Pose Detection and Recurrent Neural Networks for Monitoring Littering Violations
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 b...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
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| Series: | Eng |
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| Online Access: | https://www.mdpi.com/2673-4117/4/4/155 |
| _version_ | 1797381178113654784 |
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| author | Nyayu Latifah Husni Okta Felia Abdurrahman Ade Silvia Handayani Rosi Pasarella Akhmad Bastari Marlina Sylvia Wahyu Rahmaniar Seyed Amin Hosseini Seno Wahyu Caesarendra |
| author_facet | Nyayu Latifah Husni Okta Felia Abdurrahman Ade Silvia Handayani Rosi Pasarella Akhmad Bastari Marlina Sylvia Wahyu Rahmaniar Seyed Amin Hosseini Seno Wahyu Caesarendra |
| author_sort | Nyayu Latifah Husni |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T20:48:35Z |
| format | Article |
| id | doaj.art-3ca7766e813645baa8ae891dc5c5f1ab |
| institution | Directory Open Access Journal |
| issn | 2673-4117 |
| language | English |
| last_indexed | 2024-03-08T20:48:35Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Eng |
| spelling | doaj.art-3ca7766e813645baa8ae891dc5c5f1ab2023-12-22T14:06:15ZengMDPI AGEng2673-41172023-10-01442722274010.3390/eng4040155Pose Detection and Recurrent Neural Networks for Monitoring Littering ViolationsNyayu Latifah Husni0Okta Felia1Abdurrahman2Ade Silvia Handayani3Rosi Pasarella4Akhmad Bastari5Marlina Sylvia6Wahyu Rahmaniar7Seyed Amin Hosseini Seno8Wahyu Caesarendra9Department of Electrical Engineering, Politeknik Negeri Sriwijaya, Palembang 30139, IndonesiaDepartment of Electrical Engineering, Politeknik Negeri Sriwijaya, Palembang 30139, IndonesiaDepartment of Electrical Engineering, Politeknik Negeri Sriwijaya, Palembang 30139, IndonesiaDepartment of Electrical Engineering, Politeknik Negeri Sriwijaya, Palembang 30139, IndonesiaDepartment of Computer Engineering, Faculty of Engineering, Universitas Sriwijaya, Indralaya 30862, IndonesiaPalembang City Public Works and Spatial Planning Department, Ilir Timur Dua, Palembang 30114, IndonesiaPalembang City Public Works and Spatial Planning Department, Ilir Timur Dua, Palembang 30114, IndonesiaInstitute of Innovative Research, Tokyo Institute of Technology, Yokohama 226-8503, JapanDepartment of Computer Engineering, Faculty of Engineering, Ferdowsi University of Mashhad, Azadi Square, Mashad 917794897, IranFaculty of Integrated Technologies, Universiti Brunei Darussalam, Tungku Link St., Gadong BE1410, BruneiInfrastructure 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.https://www.mdpi.com/2673-4117/4/4/155activity monitoringartificial intelligenceIoTmachine learningpose detectionrecurrent neural network |
| spellingShingle | Nyayu Latifah Husni Okta Felia Abdurrahman Ade Silvia Handayani Rosi Pasarella Akhmad Bastari Marlina Sylvia Wahyu Rahmaniar Seyed Amin Hosseini Seno Wahyu Caesarendra Pose Detection and Recurrent Neural Networks for Monitoring Littering Violations Eng activity monitoring artificial intelligence IoT machine learning pose detection recurrent neural network |
| title | Pose Detection and Recurrent Neural Networks for Monitoring Littering Violations |
| title_full | Pose Detection and Recurrent Neural Networks for Monitoring Littering Violations |
| title_fullStr | Pose Detection and Recurrent Neural Networks for Monitoring Littering Violations |
| title_full_unstemmed | Pose Detection and Recurrent Neural Networks for Monitoring Littering Violations |
| title_short | Pose Detection and Recurrent Neural Networks for Monitoring Littering Violations |
| title_sort | pose detection and recurrent neural networks for monitoring littering violations |
| topic | activity monitoring artificial intelligence IoT machine learning pose detection recurrent neural network |
| url | https://www.mdpi.com/2673-4117/4/4/155 |
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