The advancement and popularity of smartphones have made it an essential and all-purpose device. But lack of advancement in battery technology has held back its optimum potential. Therefore, considering its scarcity, optimal use and efficient management of energy are crucial in a smartphone. For that, a fair understanding of a smartphone’s energy consumption factors is necessary for both users and device manufacturers, along with other stakeholders in the smartphone ecosystem. It is important to assess how much of the device’s energy is consumed by which components and under what circumstances. This paper provides a generalized, but detailed analysis of the power consumption causes (internal and external) of a smartphone and also offers suggestive measures to minimize the consumption for each factor. The main contribution of this paper is four comprehensive literature reviews on: 1) smartphone’s power consumption assessment and estimation (including power consumption analysis and modelling); 2) power consumption management for smartphones (including energy-saving methods and techniques); 3) state-of-the-art of the research and commercial developments of smartphone batteries (including alternative power sources); and 4) mitigating the hazardous issues of smartphones’ batteries (with a details explanation of the issues). The research works are further subcategorized based on different research and solution approaches. A good number of recent empirical research works are considered for this comprehensive review, and each of them is succinctly analysed and discussed.

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Power Consumption Analysis, Measurement, Management, and Issues: A State-of-the-Art Review of Smartphone Battery and Energy Usage

Researchers propose new algorithm to monitor fatigue of driver by tracking the movements of the eyes. This can classify the opening and closing eyes by using Haar-Like Features and Region of Interest techniques. The fatique can be classified by decision tree classification. The system works in real time and sends message to the mobile phone to alert the driver via Line Application. The results showed that the program can detect face and classify opening and closing eyes accurately at 99.93 percent in which it yielded higher accuracy than other algorithms.

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The System for Driver Fatigue Monitoring Using Decision Tree via Wireless Sensor Network for Intelligent Transport System

Mobile crowd computing (MCC) that utilizes public-owned (crowd’s) smart mobile devices (SMDs) collectively can give adequate computing power without any additional financial and ecological cost. However, the major challenge is to cope with the mobility (or availability) issue of SMDs. User’s unpredicted mobility makes the SMDs really unstable resources. Selecting such erratic resources for job schedule would result in frequent job offloading and, in the worst case, job loss, which would affect the overall performance and the quality of service of MCC. In a Local MCC, generally, a set of users are available for a certain period regularly. Based on this information, the chances of a user being available for a certain duration from a given point of time can be predicted. In this paper, we provide an effective model to predict the availability of the users (i.e., their SMDs) in such an MCC environment. We argue that before submitting a job to an SMD, the stability of it is to be assessed for the duration of execution of the job to be assigned. If the predicted availability period is greater than the job size, then only the job should be assigned to the SMD. An accurate prediction will minimize the unnecessary job offloading or job loss due to the early departure of the designated SMD. We propose an advanced convolutional feature extraction mechanism that is applied to LSTM and GRU-based time-series prediction models for predicting SMD availability. To collect user mobility data, we considered a research lab scenario, where real mobility traces were recorded with respect to a Wi-Fi access point. We compared the prediction performances of convolutional LSTM and GRU with the basic LSTM and GRU and ARIMA in terms of MAE, RMSE, R2, accuracy, and perplexity. In all the measurements, the proposed convolutional LSTM exhibited considerably better prediction performance.

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Deep Learning Based Resource Availability Prediction for Local Mobile Crowd Computing

The evolution of mobile technologies in learning, has been increased the requirements for developing appropriate usability model to fall into the same line with mobile learning applications. Usability of mobile learning applications is a topic that is into research, this paper focuses a tailored designed model called (M-UTUAT) mobile usability model that combines People at the Centre of Mobile Application Development (PACMAD) and the unified theory of acceptance and use of technology (UTAUT) to form a more robust model. As an addition to the usability research, an application (ICT) was developed for children with speech delays and children diagnosed with autism spectrum. The application is a mobile/tablet-based application that developed according to mobile usability measures to get the maximum learning skills and abilities to help autistic children. It has been designed according to the needs of the children specific to their category and skills. The autism spectrum is a broad spectrum with high and low disabilities. The application consists of both visual and audio aids to help children feel comfortable and associate objects more easily with their original meaning and connections. (PECS) is one of the most common techniques that have been clinically proven to be effective in such cases. This application helped an individual with autism spectrum as well as children with speech delays or disabilities to communicate and correlate faster and easily. The application can help so many families by constructing a more communicative path for people with disabilities. The application is innovative that it developed in the Arabic language to serve Arabic learners as most of the autistic applications available serve English learners. Results gathered after questionnaire highlight the usability issues with the (ICT) application. We developed an app to overcome usability issues.

