Abstract
Waste management is one of the crucial issues in the creation of smart cities. Because of population growth, keeping urban areas clean is a challenge. The Internet of things (IoT) has played a vital role in urban computing because it facilitates the collection, integration, and processing of various types of information. Thus, the aim of this research is to develop an Internet of Things-Based Urban Waste Management System. IoT devices hav been used to monitor human activity and to support waste management. Information about a city was collected and processed in a cuckoo search-optimized long short-term recurrent neural network. The network facilitated the analysis of the waste type, truck size, and waste source. This information alerted the waste management centers so that the appropriate actions could be taken. The efficiency of this IoT-based waste management process was evaluated through an experimental analysis. The system was found to ensure that the bins were processed on a priority basis with minimum error (0.16) and maximum accuracy (98.4%) in the minimum amount of time (15 min).