IoT-Based Garbage Monitoring System with Proposed Machine Learning Model for Smart City
The tremendous modern technological revolution in electronics, cognitive computing, and sensing has supplied the crucial foundation for today's Internet of Things (IoT) for a wide range of applications. In this chapter, we'll look at one of the most difficult issues: waste collection. When...
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Zusammenfassung: | The tremendous modern technological revolution in electronics, cognitive computing, and sensing has supplied the crucial foundation for today's Internet of Things (IoT) for a wide range of applications. In this chapter, we'll look at one of the most difficult issues: waste collection. When waste isn't collected on time, it causes environmental harm and health problems. To improve the waste collection logistic procedure, we are implementing an IoT project in which the first automation of the waste (dry or wet) is completed, and the second update of the dustbin (how much filled) is sent to the server via the Message Queuing Telemetry Transport (MQTT) protocol over a WAN with a cloud. When the dumpster reaches 80% capacity, the system will immediately send an SMS and update the server. The chapter provides the calculation of garbage-truck collection more accurately with a Light Weight protocol, i.e., MQTT, used in Matlab's ThingSpeak cloud act as a web server and NodeMCU is used which provides Internet connectivity so that data can be visualized remotely so that manage and recycle the waste and use it as fertilizer. And also the aim of this chapter is to provide a machine learning (ML)-based proposed system for smart city garbage monitoring.
In this chapter, the authors look at one of the most difficult issues: waste collection. It provides the calculation of garbage-truck collection more accurately with a Light Weight protocol, i.e., MQTT, used in Matlab's ThingSpeak cloud act as a web server and NodeMCU is used which provides Internet connectivity so that data can be visualized remotely so that manage and recycle the waste and use it as fertilizer. The chapter provides a machine learning (ML)-based proposed system for smart city garbage monitoring. Ultranationalistic sensors measure that unit of the goal toward evaluating the long stretch between those overflowing and assembling. That trigger could a chance to be seen as a fundamental pulse that turns the sensor on, every the long run a detachment will be evaluated. The chapter gives a fundamental thought regarding a productive trash checking framework by utilizing the innovation of IoT. |
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DOI: | 10.1201/9781003355960-5 |