Cyber-Collaborative Protocol for Early Detection of Stress in Crop Plants (CCP-ED)

To further explain the design of the Cyber-Collaborative Protocols (CCP), this chapter focuses on the design and application of CCP at the agent level, managing multiple agents, algorithms, and information flows. The objective of this chapter is to present the Cyber-Collaborative Protocol for Early Detection of Stress in Crop Plants (CCP-ED), which is derived from the CCP framework. The CCP-ED is developed and validated for coordinating a multi-agent system to work effectively, even optimally. The design consists of three main agents (humans, a robot, and sensors) and three main algorithms: Routing algorithm, Adaptive Search algorithm, and Stress Detection algorithm (Dusadeerungsikul et al. [9]; Dusadeerungsikul and Nof [8]). The Routing algorithm routes the robot to the sampled locations with the objective of minimizing travel cost/time, enabling the system to spend more time on higher value tasks, i.e., searching for stress and other signals in crop plants. In addition, the Adaptive Search algorithm, is activated after the Stress Detection algorithm indicates a stress in the crop plant, and provides a guideline for the system to respond to the crop plant status. The response is planned by utilizing knowledge-based information that incorporates data from crop plant pathologists, the stress characteristics of the particular crop plant, the current season, and the geographical location. The validation of the CCP-ED is conducted using numerical experiments, and the findings demonstrate that the CCP-ED shows superior results in comparison to the existing practice in two aspects: (1) the number of existing stressed crop plants found, and (2) the system’s overall efficiency.