Other Projects

Electromagnetic Compatibility Monitoring and Prediction Models for Biomedical Devices

Preamble 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 technology 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.
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IoT-AI Based Climate and Quality Monitoring System for Agricultural Value Chains (ICQMSA). Case study of Cassava Value Chain”

Project specific Aims Internet of Things (IoT) and Artificial Intelligence (AI) are powerful tools for monitoring and predicting the quality parameters in agriculture. The project intends to apply IoT and AI in Cassava value chain, because cassava is a root crop that is widely consumed in Rwanda and in sub-Saharan Africa in general. The report by Pan-African Quality Infrastructure (PAQI, 2020) on the gap analysis and need assessment has identified cassava as a poverty fighter capable of spurring industrial development in Africa and open new markets globally. The same report recommended the use of Information Communication Technology (ICT) tools to provide relevant information about the quality and quantity of stocks available, their location and price in order to facilitate the cassava purchasing processes. In addition, this crop is among the priority crops defined by the Government of Rwanda under the Crop Intensification Program. Climate fluctuations and poor tracking of the crop challenges across the value chain affect the quantity and quality of the produce.

This project has the main objective of establishing a new low-cost device that associates the IoT and AI based Climate and Quality Monitoring System for Agriculture (ICQMSA) in order to provide an ICT-based solution for cassava value chain. The Uniqueness of the project would be the establishment of new system which can monitor and predict the quality and climate parameters throughout the cassava value chain. Read more

Design and simulation of low electromagnetic absorption on human brain: case of mobile phone antenna”
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IoT-AI Based Smart Device for Radiation monitoring and prediction of Electrical power transmission lines”
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