An Efficient Smart-IoT-Aided Waste Management System with Optimal Shortest Path Routing Using Mud Ring Algorithm

The waste management is a problem for the modern cities as it affects the sustainability of the environment and on the stage of standard recognized by the people. In the past few years, some changes have done in the path of presenting a door-to-door private garbage gathering. An important factor for the victory of these activities is to attain better cooperation from humans. The digital change operation in this field needs much time other than a better handling of information related to the garbage collection approaches. The conventional garbage maintenance model performs according to the daily schedule that is very costly and inefficient. The conventional recycle bin has also revealed its ineffectiveness because of the improper recycling of the waste by the people. With the improvement of “Internet of Things (IoT) and Artificial Intelligence (AI)”, the conventional garbage handling model can be exchanged with smart sensors enclosed into the device to process real-time observation and permit for good garbage handling. Hence, to resolve the complication presented in the conventional waste management system, an innovative waste management framework is designed based on deep learning techniques. Initially, essential data for the analysis is occurred from benchmark resources and subjected to weight computing region. Here, the weights computation is performed based on trashcan type and capacity. Next, the weight computed data is utilized to identify the shortest path for the waste-collecting vehicle to reach the suitable waste centers. Moreover, the optimal paths are selected by utilizing Mud Ring Algorithm (MRA) optimization technique. Hence, the implemented waste management system secures a better performance rate than the conventional techniques in different experimental observations.