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Usability Evaluation and User Acceptance of Mobile Applications for Saudi Autistic Children

Studies on the potential of smartphone apps for people with autism are currently increasing in number, given the large digital supply available and the benefits they offer. We analyzed the opinion of educators from Florence (Italy) and Granada (Spain) regarding the benefits and applicability of apps, frequency of their use, and the type of apps used for people with autism.The study involved 1261 professionals, of whom 286 worked with apps, using a non-experimental quantitative design, descriptive and frequency statistics, parametric inferential analyses (Student's t and one-factor ANOVA), and calculation of the effect size (Cohen's d and eta squared) and intrafactorial correlations.Statistically significant differences were observed in respect of city, sex, age, years of experience, place of work, and type of teacher. The teachers from Granada found more benefits and applicability in apps, and revealed a slightly higher usage than those from Florence.It is an arduous but worthy task for professionals from schools and associations that work with people with autism to acquire the necessary knowledge to apply methodologies based on information and communication technology (ICT), as this will help achieve the integrated development of people with different capabilities. 

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Functionality of Apps for People with Autism: Comparison between Educators from Florence and Granada

Autism Spectrum Disorder is a neurological and developmental disorder. Children diagnosed with this disorder have persistent deficits in their social-emotional reciprocity skills, nonverbal communication, and developing, maintaining, and understanding relationships. Besides, autistic children usually have motor deficits that influence their imitation and gesture production ability. The present study aims to review and analyze the current research findings in using robot-based and virtual reality-based intervention to support the therapy of improving the social, communication, emotional, and academic deficits of children with autism. Experimental data from the surveyed works are analyzed regarding the target behaviors and how each technology, robot, or virtual reality, was used during therapy sessions to improve the targeted behaviors. Furthermore, this study explores the different therapeutic roles that robots and virtual reality were observed to play. Finally, this study shares perspectives on the affordances and challenges of applying these technologies.

Robot and virtual reality-based intervention in autism: a comprehensive review

Autism is a complex neurobiological disorder that is prevalence worldwide. Most autistic children have weak communication and social skills. This re-searches aims to develop and test a mobile application, named MyVoice, which supports local autistic children. The proposed design and features are discussed, and a prototype is evaluated and tested by two therapists and an autistic child. Experimental results indicate positive feedback in terms of ease of use, aesthetic, and simplicity. Parents of the autistic child are satisfied with different features such as the alert notification. Results also indicate that autistic children need about one week to easily interact with MyVoice.

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A Mobile Social and Communication Tool for Autism

Smartphones play today a significant role in providing portability and ease of use for most of the personal computer (PC) functionalities anytime and anywhere. The smartphone market, especially in the UAE, is experiencing an increase in its size. Current technology users seek ease of use, portability, efficiency, and effectiveness. This research focuses on studying and analyzing the factors that influence individuals in Abu Dhabi causing them to switch from personal computers to smartphones. The studied factors in this paper are social, technical, and dependency. This paper utilizes two models, the Technology Acceptance Model and Structural Equation Model, to focus on two technologies in smartphones to analyze their functional attributes; wireless internet connectivity and mobile service technology that provide portability and mobility. This study analyzes the reasons behind the increased use of smartphones as well as decreased use of PCs. This research also provides smartphone manufacturers and mobile application designers with latest trends and perspectives of regional customers. This paper concludes with recommendations for industry, practitioners, further research, and the successful adoption of mobile in the UAE.

Factors Influencing Individuals to Switch from Personal Computers to Smartphones

Information is a critical asset in any organization to achieve its strategic goals. For this, organizations enforce physical, logical, and administrative controls to protect their information from being corrupted, manipulated, or breached. However, an employee with little awareness of cybersecurity threats is an easy target for attackers. Nowadays, companies implement security awareness using policies, procedures, and training sessions, to list a few. Traditional information security awareness sessions have relied heavily on presentation slides and videos. This paper aims to improve the employees’ cybersecurity awareness by developing an interactive video game, a cyber shield game, that includes various embedded threat scenarios. The proposed game consists of four levels. The password complexity level educates players about password threats. The social engineering level aware employees about email attachments and trespass threats. The phishing attack level educates employees about phishing emails and ransomware threats. Finally, the physical security level aware employees about threats to storage and work documents’ disposal. Further, two surveys, pre-game and post-game, are conducted to estimate the players’ knowledge and experience in cybersecurity threats. The proposed security awareness program is applied to ten employees randomly chosen from different organizations. Experimental results indicate that the cyber shield training and awareness program is more interactive than traditional awareness methods. Results also suggest that the proposed awareness program improves the employees’ cybersecurity awareness level by 51.4%.

Fadi Abu-Amara

Papers

Robot and virtual reality-based intervention in autism: a comprehensive review

A Mobile Social and Communication Tool for Autism

Factors Influencing Individuals to Switch from Personal Computers to Smartphones

A novel SETA-based gamification framework to raise cybersecurity awareness

Fault Light Detection and Identification System using RFID.