Supporting Students' Mental Health and Academic Success Through Mobile App and IoT

Smartphones have become devices of choice for running studies on health and well-being, especially among young people. When entering college,students often face many challenges,such as adaptation to new situations, establish new interpersonal relationships, heavier workload and shorter deadlines, teamwork assignments and others. In this paper, the results of four studies examining students’ well being and mental health as well as student’s perception of challenges and obstacles they face during their academic journey are presented. In addition, a mobile application that acts as a complement to a successful tutoring project implemented at the authors’ University is proposed. The application allows students to keep their schedules and deadlines in one place while incorporating virtual tutor features. By using both, the events from the student’s calendar and his or her mood indicators, the application sends notifications accordingly. These notifications encompass motivational phrases, time management guidelines, as well as relaxation tips.info:eu-repo/semantics/publishedVersio

An Analytical Study on the Implementation of a Healthcare App to Assist People with Disabilities Using Cloud Computing and IoT

This study targets a group of people who require care, that is, people with special needs. The significance of this study lies in addressing the main problem that this group suffers from, which is the lack of awareness and information that leads to the acceptance of that group in society. This work aims to create a mobile application that contributes to spreading knowledge among people with special needs and enhancing their skills to help them become accepted by community members. This application supports people with special needs with training resources, education, suitable jobs, and other services helping them in developing their experiences and knowledge to be active in society. In addition, an evaluation questionnaire has been developed to collect data from both the private and public sectors to classify the building blocks necessary for KSA to incorporate the Internet of Things (IoT) and cloud computing into the healthcare sector. As a result, most respondents acknowledge the importance of a streamlined data-gathering process, the IoT, and cloud-based computing to meet their healthcare needs. Lastly, six main blocks for checking suppliers and the public to accept IoT and cloud healthcare applications are then acknowledged in this paper

SecureTrack- A contact tracing IoT platform for monitoring infectious diseases

The COVID-19 pandemic has highlighted the need for innovative solutions to monitor and control the spread of infectious diseases. With the potential for future pandemics and the risk of outbreaks particularly in academic institutions, there is a pressing need for effective approaches to monitor and manage such diseases. Contact tracing using Global Positioning Systems (GPS) has been found to be the most prevalent method to detect and tackle the extent of outbreaks during the pandemic. However, these services suffer from the inherent problems of infringement of data privacy that creates hindrance in adoption of the technology. Non-cellular wireless technologies on the other hand are well-suited to provide secure contact tracing methods. Such approaches integrated with the Internet of Things (IoT) have a great potential to aid in the fight against any type of infectious diseases. In response, we present a unique approach that utilizes an IoT based generic framework to identify individuals who may have been exposed to the virus, using contact tracing methods, without compromising the privacy aspect. We develop the architecture of our platform, including both the frontend and backend components, and demonstrate its effectiveness in identifying potential COVID-19 exposures (as a test case) through a proof-of-concept implementation. We also implement and verify a prototype of the device. Our framework is easily deployable and can be scaled up as needed with the existing infrastructure.Comment: 22 Pages, 8 figures, To be published in "The Global Interdisciplinary Green Cities Conference 2023 Business, Engineering, Art, Architecture, Design, Political Science, International Relations, Applied Science & Technology.

NMC Horizon Report: 2017 Higher Education Edition

The NMC Horizon Report > 2017 Higher Education Edition is a collaborative effort between the NMC and the EDUCAUSE Learning Initiative (ELI). This 14th edition describes annual findings from the NMC Horizon Project, an ongoing research project designed to identify and describe emerging technologies likely to have an impact on learning, teaching, and creative inquiry in education. Six key trends, six significant challenges, and six important developments in educational technology are placed directly in the context of their likely impact on the core missions of universities and colleges. The three key sections of this report constitute a reference and straightforward technology-planning guide for educators, higher education leaders, administrators, policymakers, and technologists. It is our hope that this research will help to inform the choices that institutions are making about technology to improve, support, or extend teaching, learning, and creative inquiry in higher education across the globe. All of the topics were selected by an expert panel that represented a range of backgrounds and perspectives

A New Artificial Intelligence-Based Hierarchical K-Means Clustering Technique to Detect Addictive Twitter Activity

To stop the COVID-19 epidemic from spreading among their populations, several countries have implemented lockdowns. Students are being forced to stay at home during these lockdowns, which is causing them to use mobile phones, social media, and other digital technologies more frequently than ever. Their poor utilization of these digital tools may be detrimental to their emotional and mental health. In this study, we implement an Artificial Intelligence (AI) approach named Hierarchy-based K-Means Clustering (HKMC) algorithm to group individuals with comparable Twitter consumption habits to detect addictive Twitter activity during the epidemic. The effectiveness of the suggested HKMC is evaluated in terms of accuracy, precision, recall, and f1-score in respect to the association between students’ mental health and mobile phone dependency. Additionally, this study offers a comparative examination of both the suggested and existing procedures

Mobile Technology Deployment Strategies for Improving the Quality of Healthcare

Ineffective deployment of mobile technology jeopardizes healthcare quality, cost control, and access, resulting in healthcare organizations losing customers and revenue. A multiple case study was conducted to explore the strategies that chief information officers (CIOs) used for the effective deployment of mobile technology in healthcare organizations. The study population consisted of 3 healthcare CIOs and 2 healthcare information technology consultants who have experience in deploying mobile technology in a healthcare organization in the United States. The conceptual framework that grounded the study was Wallace and Iyer\u27s health information technology value hierarchy. Data were collected using semistructured interviews and document reviews, followed by within-case and cross-case analyses for triangulation and data saturation. Key themes that emerged from data analysis included the application of disruptive technology in healthcare, ownership and management of mobile health equipment, and cybersecurity. The healthcare CIOs and consultants emphasized their concern about the lack of cybersecurity in mobile technology. CIOs were reluctant to deploy the bring-your-own-device strategy in their organizations. The implications of this study for positive social change include the potential for healthcare CIOs to emphasize the business practice of supporting healthcare providers in using secure mobile equipment deployment strategies to provide enhanced care, safety, peace of mind, convenience, and ease of access to patients while controlling costs

Training Engineers for the Ambient Intelligence Challenge

The increasing complexity of the new breed of distributed intelligent systems, such as the Internet of Things (IoT), which require a diversity of languages and protocols, can only be tamed with design and programming best practices. Interest is also growing for including the human factor, as advocated by the Ambient Intelligence (AmI) research field, whose focus is on transparently and intelligently supporting people. These new design methodologies are increasingly needed in the toolbox of new electronic and computer engineers, and teaching strategies should be devised that allow students to acquire a systems-level view instead of getting lost in technology-oriented approaches. This paper describes a study carried out over two academic years, in a course in ambient intelligence at Politecnico di Torino, Italy. In the course, a project-based learning approach was adopted, in which students design and prototype an AmI system, and their progress is closely monitored throughout the semester. The paper presents the learning goals and teaching strategies, analyzes the learning outcomes from the qualitative and quantitative points of view, and highlights the lessons learned in the process