Back to ProjectsFarmGazer
Problem
Monitoring crops manually is difficult for large farm owners (1,000+ acres) due to a shrinking workforce. Timely detection of issues is essential to prevent economic losses.
Approach
The team designed a system using pan & tilt cameras and microclimate sensors to automate crop monitoring. They integrated AI tagging and analysis to reduce cognitive load and improve decision-making.
Solution
By capturing crop imagery at scheduled intervals and analyzing it with LLMs, the system detects diseases, alerts users, and provides treatment guidance and predictive insights through a mobile interface.
Team Members
Wanling Yu
Haoran Zeng
Zia Sun
