학술논문

A Machine Learning Approach in Garbage Collection and Monitoring with IoT Sensors
Document Type
Conference
Source
2023 International Conference on Inventive Computation Technologies (ICICT) Inventive Computation Technologies (ICICT), 2023 International Conference on. :221-226 Apr, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Training
Machine learning algorithms
Predictive models
Sensor systems
Real-time systems
Reliability
Waste disposal
IoT
Sensors
Data Collection
Gas Sensor
Smart bins
Language
ISSN
2767-7788
Abstract
The greatest challenge people face today is garbage management and disposal. As the world is driven by technology, there are still small villages in India where waste is still disposed manually by humans. As humans remove waste, it is frequently seen spilled in unexpected places, causing health problems and spreading deadly diseases. All of this occurs due to a lack of information about waste management and a lack of communication with those involved in the process. By considering this fact, waste management can be accomplished efficiently by segregating garbage and using it to produce compost. This research study has proposed a smart waste management system by integrating IoT sensors by checking the level of the bin used, sending GPS signals to the municipality and giving alert message to the authority in case if there is any production of poisonous gas from the garbage bin. The proposed method is a sustainable and reliable waste disposal and management method deployed in the state. The data collection for the proposed system can be leveraged to further plan the most efficient ways to lower waste mishandling and ensure a clean environment. In order to perform this process, machine learning algorithm is incorporated in the data testing and training process to get higher accuracy. The method adopted can also be used for monitoring and segregating the waste in future.