‘COntext-Aware LEarning for Sustainable CybEr-agricultural (COALESCE) systems’ seeks to design a scale-agnostic, cyber-agricultural system that provides individualized plant management (i.e., customized treatment for each individual plant/plot) over farm-level coverage areas. COALESCE is a trans-disciplinary team seeking to bring Cyber-Physical Systems (CPS) principles to sustainable agriculture. The mission is to disrupt the current agricultural practices with CPS innovations to enhance efficiency, resiliency, sustainability and autonomy. To achieve this, key technological innovations include the adaptation of individualized sensing, individualized modeling, and individualized actuation via context-aware machine learning and coordinated teams of robots that are enabled by autonomy algorithms, soft and dexterous manipulators, and adaptive networking algorithms.

The COALESCE project seeks to transform CPS capabilities in agriculture by developing a novel, context-aware cyber-agricultural system that encompasses sensing, modeling, and actuation to enable farmers to respond to crop stressors with lower cost, greater agility, and significantly lower environmental impact than current practices