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1. Keynote 2 - Satellite Earth Observations and Machine Learning for Agricultural Monitoring in Sub-Saharan AfricaFood security is one of the most pressing issues faced by many African countries today. 2019 brought further shocks and setbacks to crop production across Africa. Farmers in East Africa, for example, faced more devastating floods, the most severe (and still ongoing) desert locust infestation in 70 years, and of course the COVID-19 pandemic, which has affected every sector and every food system... C. Nakalembe |
2. A Comparative Estimation of Maize Leaf Moisture Content on Smallholder Farming Systems Using Unmanned Aerial Vehicle (UAV) Based Proximal Remote SensingUnderstanding maize moisture conditions is necessary for crop monitoring and developing early warning systems to optimise agricultural production in smallholder farms. Therefore, this study evaluated the utility of UAV derived multispectral imagery and machine learning techniques in estimating maize leaf moisture indicators; equivalent water thickness (EWT), fuel moisture content (FMC) and specific leaf area (SLA). The results illustrated that both NIR and red-edge derived spectral variables were... S. Ndlovu |
3. The Future of Farming: Bringing Biophotonics and Machine Learning to Revolutionize AgricultureThe future of farming is set to be revolutionized by biophotonics and machine learning. Biophotonics is the study of the interaction of light and living matter, and machine learning is a form of artificial intelligence that allows computers to learn from data. Together, these two technologies will allow for more precise and efficient farming, as well as greater yields and less wastage. Biophotonics will allow for more precise targeting of crops with pesticides and herbicides, as well as more efficient... S. Ndlovu |
4. Design and Development of a LoRa Communication System for Scalable Smart Irrigation SystemsSmart irrigation is a promising tool to optimize irrigation water use but is still faced with challenges related to usability and applicability attributed to several constraints such as high initial costs, complex user interface, poor connectivity, limited farm coverage, etc. This study aimed to solve some of these issues through the development and testing of a LoRa communication system using a Raspberry Pi 4, LoRa HAT concentrator, and Strega smart valve at the Makerere University Agricultural... J. Wanyama , J. Ikabat, I. Kabenge, P. Hess, P. Nakawuka, E. Bwambale , J. Muyonga, S. Felicioni, A. Bühlmann, T. Anken |