(+961) 1 421 000 ext ali.ibrahim5@usj.edu.lb
Ali Ibrahim holds a master’s degree in Computer Communications Engineering from Antonine University (UA), Hadat-Baabda, Lebanon, obtained in 2018. He obtained his PhD in engineering sciences from University of Technology of Belfort-Montbéliard (UTBM), France, in 2024. His research interests include wearable ambient sensor networks for elderly people fall detection prediction. He is an experienced software engineering instructor full-stack developer with a demonstrated history of working in both universities the software development industry. He is highly skilled in programming, particularly in Java, PHP, HTML, CSS, Node.js/JavaScript, React, and React Native. Additionally, he has worked with several types of databases such as SQL, MySQL, Oracle, Sybase, and PostgreSQL.
Highest degree : PhD in Engineering Sciences - Université de Franche-Comté [France]
Degrees | University | Country | Year |
---|---|---|---|
Sciences pour l'ingénieur | Université de Franche-Comté | France | 2024 |
Mastère d'ingénieur en informatique et télécommunication | Université Antonine (UA) | Lebanon | 2018 |
Experience in University Teaching Outside USJ | Country | Institution | Start Date | End Date |
---|---|---|---|---|
Lecturer | Lebanon | Université Antonine (UA) | 09/09/2022 |
Professional Experience | Organization | Start date | End date |
---|---|---|---|
Full stack developer | BA Solutions | 31/05/2019 | 23/10/2021 |
Specialist Consultant | Azentio Software | 05/05/2019 | |
Full stack developer | Takwin Digital | 07/05/2017 | 31/05/2019 |
Engineering and Technology, Sciences
As a dedicated researcher in the field of human health technology, my primary focus revolves around falls, with a specific emphasis on bed falls, the intricate relationship between these incidents sleep patterns. The prevalence of sleep-related disorders their consequences, including falls, along with their impact on overall well-being, have sparked my interest in developing innovative solutions that leverage the power of Internet of Things (IoT) technology. Throughout my academic journey, I have explored various facets of sleep science and identified the need for advanced monitoring systems that not only track sleep patterns but also address the safety concerns associated with nocturnal falls. The core of my research lies in the development of smart devices capable of real-time sleep monitoring. These devices employ cutting-edge sensor technologies to collect comprehensive data on sleep cycles. Moreover, I have integrated machine learning algorithms to analyze this data and detect sleep posture, thereby offering insights into sleep quality. Furthermore, the system proposes a sleep quality index and can identify falls during the night. One key innovation in my proposed systems is their proactive approach to detecting sleep postures and falls by leveraging the collected data and employing advanced algorithms. The integration of hardware and software in my research is pivotal. The development of robust IoT devices is complemented by a user-friendly and efficient software interface. This ensures seamless data interpretation, visualization, and user engagement. In conclusion, my research endeavors aim to make significant contributions to the intersection of health and technology. By addressing the complex issues of sleep monitoring and detecting nocturnal falls, I aspire to enhance the quality of life for elderly people. Through the integration of IoT devices and sophisticated software, I am committed to exploring new technology and creating solutions that positively impact human health
JOURNAL ARTICLES 1. A. Ibrahim, K. Chaccour, A. Hajjam El Hassani, M. Hajjam E. Andres, ”BedSense: A Bed-Mounted Sensor Node System for Sleep Activities Monitoring Nocturnal Falls Detection,” in IEEE Sensors Journal, vol. 24, no. 12, pp. 19944-19953, 15 June15, 2024, doi: 10.1109/JSEN.2024.3397039. 2. A. Ibrahim, K. Chaccour , A. H. E. Hassani E. Andres, ”Bed -Fall Detection Prediction: A Generic Classification Review of Bed -Fall Related Systems,” in IEEE Sensor s Journal , vol . 21 , no. 5, pp. 5678 -5686, 1 March1 , 2021 , doi : 10.1 109/JSEN.2020.3037711. BOOK CHAPTER 1. Ibrahim, A., Chaccour, K., El Hassani, A.H., Andres, E. (2024). SleepPal: A Novel System for Elderly Sleep Monitoring Bed Falls Detection. In: Ziefle, M., Lozano, M.D., Mulvenna, M. (eds) Information Communication Technologies for Ageing Well and e-Health. ICT4AWE 2023. Communications in Computer and Information Science, vol 2087. Springer, Cham. https://doi.org/10.1007/978-3-031-62753-8 5 INTERNATIONAL CONFERENCE PAPERS 1. A. Ibrahim, K. Chaccour, G. Badr and A. H. E. Hassani, ”Fall Detection Algorithm using Body Angle for Accurate Classification of Falls and ADLs,” 2021 International Conference on e-Health and Bioengineering (EHB), Iasi, Romania, 2021, pp. 1-4. 2. A. Ibrahim, K. Chaccour, A. H. E. Hassani and E. Andres, SleepPal: A Sleep Monitoring System for Body Movement and Sleep Posture Detection. In Proceedings of the 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health 2023.