Conceptual and Simulated Semi-Automatic Urban Waste Management System using Global Systems for Mobile Communication and Customer Reliability Indices

Abstract

: Municipal Solid Waste Management (MSWM) poses great challenges to many cities around the world. The challenges are fuelled by population explosions all over the world, especially in the major urban centres, against the backdrop of limited resources to manage wastes efficiently. In this paper, a conceptual and simulated semi-automatic approach to MSWM is considered using the prevalent Global Systems for Mobile Communication (GSM) technology to engage both the waste generators and collectors. This system connects users into a central database where data about their waste bin levels are harnessed. Users are prompted via GSM handsets daily for the level of the waste bin. Waste Collection Vehicles are routed based on the responses while an updatable Reporting Reliability Index (RRI) is computed for each user based on estimate of actual level of waste collected as against the reported level to factor future reporting. With history of collection volume at a location known, forecast is made as to the generated waste level when a customer’s response to prompt is not available. The system is tested on a simulated 30-node housing estate and two dump sites with vehicles routed to optimize distance covered and volume of waste collected. Customers report when prompted with 0, 1, 2, 3, 4 for waste levels ranging from empty to full bin fills. Vehicles are routed to collect wastes at locations with a minimum threshold level of 2. Results obtained showed statistically insignificant differences in distribution of means of collection distance covered weekly but 13.31 volume units/km collected with this method compared with 3.08 volume units/km run of fixed routing scheme, at = 0.05. The cost saving potential and environmental benefits of timely waste disposal of this scheme is thus demonstrable.

Keywords: Municipal Solid Waste, Waste Management, SMS Gateway, GSM, Reporting Reliability Index.