Wildlife Monitoring in Zoological Parks Using RASPBERRYPI and Machine Learning
S K. Nayab Rasool1, T. S R.C H. Murthy2

1S K. Nayab Rasool, Assistant Professor, Department of ECE, Anurag Group of Institutions, Hyderabad (Telangana), India.
2T. S R.C H. Murthy, Assistant Professor, Department of ECE, Anurag Group of Institutions, Hyderabad (Telangana), India.
Manuscript received on 17 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 3016-3020 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B13870982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1387.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Wildlife monitoring in zoological parks using raspberry pi is the application of science and technology to monitor the wildlife enclosures in zoological parks and to maintain the security of animals. Recently many incidents that occur in zoo parks like animals escaping form cages and causing damage to other animals and humans, and also sometimes humans also fall into the enclosures of animals. Hence, designed a system that can monitor such conditions. This system is used for surveillance and security of animal to detect the intruder that entered the area of animals and also to detect if the animal escaped or missing from the enclosure. This system could also label what intruder has entered the enclosure using Machine Learning. The system consists of raspberry pi camera Rev 1.3 and SD card circuitry interfaced to a raspberry pi B+ board The raspberry pi camera takes the video of the cage and gives to the raspberry pi, then the obtained video streaming data is analyzed using opencv platform. In opencv platform the data is classified using Machine Learning algorithms. The data is analyzed to check whether any intruder entered the cage or if the animal escaped from the cage. If any of the conditions mentioned above occurs then the alerts are sent to the caretaker using IoT.
Keywords: Wild Life, Raspberry pi, Machine Learning, Python, Open Cv.
Scope of the Article: Machine Learning