ 5 , 6 ].

In 2015, the UN adopted the sustainable development goals (SDGs) and recognized them as international legislation, which demands a global effort to end poverty, safeguard the environment and guarantee that by 2030, humanity lives in prosperity and peace. Consequently, progress needs to be balanced among economic, social and environmental sustainability models [ 7 ].

Many national and international regulations have been established to control the gas emissions and pollutants that impact the environment [ 8 ]. However, the negative effects of increased carbon in the atmosphere have grown in the last 10 years. Production and use of fossil fuels emit methane (CH 4 ), carbon dioxide (CO 2 ) and carbon monoxide (CO), which are the most significant contributors to environmental emissions on our planet. Additionally, coal and oil, including gasoline, coal, oil and methane, are commonly used in energy for transport or for generating electricity. Therefore, burning these fossil fuel s is deemed the largest emitter when used for electricity generation, transport, etc. However, these energy resources are considered depleted energy sources being consumed to an unsustainable degree [ 9–11 ].

Energy is an essential need for the existence and growth of human communities. Consequently, the need for energy has increased gradually as human civilization has progressed. Additionally, in the past few decades, the rapid rise of the world’s population and its reliance on technological developments have increased energy demands. Furthermore, green technology sources play an important role in sustainably providing energy supplies, especially in mitigating climate change [ 5 , 6 , 8 ].

Currently, fossil fuels remain dominant and will continue to be the primary source of large-scale energy for the foreseeable future; however, renewable energy should play a vital role in the future of global energy. The global energy system is undergoing a movement towards more sustainable sources of energy [ 12 , 13 ].

Power generation by fossil-fuel resources has peaked, whilst solar energy is predicted to be at the vanguard of energy generation in the near future. Moreover, it is predicted that by 2050, the generation of solar energy will have increased to 48% due to economic and industrial growth [ 13 , 14 ].

In recent years, it has become increasingly obvious that the globe must decrease greenhouse gas emissions by 2050, ideally towards net zero, if we are to fulfil the Paris Agreement’s goal to reduce global temperature increases [ 3 , 4 ]. The net-zero emissions complement the scenario of sustainable development assessment by 2050. According to the agreed scenario of sustainable development, many industrialized economies must achieve net-zero emissions by 2050. However, the net-zero emissions 2050 brought the first detailed International Energy Agency (IEA) modelling of what strategy will be required over the next 10 years to achieve net-zero carbon emissions worldwide by 2050 [ 15–17 ].

The global statistics of greenhouse gas emissions have been identified; in 2019, there was a 1% decrease in CO 2 emissions from the power industry; that figure dropped by 7% in 2020 due to the COVID-19 crisis, thus indicating a drop in coal-fired energy generation that is being squeezed by decreasing energy needs, growth of renewables and the shift away from fossil fuels. As a result, in 2020, the energy industry was expected to generate ~13 Gt CO 2 , representing ~40% of total world energy sector emissions related to CO 2 . The annual electricity generation stepped back to pre-crisis levels by 2021, although due to a changing ‘fuel mix’, the CO 2 emissions in the power sector will grow just a little before remaining roughly steady until 2030 [ 15 ].

Therefore, based on the information mentioned above, the advantages of solar energy technology are a renewable and clean energy source that is plentiful, cheaper costs, less maintenance and environmentally friendly, to name but a few. The significance of this paper is to highlight solar energy applications to ensure sustainable development; thus, it is vital to researchers, engineers and customers alike. The article’s primary aim is to raise public awareness and disseminate the culture of solar energy usage in daily life, since moving forward, it is the best. The scope of this paper is as follows. Section 1 represents a summary of the introduction. Section 2 represents a summary of installed capacity and the application of solar energy worldwide. Section 3 presents the role of solar energy in the sustainable development and employment of renewable energy. Section 4 represents the perspective of solar energy. Finally, Section 5 outlines the conclusions and recommendations for future work.

1.1 Installed capacity of solar energy

The history of solar energy can be traced back to the seventh century when mirrors with solar power were used. In 1893, the photovoltaic (PV) effect was discovered; after many decades, scientists developed this technology for electricity generation [ 18 ]. Based on that, after many years of research and development from scientists worldwide, solar energy technology is classified into two key applications: solar thermal and solar PV.

