Low financial cost with ant colony optimisation in intelligent agriculture

With the development of wireless sensor networks, and other information related high technologies, a lot of practical Internet of Things (IoT) applications have greatly increased the productivity. Currently, more and more capital is invested in IoT, especially intelligent agriculture as many countries begin to pay more attention to basic and intelligent agriculture. For a large intelligent agriculture system, it will cost a lot of time and energy for the mobile sink to collect all the data of the sensing system with the help of cluster head node. In this paper, we try to solve this issue by minimising the data collection path of the mobile sink, using the ant colony optimisation algorithm. We implement the algorithm in Python and conduct two experiments which show that we can get the best path of the given example and show how the efficiency changes when the numbers of ants and loops increase.