EE Colloquium: Precision Farming: How Intelligent Systems Are Shaping Future Agriculture

Abstract: The Food and Agriculture Organization (FAO) estimates that food demand will require a substantial increase of global food production of 70 percent by 2050. How can we produce more and better quality of food sustainably? Precision farming, or precision agriculture, is an emerging area that involves using data and automation technologies to optimize farm management practices and increase productivity. Data-based agricultural practices use real-time and historical data along with machine learning to make specific decisions for site-specific application in the field. In smart agriculture laboratory, we use field cameras, sensors, and micro-climate data to monitor and provide crop information in real time. Deep learning and computer vision analyze geo-referenced data and report when something important is happening in the field. This helps farmers in a number of ways, such as producing accurate diagnostics of individual areas or even individual plants, preventing crop damages from weather event, and controlling yield potential while reducing costs and environmental footprint.

Biography: Dr. Dana Choi is an Assistant Professor in the Department of Agricultural and Biological Engineering. Her research focuses on providing practical solutions to current labor shortage and safety issues through technical advancement using automation and artificial intelligence. Her current research involves developing agricultural robotics and smart sensing systems applied in Pennsylvania’s specialty crops, especially for tree fruit and mushrooms.