Resource Management in Controlled Environment Agriculture

Achieving food self-sufficiency in any context requires farming activities to take place all year-round. This is a challenging endeavor in hot desert climates due to extreme weather conditions and the scarcity of water and arable land. Indoor soil-less farming removes the limitations imposed by the lack of arable land and significantly reduces the use of water. However, in addition to higher operational complexity, indoor farming in hot desert climates requires extensive use of electricity and water for cooling purposes, with ensuing challenges to economic sustainability. In addressing these problems, the project focuses on the development of an Enterprise Resource Planning (ERP) component for Hydroponic Greenhouses (HG) that monitors and optimizes farming operation system and provides a predictive evaluation of the profitability of each greenhouse. The HG-ERP system comprises hardware and software components. The hardware component consists of a network of Internet of Things (IoT) sensors which collect data relevant to the optimization of HG operations (e.g., temperature, humidity, solar radiation, soil moisture and electrical conductivity, pH, etc.) and send them to a database on the cloud. The software component includes a Greenhouse Digital Twin (GDT), an optimization component, and a technoeconomic component. The GDT analyses the data collected by the IoT network at any point in the crop cycle to predict crop output at the end of the cycle. The optimization component individuates optimal trade-offs scenarios for each GDT prediction in the use of resources and crop output. The technoeconomic component provides an economic evaluation of each optimal trade-off scenario.

Hamad Bin Khalifa University (HBKU)