PFI-RP: Smart Connected Farms: Pest Management in Agriculture through Artificial Intelligence (AI) and Internet of Things (IoT)

This Partnerships for Innovation – Research Partnerships (PFI-RP) project has the potential to improve pest and disease management in agriculture, contributing to efforts to address increased food production. By integrating Artificial Intelligence (AI), Internet of Things (IoT), machine learning, and affordable communication networks, this project aims to reduce the reliance on manual labor and outdated practices in pest management. This innovation will also enhance scientific and technological understanding of agricultural pest management, providing valuable data and insights that can inform biotechnology. By collaborating with agricultural university extensions, the project will help create new job opportunities in fields such as agricultural data analysis. The project aims to develop an automated pest management system for rural farms by introducing a cyber-agricultural system framework that integrates multi-modal sensor data and enables real-time pest detection directly on the edge devices. The system optimizes data processing by employing dynamic data and model compression algorithms, reducing the need for extensive communication bandwidth and computational resources. The primary objective is to automate the pest monitoring process, reducing the manual labor and costs associated with traditional scouting methods. The project addresses critical gaps in current pest management practices, such as the reliance on inconsistent data collection and the risks of excessive chemical treatments. The approach offers a scalable solution that can be deployed to overcome the limitations of existing digital monitoring services, often hampered by high operational costs. The anticipated technical outcomes include developing a privacy-preserving, AI-driven system that predicts pest migration patterns and provides proactive, real-time recommendations to growers through an Integrated Pest Management-dedicated chatbot. The system is designed to be a cost-effective and user-friendly solution that enhances decision-making, reduces pesticide reliance, and ultimately improves crop yield. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.