IoT-based Route Recommendation for an Intelligent Waste Management System
This work addresses waste management efficiency for smart cities, but it appears incremental as it applies existing AI methods to IoT data without introducing new paradigms.
The paper tackles the problem of optimizing waste collection routes in smart cities using IoT data, proposing an AI-based approach that considers bin status and coordinates to recommend routes, with results compared across methods.
The Internet of Things (IoT) is a paradigm characterized by a network of embedded sensors and services. These sensors are incorporated to collect various information, track physical conditions, e.g., waste bins' status, and exchange data with different centralized platforms. The need for such sensors is increasing; however, proliferation of technologies comes with various challenges. For example, how can IoT and its associated data be used to enhance waste management? In smart cities, an efficient waste management system is crucial. Artificial Intelligence (AI) and IoT-enabled approaches can empower cities to manage the waste collection. This work proposes an intelligent approach to route recommendation in an IoT-enabled waste management system given spatial constraints. It performs a thorough analysis based on AI-based methods and compares their corresponding results. Our solution is based on a multiple-level decision-making process in which bins' status and coordinates are taken into account to address the routing problem. Such AI-based models can help engineers design a sustainable infrastructure system.