PV systems convert the Sun’s energy into electricity by utilizing solar panels. These PV devices have quickly become the cheapest option for new electricity generation in numerous world locations due to their ubiquitous deployment. For example, during the period from 2010 to 2018, the cost of generating electricity by solar PV plants decreased by 77%. However, solar PV installed capacity progress expanded 100-fold between 2005 and 2018. Consequently, solar PV has emerged as a key component in the low-carbon sustainable energy system required to provide access to affordable and dependable electricity, assisting in fulfilling the Paris climate agreement and in achieving the 2030 SDG targets [ 19 ].

The installed capacity of solar energy worldwide has been rapidly increased to meet energy demands. The installed capacity of PV technology from 2010 to 2020 increased from 40 334 to 709 674 MW, whereas the installed capacity of concentrated solar power (CSP) applications, which was 1266 MW in 2010, after 10 years had increased to 6479 MW. Therefore, solar PV technology has more deployed installations than CSP applications. So, the stand-alone solar PV and large-scale grid-connected PV plants are widely used worldwide and used in space applications. Fig. 1 represents the installation of solar energy worldwide.

Installation capacity of solar energy worldwide [20].

Installation capacity of solar energy worldwide [ 20 ].

1.2 Application of solar energy

Energy can be obtained directly from the Sun—so-called solar energy. Globally, there has been growth in solar energy applications, as it can be used to generate electricity, desalinate water and generate heat, etc. The taxonomy of applications of solar energy is as follows: (i) PVs and (ii) CSP. Fig. 2 details the taxonomy of solar energy applications.

The taxonomy of solar energy applications.

The taxonomy of solar energy applications.

Solar cells are devices that convert sunlight directly into electricity; typical semiconductor materials are utilized to form a PV solar cell device. These materials’ characteristics are based on atoms with four electrons in their outer orbit or shell. Semiconductor materials are from the periodic table’s group ‘IV’ or a mixture of groups ‘IV’ and ‘II’, the latter known as ‘II–VI’ semiconductors [ 21 ]. Additionally, a periodic table mixture of elements from groups ‘III’ and ‘V’ can create ‘III–V’ materials [ 22 ].

PV devices, sometimes called solar cells, are electronic devices that convert sunlight into electrical power. PVs are also one of the rapidly growing renewable-energy technologies of today. It is therefore anticipated to play a significant role in the long-term world electricity-generating mixture moving forward.

Solar PV systems can be incorporated to supply electricity on a commercial level or installed in smaller clusters for mini-grids or individual usage. Utilizing PV modules to power mini-grids is a great way to offer electricity to those who do not live close to power-transmission lines, especially in developing countries with abundant solar energy resources. In the most recent decade, the cost of producing PV modules has dropped drastically, giving them not only accessibility but sometimes making them the least expensive energy form. PV arrays have a 30-year lifetime and come in various shades based on the type of material utilized in their production.

The most typical method for solar PV desalination technology that is used for desalinating sea or salty water is electrodialysis (ED). Therefore, solar PV modules are directly connected to the desalination process. This technique employs the direct-current electricity to remove salt from the sea or salty water.

The technology of PV–thermal (PV–T) comprises conventional solar PV modules coupled with a thermal collector mounted on the rear side of the PV module to pre-heat domestic hot water. Accordingly, this enables a larger portion of the incident solar energy on the collector to be converted into beneficial electrical and thermal energy.

A zero-energy building is a building that is designed for zero net energy emissions and emits no carbon dioxide. Building-integrated PV (BIPV) technology is coupled with solar energy sources and devices in buildings that are utilized to supply energy needs. Thus, building-integrated PVs utilizing thermal energy (BIPV/T) incorporate creative technologies such as solar cooling [ 23 ].

A PV water-pumping system is typically used to pump water in rural, isolated and desert areas. The system consists of PV modules to power a water pump to the location of water need. The water-pumping rate depends on many factors such as pumping head, solar intensity, etc.

A PV-powered cathodic protection (CP) system is designed to supply a CP system to control the corrosion of a metal surface. This technique is based on the impressive current acquired from PV solar energy systems and is utilized for burying pipelines, tanks, concrete structures, etc.

