|Principal Investigator:||Bamurigire Peace|
Dr. Peace Bamurigire is a lecturer with eleven years of experience working at the University of Rwanda. Peace specializes in embedded computing systems and is responsible for lecturing and researcher’s other researchers’ employees on using progressive systems and applications, including ICT software, and designing and programming IoT devices. Peace is a powerful force in the workplace and uses her positive attitude and tireless energy to encourage others to work hard and succeed. Peace graduated from the University of Rwanda in 2022 with PhD degree in Embedded Computing Systems in Internet of Things. While in 2022.Peace is inspired daily by her courage and her two daughters. In her free time, Peace likes to solve problems, think of ways to help others, and help those who need it.
Peace general area of expertise in computer engineering is developing and improving existing computer-based technologies, systems, and solutions, working with computer programmers and information technology professionals, designing and engineering operating systems, software, hardware, networks and communications, and databases, and solving technological problems.
Much of Peace recent work has focused on developing smart agriculture using machine-learning techniques linked to weather forecasts, designing waste management applications, designing and developing a smart and portable vital sign screener called "health neighbor smart kit" (hensk), developing a low-complexity facial recognition algorithm for mask checking and alerting accordingly to allow or deny access or entry, and developing a mobile application.
|Title of the project:||IoT Empowered Precision Agricultural Techniques for Improved Rice Production: AnAutomated Irrigation and Fertilization Application System for Small-scale Rice Producers inRwanda|
|Type of the project: Postdoc/research award , cooperability, academia-industry, etc||research award|
|Partners:||RIT-USA and SRM University-India|
|Team members:||Principal Investigator (PI): Peace Bamurigire, Assistant lecturer at University of Rwanda, Tel: +250 788857274, e-mails: firstname.lastname@example.org and email@example.com Co-PIs: Prof. Anthony VODACEK(RIT-USA), Prof.Kayalvizhi Jayavel (SRM University-India), Mr. Evariste Twahirwa, Mrs. Jane MURERWA, Mr. Kambombo Mtonga, Mrs. Kellen Sumwiza|
|Project amount:||150,000,000 RWF|
|Funder:||NCST||Project period:||5 years||Short description of the project:||Rice is one of the priority food crops in Rwanda, and a major commodity in the food baskets of rural and urban households. However, 76% of the rice on the local market is imported from other rice producing countries in order to meet the demand. One of the initiatives taken by the Government of Rwanda to boost rice production, was the establishment of the Muvumba Valley rice project. This project was established to provide irrigation for the flat land of the valley bottom to support rice farming. This project supports more than 1000 small-scale farmers with field sizes of about 1 ha. However, lack of field-by-field control of irrigation causes conflicts and irrigation inefficiency. Further, lack of adequate soil testing in Rwanda means fertilizer applications are made at times of the growing season that saves labor rather than when maximum plant uptake can occur, leading to over-fertilization and soil degradation. The University of Rwanda (UR) Center of Excellence in Internet of Things (ACEIoT), Rochester Institute of Technology of USA and SRM Institute of Science and Technology of India have joined hands to develop low cost IoT-based technologies thereby providing farmers with a robust tech-based means for monitoring farm conditions to inform irrigation and fertilizer application scheduling. This objective is based on the hypothesis that there are fertilizer and water wastage on farms, which can be analyzed using modeling methods such as a fuzzy algorithm, Markov Chain process, and SARSA to determine nominal conditions versus problem conditions and thus provide rice farmers information that will allow them to reduce the amount of fertilizer and water from current practice while increasing yield. Meeting this overall object leads us to three secondary objectives. (1) To design an IoT-based system that will function to monitor soil conditions via control algorithms to advise farmers with information on optimal irrigation and fertilization schedules. (2) To develop machine learning algorithms to be embedded in the network and help process the automatic control of irrigation and fertilization as well as fault tolerance. (3) To test and deploy the designed and developed irrigation and fertilization recommender system. A mobile application will be developed which will interface with farmers giving them chance to interrogate the system for appropriate information.|
|Type of the Project: National or International :||National|