The Smart Dustbin using Raspberry Pi project aims to tackle the issue of inefficient and untimely waste collection in urban areas. By leveraging the power of Internet of Things (IoT) technology, the proposed system enables the real-time monitoring of dustbins and efficient waste collection. This document outlines the literature study, proposed methodology, results, and future work of the project. The proposed system consists of distributed dustbins, a central system, and a dashboard that is connected through the IoT. The document also discusses the data transmission protocols and the logic used in the system. Overall, the proposed system provides a reliable and scalable solution for efficient waste management in urban areas.
MethodologyThe Smart Dustbin Management System is a proposed solution to the issue of inefficient and untimely waste collection in urban areas. The system is designed to leverage the power of the Internet of Things (IoT) to enable real-time monitoring of dustbins and efficient waste collection. The system consists of three main components: dustbins, a central system, and a dashboard.
The dustbins are the most important part of the system. They are equipped with various sensors such as ultrasonic sensors and infrared sensors, Raspberry Pi, LEDs, and servo motors. The dustbins act as nodes of a larger system and keep publishing data to the central system. They have multiple functionalities such as opening the dustbin lid when someone approaches the dustbin, measuring the remaining capacity in the dustbin, and indicating users using LEDs.
The central system is the brain of the Smart Dustbin Management System. It collects the data from the dustbins, processes it, and serves it for monitoring and analytics. AWS IoT Core is used as a managed service to facilitate the data transfer between the dustbins and the central system using the MQTT protocol. The data generated in the system is time-series data, and AWS Timestream DB is used for storing it. An API server is required to serve the data, and AWS Lambda is used for this purpose. The API server is built using Node.js (in TypeScript).
The dashboard is a webpage where users or administrators can monitor the status of the dustbins and act accordingly. The dashboard shows the status of the dustbins deployed in the system. If a new dustbin is added to the system, the count of the dustbins populated in the dashboard increases by 1. The status of the dustbins can be updated in various predefined intervals such as 5s, 15s, 1m, 5m, and 1h. The number of data points (in the time scale) can be adjusted. The dashboard uses the REST protocol to communicate with the central system.
The proposed system provides a reliable and scalable solution for efficient waste management in urban areas. It uses MQTT and REST protocols for data transmission. Although the system is hard-coded and lacks artificial intelligence, it provides a practical solution for the issue of inefficient and untimely waste collection in urban areas. However, there are limitations to the proposed model, such as the lack of location data for the deployed dustbins. This can be resolved using GPS technology. Each dustbin can send the data along with its location, and with the help of a map, the locations of the dustbins can be displayed. Besides, the lack of reliable and widespread connectivity of the network in non-urban areas is another limitation of the model. This problem can be solved by implementing GSM.
ResultThe Smart Dustbin using Raspberry Pi project provides a reliable and scalable solution for efficient waste management in urban areas. The proposed system consists of distributed dustbins, a central system, and a dashboard that is connected through the IoT. The dustbins are equipped with Raspberry Pi, LEDs, ultrasonic sensors, infrared sensors, and servo motors. The central system collects the data from the dustbins, processes it, and serves it for monitoring and analytics. The dashboard shows the status of the dustbins deployed in the system. The proposed system uses MQTT and REST protocols for data transmission. Overall, the proposed system provides a solution for the issue of inefficient and untimely waste collection in urban areas. However, there are limitations to the proposed model, such as the lack of location data for the deployed dustbins and the lack of reliable and widespread connectivity of the network in non-urban areas.
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