Concentrated PV (CPV) technology uses either the refractive or the reflective concentrators to increase sunlight to PV cells [ 24 , 25 ]. High-efficiency solar cells are usually used, consisting of many layers of semiconductor materials that stack on top of each other. This technology has an efficiency of >47%. In addition, the devices produce electricity and the heat can be used for other purposes [ 26 , 27 ].

For CSP systems, the solar rays are concentrated using mirrors in this application. These rays will heat a fluid, resulting in steam used to power a turbine and generate electricity. Large-scale power stations employ CSP to generate electricity. A field of mirrors typically redirect rays to a tall thin tower in a CSP power station. Thus, numerous large flat heliostats (mirrors) are used to track the Sun and concentrate its light onto a receiver in power tower systems, sometimes known as central receivers. The hot fluid could be utilized right away to produce steam or stored for later usage. Another of the great benefits of a CSP power station is that it may be built with molten salts to store heat and generate electricity outside of daylight hours.

Mirrored dishes are used in dish engine systems to focus and concentrate sunlight onto a receiver. The dish assembly tracks the Sun’s movement to capture as much solar energy as possible. The engine includes thin tubes that work outside the four-piston cylinders and it opens into the cylinders containing hydrogen or helium gas. The pistons are driven by the expanding gas. Finally, the pistons drive an electric generator by turning a crankshaft.

A further water-treatment technique, using reverse osmosis, depends on the solar-thermal and using solar concentrated power through the parabolic trough technique. The desalination employs CSP technology that utilizes hybrid integration and thermal storage allows continuous operation and is a cost-effective solution. Solar thermal can be used for domestic purposes such as a dryer. In some countries or societies, the so-called food dehydration is traditionally used to preserve some food materials such as meats, fruits and vegetables.

Sustainable energy development is defined as the development of the energy sector in terms of energy generating, distributing and utilizing that are based on sustainability rules [ 28 ]. Energy systems will significantly impact the environment in both developed and developing countries. Consequently, the global sustainable energy system must optimize efficiency and reduce emissions [ 29 ].

The sustainable development scenario is built based on the economic perspective. It also examines what activities will be required to meet shared long-term climate benefits, clean air and energy access targets. The short-term details are based on the IEA’s sustainable recovery strategy, which aims to promote economies and employment through developing a cleaner and more reliable energy infrastructure [ 15 ]. In addition, sustainable development includes utilizing renewable-energy applications, smart-grid technologies, energy security, and energy pricing, and having a sound energy policy [ 29 ].

The demand-side response can help meet the flexibility requirements in electricity systems by moving demand over time. As a result, the integration of renewable technologies for helping facilitate the peak demand is reduced, system stability is maintained, and total costs and CO 2 emissions are reduced. The demand-side response is currently used mostly in Europe and North America, where it is primarily aimed at huge commercial and industrial electricity customers [ 15 ].

International standards are an essential component of high-quality infrastructure. Establishing legislative convergence, increasing competition and supporting innovation will allow participants to take part in a global world PV market [ 30 ]. Numerous additional countries might benefit from more actively engaging in developing global solar PV standards. The leading countries in solar PV manufacturing and deployment have embraced global standards for PV systems and highly contributed to clean-energy development. Additional assistance and capacity-building to enhance quality infrastructure in developing economies might also help support wider implementation and compliance with international solar PV standards. Thus, support can bring legal requirements and frameworks into consistency and give additional impetus for the trade of secure and high-quality solar PV products [ 19 ].

Continuous trade-led dissemination of solar PV and other renewable technologies will strengthen the national infrastructure. For instance, off-grid solar energy alternatives, such as stand-alone systems and mini-grids, could be easily deployed to assist healthcare facilities in improving their degree of services and powering portable testing sites and vaccination coolers. In addition to helping in the immediate medical crisis, trade-led solar PV adoption could aid in the improving economy from the COVID-19 outbreak, not least by providing jobs in the renewable-energy sector, which are estimated to reach >40 million by 2050 [ 19 ].

