HARVEST: Comprehensive Farming Verification and Early Prediction System Using AI Models

• Research Topic: HARVEST: A Four-Country Cross-Disciplinary Approach to Building Comprehensive Farming Verification and Early Prediction Systems Using AI Models
• Japan PI: Prof. Hirozumi Yamaguchi (Graduate School of Information Science and Technology, Osaka University)
• US PI: Prof. Sajal K. Das (Department of Computer Science, Missouri University of Science and Technology)
• Australia PI: Prof. Marimuthu Palaniswami (Department of Electrical and Electronic Engineering, University of Melbourne)
• India PI: Dr. Kesavan Subaharan (National Bureau of Agricultural Insect Resources, ICAR)
• Period: October 2025 – September 2028 (3 years)
• Program website: here

Overview

This project has been selected for the AI-ENGAGE (Advancing Innovations for Empowering NextGen AGriculturE) program, a Quad international joint research initiative implemented under Japan's Moonshot R&D Program by the Japan Science and Technology Agency (JST).

AI-ENGAGE, based on the agreement at the May 2023 QUAD Leaders' Summit, promotes international collaborative research leveraging advanced technologies such as AI, robotics, and sensing for agriculture. The program is implemented in partnership with the NSF (National Science Foundation, USA), CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia), and ICAR (Indian Council of Agricultural Research, India).

The HARVEST project aims to build comprehensive farming verification and early prediction systems using AI models, conducting research through a four-country cross-disciplinary approach across Japan, the United States, Australia, and India.