Video analytics with deep learning techniques has generated immense interest in academia and industry, captivating minds with its transformative potential. Deep learning techniques and the deluge of video data enable the mechanization of tasks that were once the exclusive domain of human effort. Furthermore, edge intelligence is emerging as an interdisciplinary technology that drives the fusion of edge computing and artificial intelligence (AI). Edge computing allows the Internet of Things (IoT) devices with limited resources to offload their compute-intensive AI applications to the network edge servers for execution. Specifically, AI workloads for video analytics can be moved to the network edge from the cloud, providing improved latency and bandwidth savings, among other benefits. This article reviews current technologies used in Edge AI-assisted video analytics in smart cities. It examines the various artificial intelligence models and privacy-preserving techniques used in edge video analytics. It identifies the various applications of video analytics in smart cities, including security and surveillance, transportation and traffic management, healthcare, education, sports and entertainment, and many more. Besides, it highlights the challenges of edge video analysis and open research issues. It is expected that this review will be valuable for researchers, engineers, and decision-makers who want to understand the landscape and scale of edge video analytics in smart cities.

Background: Mobile applications play a crucial role in postnatal, contraception, and prenatal care, offering vital monitoring and resources for mothers and infants. This study assessed the software product quality (SPQ) (the degree to which a software product meets specified requirements and user expectations) of three reproductive health monitoring mobile applications, employing ISO/IEC 25010 and ISO/IEC 25023 standards. The objective was to analyze the strengths and weaknesses of each app, thereby providing valuable information for potential users. By identifying areas requiring enhancement, this study improves the overall quality and usability of these applications. Methods: We implemented a three-step analysis process, examining the sub-features and features outlined in the ISO/IEC 25010 standard for software product quality, encompassing functionality, reliability, usability, efficiency, and maintainability. Subsequently, we formulated a checklist summarizing the influence of the three mobile applications on SPQ. Finally, we calculated the impact of each requirement block on both SPQ and quality in use (QIU) models. Results: The results show that the functional suitability SPQ characteristic is greatly influenced by the predefined requirements, with subsequent impacts on the operability, performance efficiency, reliability, and security SPQ characteristics. Thus, developers, designers, and testers must integrate these requirements across the developmental stages of health mobile applications to create a high-quality, patient-centered product with substantial added value. Conclusions: This study has produced a range of requirements tailored for pregnancy monitoring and childcare applications, serving as a valuable reference for developers aiming to create high-quality applications and evaluate their quality effectively. It underscores the importance of integrating SPQ characteristics into the software development process to ensure the creation of high-quality products with essential key performance indicators (KPIs). Such considerations facilitate better evaluations in application stores and increase user adoption and satisfaction levels.

This study empirically evaluates the functionality coverage of 18 mobile applications (apps) for Postnatal care including a recently developed app in Morocco "Mamma&Baby". This evaluation is based on a comparison of the COSMIC _ISO 19,761 functional size of these apps with the score obtained in a previous evaluation based on functions extraction through a quality assessment questionnaire. This comparison allows to discuss the relationship between the functional size of the 18 apps, their users' ratings in the Play Store as well as the number of downloads. While for most of the assessed apps, there is only a small shift between the rankings of the two evaluations, for some apps, the shift is huge due to the number of features added and not covered by the score previously obtained. This study illustrates the use of COSMIC as an effective method for corrective or evolutionary updates since it takes into account all the functions and features of postnatal apps. For the "Mamma&Baby" app, efforts are required to boost the number of downloads, optimize its visibility, and attract the highest number of users.

Background and objective. Mobile apps for postnatal, contraception, and prenatal care are crucial for enhancing the health of mothers and babies. These apps provide daily monitoring and resources, including reliable infant care, feeding, and maternal recovery information. Contraception apps give individuals the means to make informed family planning decisions and access various contraception methods. Prenatal apps offer expectant mothers educational resources, tracking tools for pregnancy milestones, and a connection to healthcare providers for important check-ups and screenings, all while boosting doctor-patient communication. The apps also often include discussion forums where users can connect and share experiences. By providing access to care, information, and support, these mobile apps significantly ensure mothers and babies receive the necessary resources and care to thrive. This study assesses the software quality (SQ) of three reproductive health monitoring mobile apps using ISO/IEC 25010 and ISO/IEC 25023 standards. The aim of the study is to identify the strengths and weaknesses of each app in terms of SQ, with the goal of providing valuable information for users who are considering using one of these apps. By examining the positive aspects of each app, the study provides insights into what makes them a valuable choice. Similarly, by identifying negative points in terms of quality, the study provides an opportunity to identify areas for improvement, so that the apps can be evaluated and improved over time. Methods. A three-step analysis process was implemented, of which the initial step involved examining the sub-features and features of the ISO/IEC 25010 standard for Software Product Quality (SPQ). The next step involved developing a checklist that summarizes the effect of the three mobile apps on SPQ. Finally, a calculation was performed to assess the impact of each requirement block on both the SPQ and the Quality in Use model. Results. The findings indicate the Functional Suitability SPQ characteristic is greatly influenced by the predefined requirements, followed by the Operability, Performance Efficiency, Reliability, and Security SQ characteristics. Therefore, developers, designers, and testers must factor in these requirements throughout the development cycle of health mobile apps to produce a high-quality, patient-centered product with significant added value. Conclusion. This study generated various requirements for pregnancy monitoring and childcare apps, providing a useful reference for developers in creating high-quality apps also assessing the quality of these kinds of apps. The software development process must consider SPQ characteristics to create a high-quality product with crucial KPIs, leading to better evaluations in app stores and increased user adoption and satisfaction.