MONITORING AND ALERTING OF HAZARDOUS GASES IN MUNICIPAL SOLID WASTE USING MACHINE LEARNING TECHNIQUE

In recent times, the rate of urbanization is proliferating; thus, there is a need to find a sustainable way for an urban development plan. There is rapid growth in the concept of smart cities all around the globe. A smart city is always incomplete without a smart waste monitoring structure that can manage the waste collection of the entire city. This paper proposes a Forest Fire alerting system, which keeps track of the hazardous gases produced by dumped waste by integrating a network of gas sensors. Land fill sites collect tons of municipal solid waste (MSW) using an open dump mechanism, causing gases to emerge, which may cause disease and the greenhouse effect. Mainly, landfill environments are observed using a portable system that does not continuously monitor and measure emitted gas levels. It is also difficult to evaluate changes in landfill emissions over the long term unless they are monitored at regular intervals according to a detailed plan. This paper presents a new monitoring method to measure gas levels in landfill sites, which documents dynamic changes in gas composition concentrations over the long term. The system was placed in the middle area of the landfill and was charged using solar panels for convenience and greater efficiency during monitoring.