Cyber-Collaborative Optimal Search Protocol for Precision Agriculture (CCOSP)

In this chapter, we consider improvements in the Adaptive Search algorithm (AS) as examples of how Cyber-Collaborative Protocols (CCP) may increase algorithm performance, especially by minimizing the total cost of errors. The previous chapter has shown that AS has the potential to increase the monitoring system’s efficiency. As a result, it is worthwhile to explore the algorithm further in order to determine the optimal AS procedure. The Cyber-Collaborative Optimal Search Protocol for Precision Agriculture (CCOSP), developed and analyzed in this chapter, considers the dynamics of a system, such as errors that may occur in the Agricultural Robotic System (ARS) and differences in crop plants’ stress characteristics. CCOSP connects Dynamic Adaptive Search (D-AS) and the Stress Propagation Model (SPM), resulting in an optimal search procedure. CCOSP is developed, tested, validated, and integrated into the ARS to improve the system performance. Experiments are conducted to evaluate the CCOSP, and results show that CCOSP delivers the best performance compared to other search algorithms. Moreover, the sensitivity analyses show that CCOSP still yields high performance, even when the input parameter may deviate from the known true value.