OPTIMIZATION OF TRASH BIN USAGE BASED ON INTERNET OF THINGS (IOT)

Authors

  • Ari Adrian Tanjungpura University
  • Muhammad Saleh Tanjungpura University
  • Syaifurrahman - Tanjungpura University
  • Supriono Supriono Dept. of Electrical Engineering, Faculty of Engineering, Tanjungpura University

DOI:

https://doi.org/10.26418/telectrical.v2i1.77615

Keywords:

Trash height, Methane gas, Ammonia gas, Hydrogen sulfide gas, Trash weight

Abstract

Trash is a byproduct of human activity that poses serious challenges in its management. Suboptimal handling can lead to trash spread, create uncomfortable environmental conditions, and produce hazardous gases such as methane, ammonia, and hydrogen sulfide. To address this, an Internet of Things (IoT)-based trash bin optimization system is needed. This system includes monitoring trash height, gases produced by the trash, and trash weight using sensors installed on the trash bin, such as the HC-SR04 ultrasonic sensor, MQ-4 sensor, MQ-135 sensor, TGS2602 sensor, and load cell sensor. Additionally, the system is equipped with an automatic lid system using the MG995 servo motor and Solenoid Lock Door to lock the trash bin when it is full. Specific limits have been set for each trash parameter, and if they exceed these limits, the automatic system will lock the trash bin and send notifications through the Blynk application on a smartphone. Component testing in this research has shown satisfactory results, with high levels of accuracy. Overall, the designed system successfully optimizes the use of trash bins by providing immediate notifications to sanitation workers when the trash bin is full, preventing scattered trash piles, and maintaining the safety and comfort of the surrounding environment.

Author Biographies

Ari Adrian, Tanjungpura University

Electrical Engineering Study Program

Muhammad Saleh, Tanjungpura University

Department of Electrical Engineering

Syaifurrahman -, Tanjungpura University

Department of Electrical Engineering

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Published

2024-06-07

Issue

Vol. 2 No. 1: June 2024

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