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Title	Smart Waste Collecting Robot Integration With Iot And Machine Learning
ID_Doc	51715
Authors	Srinivasan S.; Jambulingam U.; Purushothaman K.E.; Jegan Amarnath J.
Year	2023
Published	2023 2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023
DOI	http://dx.doi.org/10.1109/SmartTechCon57526.2023.10391813
Abstract	Non-biodegradable waste collecting from a wide area is a time-consuming process. The study aims to create an intelligent robot that can independently collect waste utilizing innovative technology. The study uses the Internet of Things (IoT) to connect and manage the various robot parts. A Raspberry Pi organizes many functions as the system's central processing unit. Real-time visual data, essential for waste detection and identification, is captured by a camera module. Ultrasonic sensors identify obstacles and measure distances so the robot can navigate its environment. The sensor helps the robot avoid collisions and navigate the predetermined space effectively. The robot's robotic arm, which enables it to pick up and collect waste materials physically, is one of its primary features. The Raspberry Pi controls the arm, allowing for accurate and synchronized motions for waste collection. They use machine learning methods to facilitate waste identification and categorization, especially a CNN model. To reliably identify various forms of waste, the CNN model is trained using a collection of waste images. These technologies may be combined to enable the automated waste-collected robot to function independently while effectively locating and collecting rubbish. By seamlessly integrating IoT, machine learning, and robots, this solution helps to save human labor and enhance waste management procedures. © 2023 IEEE.
Author Keywords	Convolutional Neural Network (CNN); Environmental sustainability; Image processing; Internet of Things (IoT); Waste Collecting Robot

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