The Research Team at the National University of Science and Technology proposes developing an artificial intelligence-based (AI-based) UAV (unmanned aerial vehicle) system for agricultural applications to support the Irrigation Sector. This proposal investigates the five domains as potential areas while developing drone Mechanism to optimize the use of inputs (seed, fertilizers, water) to react more quickly to threats (weeds, pests, fungi). The domains are:
- To save time crop scouting (validate treatment/actions taken).
- To enable farmers to construct VRPs (variable-rate prescriptions) for crop protection and manage products in a way that improves ROI (return on investment) in real-time.
- To develop a dates plucking mechanism to eliminate/minimize human effort and risk for inexperienced climbers.
- To determine the most optimal and cost-effective date-tree harvesting mechanism. Moreover, to boost efficiency by automating the harvesting process.With the developed AI model using deep learning features, farmers can also estimate yield from afield, one of the project’s primary goals.
Objectives
- The main goal of this proposal is to construct an Artificial Intelligence-based UAV system for agriculture to assist farmers in Oman. According to the project’s principal goals, the proposal’s main objectives are to build AI-based drones and automated robots to assist farmers:
- To make the best use of inputs like seed, fertilizers, and water-based on different soil types and crops for irrigation.
- To analyze the impact of threats like weeds, pests, and fungi and alert the farmers to respond to threats more swiftly.
- To create an intelligent framework with the appropriate knowledge base to train and test at different stages of treats like crop health/ treatment/scouting/damage assessments, type of irrigation and field soil analysis.
- To monitor crop health and crop scouting (validation of treatment/actions taken) to save time, estimate yield from a field, and optimize variable-rate prescriptions in real-time to maximize profit.
- To model the most optimal and cost-effective automatic date fruit harvesting mechanism and reduce/eliminate the human effort and human risk for inexperienced climbers for date harvesting, the safety of humans is not compromised.
- The goal of this research is to boost efficiency by automating the harvesting process through the AI-powered framework. The final product will be shared with FAO and provide necessary support/training to benefit the farmers in Oman.
Funding Agency
MOHERI
Collaboration
Collaborator 1: Dr Seyedali Mirjalili, Professor, Director Centre for Artificial Intelligence Research and Optimisation Torrens University, Australia
Collaborator 2: Dr Falah Younis Hamode, Associate Professor, Faculty of Computing and IT, Sohar University Oman
Collaborator 3: Dr V.Rajinikanth, Professor, department of ICE, St Joseph Engineering College India