AIoT Aided Farm Management for the Optimized Production of Selected High Value Crop

Funding Agency: Department of Science and Technology (DOST)

Monitoring Agency: Philippine Council for Agriculture, Aquatic and Natural Resources Research and Development (PCAARRD)

Implementing Agency: Center for Agri-Fisheries and Biosystems Mechanization (BIOMECH)

Personnel: Victor A. Rodulfo, Jr. – Project Leader, Alexis C. del Rosario – Study Leader, John Paolo A. Ramoso – Study Leader, Melvin C. Ilang-Ilang – Study Leader

Mel Vincent A. Ampo – Project Staff,, Jasper Adrian Dwight V. Castro – Project Staff

The occurrence of new and emerging challenges in agriculture such as climate change, changes in land use, pests and diseases, and the growing population of the country established the need for more accurate and specific solutions and interventions. Such challenges have brought about the concept of SMART agriculture. SMART agriculture is a confluence of new and emerging technologies that allow farmers and policy makers a greater wealth of information that allows them more accurate interventions. Technologies such as Internet of Things (IoT), remote sensing, GIS, big data, crop and climate modelling, and smart machines have allowed modern agriculture to deal with emerging challenges. Meanwhile, the emergence of Artificial Intelligence and Machine Learning in the past decade answered the need for collecting and utilizing data.

The project aims to develop a system using the combination of Artificial Intelligence and Internet of Things, which is now referred to Artificial Intelligence of Things (AIoT), that would enable monitoring and control of critical growth factors of a selected high value crop (tomato) for optimal growing conditions. The interfacing of sensors using the internet of things (IoT) combined with the machine learning capabilities brought about by artificial intelligence (AI) would allow control of these critical growth parameters at various stages of the crop’s growth cycle. This will allow optimal production of the crop all year round, even during the considered “off-season” period. As the example of National Tsing Hua University (NTHU) in Taiwan has shown, this could be done through the development of control and monitoring devices for smarter farm management.