Optimal Deployment Planning to Maximize Coverage of Agricultural Operations with Effective Resource Utilization

In organised precision agriculture setups, one has to take time-bound action aligned with the crop phase over a large area of cultivation with a fixed set of resources. A significant fraction of this is often the human resources that need to be deployed for various daily activities. For crops such as tea, quality of harvested leaf is usually better with hand-plucking than mechanised-harvesting. In order to ensure resources are utilized effectively, it is essential to plan daily movement and quantum of work of human resources keeping various constraints in view like working hours in a day and the need to cover the entire area of interest within a fixed duration. We propose an algorithm to carry out optimal coverage planning towards efficient operations in order to significantly boost harvesting efficiency, reduce production cost and increase the crop quality. Multiple parameters over a period like the number of workers, daily working time, minimum yield per day, and safe harvesting interval are used to arrive at the optimal coverage plan that effectively mirrors the practical scenarios in managing large plots. For a component of coverage planning that involves finding optimal routes, a comparison with various approaches to address the Travelling Salesman Problem (TSP) is carried out to recommend the most suitable option. Farm scenarios are then defined to simulate and compare OCP with a randomised coverage approach and performance improvements on various metrics are discussed.