The framework for energy sustainability development, by the application of solar energy, is one way to achieve that goal. With the large availability of solar energy resources for PV and CSP energy applications, we can move towards energy sustainability. Fig. 3 illustrates plans for solar energy sustainability.

Framework for solar energy applications in energy sustainability.

Framework for solar energy applications in energy sustainability.

The environmental consideration of such applications, including an aspect of the environmental conditions, operating conditions, etc., have been assessed. It is clean, friendly to the environment and also energy-saving. Moreover, this technology has no removable parts, low maintenance procedures and longevity.

Economic and social development are considered by offering job opportunities to the community and providing cheaper energy options. It can also improve people’s income; in turn, living standards will be enhanced. Therefore, energy is paramount, considered to be the most vital element of human life, society’s progress and economic development.

As efforts are made to increase the energy transition towards sustainable energy systems, it is anticipated that the next decade will see a continued booming of solar energy and all clean-energy technology. Scholars worldwide consider research and innovation to be substantial drivers to enhance the potency of such solar application technology.

2.1 Employment from renewable energy

The employment market has also boomed with the deployment of renewable-energy technology. Renewable-energy technology applications have created >12 million jobs worldwide. The solar PV application came as the pioneer, which created >3 million jobs. At the same time, while the solar thermal applications (solar heating and cooling) created >819 000 jobs, the CSP attained >31 000 jobs [ 20 ].

According to the reports, although top markets such as the USA, the EU and China had the highest investment in renewables jobs, other Asian countries have emerged as players in the solar PV panel manufacturers’ industry [ 31 ].

Solar energy employment has offered more employment than other renewable sources. For example, in the developing countries, there was a growth in employment chances in solar applications that powered ‘micro-enterprises’. Hence, it has been significant in eliminating poverty, which is considered the key goal of sustainable energy development. Therefore, solar energy plays a critical part in fulfilling the sustainability targets for a better plant and environment [ 31 , 32 ]. Fig. 4 illustrates distributions of world renewable-energy employment.

World renewable-energy employment [20].

World renewable-energy employment [ 20 ].

The world distribution of PV jobs is disseminated across the continents as follows. There was 70% employment in PV applications available in Asia, while 10% is available in North America, 10% available in South America and 10% availability in Europe. Table 1 details the top 10 countries that have relevant jobs in Asia, North America, South America and Europe.

List of the top 10 countries that created jobs in solar PV applications [ 19 , 33 ]

Solar energy investments can meet energy targets and environmental protection by reducing carbon emissions while having no detrimental influence on the country’s development [ 32 , 34 ]. In countries located in the ‘Sunbelt’, there is huge potential for solar energy, where there is a year-round abundance of solar global horizontal irradiation. Consequently, these countries, including the Middle East, Australia, North Africa, China, the USA and Southern Africa, to name a few, have a lot of potential for solar energy technology. The average yearly solar intensity is >2800 kWh/m 2 and the average daily solar intensity is >7.5 kWh/m 2 . Fig. 5 illustrates the optimum areas for global solar irradiation.

World global solar irradiation map [35].

World global solar irradiation map [ 35 ].

The distribution of solar radiation and its intensity are two important factors that influence the efficiency of solar PV technology and these two parameters vary among different countries. Therefore, it is essential to realize that some solar energy is wasted since it is not utilized. On the other hand, solar radiation is abundant in several countries, especially in developing ones, which makes it invaluable [ 36 , 37 ].

Worldwide, the PV industry has benefited recently from globalization, which has allowed huge improvements in economies of scale, while vertical integration has created strong value chains: as manufacturers source materials from an increasing number of suppliers, prices have dropped while quality has been maintained. Furthermore, the worldwide incorporated PV solar device market is growing fast, creating opportunities enabling solar energy firms to benefit from significant government help with underwriting, subsides, beneficial trading licences and training of a competent workforce, while the increased rivalry has reinforced the motivation to continue investing in research and development, both public and private [ 19 , 33 ].

The global outbreak of COVID-19 has impacted ‘cross-border supply chains’ and those investors working in the renewable-energy sector. As a result, more diversity of solar PV supply-chain processes may be required in the future to enhance long-term flexibility versus exogenous shocks [ 19 , 33 ].

