An Optimized IoT-Based Waste Collection and Transportation Solution: A Case Study of a Norwegian Municipality

Abstract

Smart and sustainable solid waste management systems (SWMS) are of major interest in the development of smart sustainable cities (SSC). Selective waste collection and transportation are known to be major expenditures of city waste management systems. In this paper, we investigate a waste management system for domestic waste in a Norwegian municipality as a case study. Different scenarios for route planning are considered to improve cost and time usage. The study provides an auxiliary management system for multi-objective TSP using Google Maps and operation research (OR) tools for optimal domestic waste collection. Additionally, a prediction model for scheduling future waste collection trips is provided, whereby challenges such as road conditions, road traffic, \(CO_{2}\) and other gases emissions, and fuel consumption are considered. The proposed prediction model considers the hazards associated with food waste bins that need to be emptied more frequently than bins containing other waste types such as plastic and paper. Both proposed models signify consistency and correctness.