Abstract:
Cities have a high population density comparatively to rural areas and villages. Tons of garbage are created on a daily basis, and yet no properly designed infrastructure to manage the waste in developing countries. Due to these open waste dumping is practiced and hence waste is dumped to land owned by the government, which results in a series of negative consequences. Depreciation of health levels and living conditions of people living near the landfills are common problems. Transporting garbage requires high fuel-intensive vehicles and those vehicles do not use the optimum pathway in the garbage collection routine. The decomposing waste produces valuable biogas and organic liquid fertilizer as a byproduct. Which can solve the problems caused by using chemical fertilizer and help reduce fossil fuel consumption overall. In this paper, we present a novel method to efficiently manage garbage collection. Our focus is to reduce the fuel consumption of the garbage collection. It involves facilitating in-house methane production processes and methane leakage detection systems. Also, the proposed system needs less maintenance staff thereby reducing the operational cost and maintenance cost. Further, the proposed system consumes less space than traditional systems for garbage storage.
Citation:
M. R. M. Rilfi and J. D. Kanchana, "IoT and Machine Learning Based Efficient Garbage Management System for Apartment Complex and Shopping Malls," 2021 6th International Conference on Information Technology Research (ICITR), 2021, pp. 1-6, doi: 10.1109/ICITR54349.2021.9657432.