External Funded Project

Dr. Omar Gatera

Project Investigator Dr. Omar Gatera
PI Profile Dr. Omar Gatera is Lecturer and Head of PhD Studies and Research in the African Center of Excellence in Internet of Things (ACEIoT), College of Science and Technology, University of Rwanda.

From 2008 to 2020, Dr. Gatera was working for Rwanda Standards Board (RSB), where he gained a sound expertise in standardization and conformity assessment for electrotechnical systems.In addition, Dr. Gatera successfully participated in the in-country training workshop on Research & Development and Innovation measurement instruments for evidence-based science, Technology and Innovation Policy Implementation under both the African Science, Technology and Innovation Indicators (ASTII) and the Science Granting Councils (SGCs) Initiatives; obtained an “IEC Recognitions of Achievement” for IECEE, IECEx and IECRE, and successfully completed the Intertek CQI-IRCA Certified ISO 9001 Quality Management Systems and ISO 50001 Energy Management Systems Auditor /Lead Auditor Training Courses.

Dr. Gatera is a member of regional and international organizations for standardization such as African Electrotechnical Standardization Commission (AFSEC), International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC). Dr. Gatera also contributes in standards harmonization for eastern african countries (EAC).

Dr. Gatera holds a BSc Degree in Electronics and Telecommunication Systems and MSc Degree in Telecommunication Engineering both from the University of Rwanda in 2006 and 2008, respectively. He received his Ph.D in Telecommunication Engineering from Istanbul Technical University (ITU), Istanbul, Turkey in 2017. His research interests include cooperative mobile communications, wireless sensor networks, IoT systems, ad-hoc networks, signal processing techniques, health information technologies and software engineering.

Dr.Gatera has published various papers in international journals and conferences and most of them are indexed by both Scopus and Thomson Reuters.

Publication links:

https://scholar.google.com/citations?hl=fr&user=T4KxmdYAAAAJ

https://orcid.org/0000-0002-5001-377X

Title of the project: Electromagnetic Compatibility Monitoring and Prediction Models for Biomedical Devices
Type of the project: Postdoc/research award , cooperability, academia-industry, etc Research award
Partners: Rochester Institute of Technology (RIT)
Team members: Dr. Omar Gatera (UR), Dr. Gerard Rushingabigwi (UR), Dr. Celestin Twizere (UR), Dr. Didacienne Mukanyiligira (NCST), Prof. Bolaji Thomas (RIT)
Project amount: 83,688 USD
Funder: RSIF
Project period Two years (2022-2023)
Short description of the project: Electromagnetic compatibility (EMC) is a big concern in electronic devices, particularly in hospitals’ medical devices where there is high concern of health and safety. The unacceptable level of electromagnetic emissions from medical devices in hospitals can cause different illness to patients, doctors, nurses and other staff in hospitals such as cancer, mental and skin disorder, and other health and safety issues. Therefore, EMC monitoring and prediction on biomedical devices in hospitals would be a potential solution for the health and safety of people in hospitals. The main objective of the project is to develop an Internet of Things (IoT) based monitoring system and EMC prediction algorithm for the hospital’s biomedical devices. IoT is a low cost and emerging technology for data monitoring in real time and machine learning algorithms are powerful tools for data prediction. An IoT system will be designed and implemented with EMC sensors installed on selected biomedical devices. Data of field strength, frequency, voltage fluctuation and flicker emissions, electrostatic discharge, electrical fast transient, power frequency, magnetic field immunity and radiated RF electromagnetic (EM) immunity will be collected using sensors attached to medical devices, analyzed and compared with the standards thresholds for decision making. Prediction algorithm based on machine learning will be developed to predict the EM emissions of biomedical devices for prevention purposes, proper management and planning of electronic devices maintenance.The implementation of the project will help the hospitals to prevent the effect of EM emissions and it will also assist the hospitals to plan for preventive measures and to have a clear management plan of biomedical devices. At the national level, there will be a reduction of illness as well as accidents caused by EM emissions, improvement of the health and safety of the people at hospitals and thus, the enhancement of performance of hospitals in general. This is in line with national and regional health policies and sustainable development goals (SDGs) for good health and wellbeing of the people.
Project status: Early stage
Type of the Project: National or International : International