Eng (Oct 2023)

Pose Detection and Recurrent Neural Networks for Monitoring Littering Violations

  • Nyayu Latifah Husni,
  • Okta Felia,
  • Abdurrahman,
  • Ade Silvia Handayani,
  • Rosi Pasarella,
  • Akhmad Bastari,
  • Marlina Sylvia,
  • Wahyu Rahmaniar,
  • Seyed Amin Hosseini Seno,
  • Wahyu Caesarendra

DOI
https://doi.org/10.3390/eng4040155
Journal volume & issue
Vol. 4, no. 4
pp. 2722 – 2740

Abstract

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Infrastructure development requires various considerations to maintain its continuity. Some public facilities cannot survive due to human indifference and irresponsible actions. Unfortunately, the government has to spend a lot of money, effort, and time to repair the damage. One of the destructive behaviors that can have an impact on infrastructure and environmental problems is littering. Therefore, this paper proposes a device as an alternative for catching littering rule violators. The proposed device can be used to monitor littering and provide warnings to help officers responsible for capturing the violators. In this innovation, the data obtained by the camera are sent to a mini-PC. The device will send warning information to a mobile phone when someone litters. Then, a speaker will turn on and issue a sound warning: “Do not litter”. The device uses pose detection and a recurrent neural network (RNN) to recognize a person’s activity. All activities can be monitored in a more distant place using IoT technology. In addition, this tool can also monitor environmental conditions and replace city guards to monitor the area. Thus, the municipality can save money and time.

Keywords