Human-Wildlife Conflict Early Warning System Using the Internet of Things and Short Message Service
Human-wildlife conflict (HWC) is an important challenge to communities living in areas bordering wildlife game parks and reserves. It is more evident in the United Republic of Tanzania, whose economy depends on wildlife tourism. This paper proposes a low-cost and low-power early warning system usin...
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| Format: | Article |
| Language: | English |
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D. G. Pylarinos
2022-04-01
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| Series: | Engineering, Technology & Applied Science Research |
| Subjects: | |
| Online Access: | https://etasr.com/index.php/ETASR/article/view/4662 |
| _version_ | 1798036650571333632 |
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| author | E. K. Ronoh S. Mirau M. A. Dida |
| author_facet | E. K. Ronoh S. Mirau M. A. Dida |
| author_sort | E. K. Ronoh |
| collection | DOAJ |
| description |
Human-wildlife conflict (HWC) is an important challenge to communities living in areas bordering wildlife game parks and reserves. It is more evident in the United Republic of Tanzania, whose economy depends on wildlife tourism. This paper proposes a low-cost and low-power early warning system using the Internet of Things (IoT) and Short Message Service (SMS) to support HWC respond teams in mitigating these challenges. The system comprises three primary units: sensing, processing, and alerting. The sensing unit consists of a Passive Infrared (PIR) sensor, a Global Positioning System (GPS), and a Raspberry Pi camera. The PIR sensor detects the proximity of the animal using the heat signature, GPS senses and records the current location, while the Raspberry Pi camera has the primary purpose of taking a picture after the PIR sensor detects the proximity of the animal. The processing unit with a Raspberry microcomputer performs data processing and image inferencing using the You Only Look Once (YOLO) algorithm. Last is the alerting unit, which includes a Global System for Mobile (GSM) communications module for sending SMS messages to the human-wildlife conflict response team and the nearer community response team leader whenever wild animals are spotted near the park’s border. The system detects, identifies, and reports the detected wild animals. The GPRS provides internet connectivity to support data collection, storage, and monitoring in the cloud.
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| first_indexed | 2024-04-11T21:15:48Z |
| format | Article |
| id | doaj.art-735a2b4bb4f747c391058a45a9c6405a |
| institution | Directory Open Access Journal |
| issn | 2241-4487 1792-8036 |
| language | English |
| last_indexed | 2024-04-11T21:15:48Z |
| publishDate | 2022-04-01 |
| publisher | D. G. Pylarinos |
| record_format | Article |
| series | Engineering, Technology & Applied Science Research |
| spelling | doaj.art-735a2b4bb4f747c391058a45a9c6405a2022-12-22T04:02:49ZengD. G. PylarinosEngineering, Technology & Applied Science Research2241-44871792-80362022-04-0112210.48084/etasr.46623903Human-Wildlife Conflict Early Warning System Using the Internet of Things and Short Message ServiceE. K. Ronoh0S. Mirau1M. A. Dida2School of Computational and Communication Science and Engineering, Nelson Mandela African Institution of Science and Technology, TanzaniaSchool of Computational and Communication Science and Engineering, Nelson Mandela African Institution of Science and Technology, TanzaniaNelson Mandela African Institute of Science and Technology, Tanzania Human-wildlife conflict (HWC) is an important challenge to communities living in areas bordering wildlife game parks and reserves. It is more evident in the United Republic of Tanzania, whose economy depends on wildlife tourism. This paper proposes a low-cost and low-power early warning system using the Internet of Things (IoT) and Short Message Service (SMS) to support HWC respond teams in mitigating these challenges. The system comprises three primary units: sensing, processing, and alerting. The sensing unit consists of a Passive Infrared (PIR) sensor, a Global Positioning System (GPS), and a Raspberry Pi camera. The PIR sensor detects the proximity of the animal using the heat signature, GPS senses and records the current location, while the Raspberry Pi camera has the primary purpose of taking a picture after the PIR sensor detects the proximity of the animal. The processing unit with a Raspberry microcomputer performs data processing and image inferencing using the You Only Look Once (YOLO) algorithm. Last is the alerting unit, which includes a Global System for Mobile (GSM) communications module for sending SMS messages to the human-wildlife conflict response team and the nearer community response team leader whenever wild animals are spotted near the park’s border. The system detects, identifies, and reports the detected wild animals. The GPRS provides internet connectivity to support data collection, storage, and monitoring in the cloud. https://etasr.com/index.php/ETASR/article/view/4662edge machine learningraspberry pihuman-wildlife conflictearly warning systemcamera trap |
| spellingShingle | E. K. Ronoh S. Mirau M. A. Dida Human-Wildlife Conflict Early Warning System Using the Internet of Things and Short Message Service Engineering, Technology & Applied Science Research edge machine learning raspberry pi human-wildlife conflict early warning system camera trap |
| title | Human-Wildlife Conflict Early Warning System Using the Internet of Things and Short Message Service |
| title_full | Human-Wildlife Conflict Early Warning System Using the Internet of Things and Short Message Service |
| title_fullStr | Human-Wildlife Conflict Early Warning System Using the Internet of Things and Short Message Service |
| title_full_unstemmed | Human-Wildlife Conflict Early Warning System Using the Internet of Things and Short Message Service |
| title_short | Human-Wildlife Conflict Early Warning System Using the Internet of Things and Short Message Service |
| title_sort | human wildlife conflict early warning system using the internet of things and short message service |
| topic | edge machine learning raspberry pi human-wildlife conflict early warning system camera trap |
| url | https://etasr.com/index.php/ETASR/article/view/4662 |
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