It is vital to establish a well-functioning quality infrastructure to expand the distribution of solar PV technologies beyond borders and make it easier for new enterprises to enter solar PV value chains. In addition, a strong quality infrastructure system is a significant instrument for assisting local firms in meeting the demands of trade markets. Furthermore, high-quality infrastructure can help reduce associated risks with the worldwide PV project value chain, such as underperforming, inefficient and failing goods, limiting the development, improvement and export of these technologies. Governments worldwide are, at various levels, creating quality infrastructure, including the usage of metrology i.e. the science of measurement and its application, regulations, testing procedures, accreditation, certification and market monitoring [ 33 , 38 ].

The perspective is based on a continuous process of technological advancement and learning. Its speed is determined by its deployment, which varies depending on the scenario [ 39 , 40 ]. The expense trends support policy preferences for low-carbon energy sources, particularly in increased energy-alteration scenarios. Emerging technologies are introduced and implemented as quickly as they ever have been before in energy history [ 15 , 33 ].

The CSP stations have been in use since the early 1980s and are currently found all over the world. The CSP power stations in the USA currently produce >800 MW of electricity yearly, which is sufficient to power ~500 000 houses. New CSP heat-transfer fluids being developed can function at ~1288 o C, which is greater than existing fluids, to improve the efficiency of CSP systems and, as a result, to lower the cost of energy generated using this technology. Thus, as a result, CSP is considered to have a bright future, with the ability to offer large-scale renewable energy that can supplement and soon replace traditional electricity-production technologies [ 41 ]. The DESERTEC project has drawn out the possibility of CSP in the Sahara Desert regions. When completed, this investment project will have the world’s biggest energy-generation capacity through the CSP plant, which aims to transport energy from North Africa to Europe [ 42 , 43 ].

The costs of manufacturing materials for PV devices have recently decreased, which is predicted to compensate for the requirements and increase the globe’s electricity demand [ 44 ]. Solar energy is a renewable, clean and environmentally friendly source of energy. Therefore, solar PV application techniques should be widely utilized. Although PV technology has always been under development for a variety of purposes, the fact that PV solar cells convert the radiant energy from the Sun directly into electrical power means it can be applied in space and in terrestrial applications [ 38 , 45 ].

In one way or another, the whole renewable-energy sector has a benefit over other energy industries. A long-term energy development plan needs an energy source that is inexhaustible, virtually accessible and simple to gather. The Sun rises over the horizon every day around the globe and leaves behind ~108–1018 kWh of energy; consequently, it is more than humanity will ever require to fulfil its desire for electricity [ 46 ].

The technology that converts solar radiation into electricity is well known and utilizes PV cells, which are already in use worldwide. In addition, various solar PV technologies are available today, including hybrid solar cells, inorganic solar cells and organic solar cells. So far, solar PV devices made from silicon have led the solar market; however, these PVs have certain drawbacks, such as expenditure of material, time-consuming production, etc. It is important to mention here the operational challenges of solar energy in that it does not work at night, has less output in cloudy weather and does not work in sandstorm conditions. PV battery storage is widely used to reduce the challenges to gain high reliability. Therefore, attempts have been made to find alternative materials to address these constraints. Currently, this domination is challenged by the evolution of the emerging generation of solar PV devices based on perovskite, organic and organic/inorganic hybrid materials.

This paper highlights the significance of sustainable energy development. Solar energy would help steady energy prices and give numerous social, environmental and economic benefits. This has been indicated by solar energy’s contribution to achieving sustainable development through meeting energy demands, creating jobs and protecting the environment. Hence, a paramount critical component of long-term sustainability should be investigated. Based on the current condition of fossil-fuel resources, which are deemed to be depleting energy sources, finding an innovative technique to deploy clean-energy technology is both essential and expected. Notwithstanding, solar energy has yet to reach maturity in development, especially CSP technology. Also, with growing developments in PV systems, there has been a huge rise in demand for PV technology applications all over the globe. Further work needs to be undertaken to develop energy sustainably and consider other clean energy resources. Moreover, a comprehensive experimental and validation process for such applications is required to develop cleaner energy sources to decarbonize our planet.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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