Fine-Tuning of UAV Control Rules for Spraying Pesticides on Crop Fields

Abstract

The use of pesticides in agriculture is essential to maintain the quality of large-scale production. The spraying of these products by using aircraft speeds up the process and prevents compacting of the soil. However, adverse weather conditions (e.g. The speed and direction of the wind) can impair the effectiveness of the spraying of pesticides in a target crop field. Thus, there is a risk that the pesticide can drift to neighboring crop fields. It is believed that a large amount of all the pesticide used in the world drifts outside of the target crop field and only a small amount is effective in controlling pests. However, with increased precision in the spraying, it is possible to reduce the amount of pesticide used and improve the quality of agricultural products as well as mitigate the risk of environmental damage. With this objective, this paper proposes a methodology based on Particle Swarm Optimization (PSO) for the fine-tuning of control rules during the spraying of pesticides in crop fields. This methodology can be employed with speed and efficiency and achieve good results by taking account of the weather conditions reported by a Wireless Sensor Network (WSN). In this scenario, the UAV becomes a mobile node of the WSN that is able to make personalized decisions for each crop field. The experiments that were carried out show that the optimization methodology proposed is able to reduce the drift of pesticides by fine-tuning of control rules.