Smart University Application: Internet of Things (IoT)-Based Smart and Random Method to Collect Waste Management System in a University Campus by Using Ant Colony Optimization (ACO) Algorithm

The paper is focusing the importance of NIC algorithms for Internet of Things (IoT) to find the shortest path to collect waste management efficiently in the university campus by applying Ant Colony Optimization (ACO) algorithm. ACO algorithm is in the category of Swarm Intelligence (SI) algorithms. The SI algorithms are one of the category of NIC algorithms. Nowadays institutions are facing waste management problem due to non-proper management of waste collection in a campus. It requires new solutions to solve in an intelligent way. The proposed paper is efficiently designed to optimize waste collection to reduce cost as well as pollution affecting environment in campus. In this system the truck bins are integrated with IoT-based ultra-sonic sensor to measuring filled level of waste, temperature and carbon dioxide inside of truck bins. The aim of the paper is applying ant colony optimization (ACO) algorithm in an efficient way to optimize to randomly collect garbage waste-filled trash bins in the campus. The proposed system shows better results by improving 75% minimized route, minimized fuel cost, minimized time, minimized environmental pollution and maximized efficient routing. The proposed IoT-based waste garbage collection by ACO algorithm is to efficiently optimize waste management system in university campus.