Raspberry Pi 4 and Ultrasonic Sensor for Real-Time Waste Classification and Monitoring with Capacity Alert System

Authors

  • Yuliza Yuliza Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia
  • Rachmat Muwardi Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia
  • Prima Wijaya Kusuma Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia
  • Lenni Lenni Department of Electrical Engineering, Universitas Muhammadiyah Tangerang, Tangerang, Indonesia
  • Rizky Rahmatullah School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing, China
  • Mirna Yunita School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
  • Akhmad Wahyu Dani Department of Electrical Engineering, Universitas Mercu Buana, Jakarta, Indonesia

DOI:

https://doi.org/10.26555/jiteki.v10i4.30036

Keywords:

Raspberry pi 4, API, HTTP, Telegram, Quality osf Service

Abstract

The problem of waste management creates daily rubbish buildup due to thorough sorting. garbage sometimes accumulates in public garbage receptacles due to officials' ignorance of bin capacity and collectors' schedules, causing unclean conditions and the development of deadly diseases. Internet of Things technology was used to create a smart waste classification system with a notification mechanism in this study. This system classifies waste into plastic, metal, B3, and organic using a Raspberry Pi 4, camera module, and deep learning model. The classification uses a Convolutional Neural Network to speed up waste processing and separation. This research can be linked with research on separating trash types in one container and then allocated to garbage bins by type. Ultrasonic sensors and Raspberry Pi 4 can continuously monitor waste levels by sending data to the Ubidots IoT platform over HTTP. Based on experimental device data, system analysis shows 90% classification accuracy for all four waste categories. A Wireshark network analysis showed 61,098 bytes/s of throughput, 16 ms of delay, and zero data loss, demonstrating the system's ability for real-time monitoring and alerting. This research provides a realistic, cost-effective, and minimal solution to improve garbage classification and reduce collection costs to promote sustainability.

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2024-12-23

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[1]
Y. Yuliza, “Raspberry Pi 4 and Ultrasonic Sensor for Real-Time Waste Classification and Monitoring with Capacity Alert System”, J. Ilm. Tek. Elektro Komput. Dan Inform, vol. 10, no. 4, pp. 803–816, Dec. 2024.

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Vol. 10 No. 4 (2024): December

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Copyright (c) 2024 Yuliza Yuliza, Rachmat Muwardi, Prima Wijaya Kusuma, Lenni Lenni, Rizky Rahmatullah, Mirna Yunita, Akhmad Wahyu Dani

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