Boosting Farm Efficiency: An Ant Colony Optimization Approach to Smart Agriculture

The production of palm oil on a commercial scale is labour intensive with many of its processes handled by humans. In some countries, there can be as many as 500,000 plantation workers in the palm oil sector as the plantations are usually large. However, such dependence on humans for low skill manual work has led to many problems. Unmanned aerial vehicles (UAVs) have been seen as a possible alternative to support some of the processes that require low skills in the palm oil industry. However, the flying time of the UAVs is finite and hence it is important to maximize the number of palm trees that it can service. In this paper, problem of area segmenting is modeled as a bin packing problem. In addition, Ant Colony Optimization was used to assign an optimal number of palm trees for each segmented area that can be comfortably serviced by the agriculture UAV. Good results were obtained for various data sets especially when compared with other methods as well as the results computed by the human experts.