Detection and Identification of Animals in Wild Life Sanctuaries using Convolutional Neural Network
Ramakant Chandrakar1, Rohit Raja2, Rohit Miri3, S R Tandan4, K. Ramya Laxmi5
1Ramakant Chandrakar, Research Scholar, Department of CSE, Dr. C. V. RAMAN University, Bilaspur, India.
2Rohit Raja*, Professor, Department of CSE, Sreyas Institute of Engineering and Technology, Nagole, Hyderabad, India.
3Rohit Raja, Professor, Department of CSE, Dr. C. V. RAMAN University Bilaspur, India.
4S. R. Tandan, Professor, Department of CSE, Dr. C. V. RAMAN University Bilaspur, India.
5K Ramya Laxmi, Assistant Professor, Department of CSE, Sreyas Institute of Engineering and Technology, Nagole, Hyderabad.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 181-185 | Volume-8 Issue-5, January 2020. | Retrieval Number: E4579018520/2020©BEIESP | DOI: 10.35940/ijrte.E4579.018520
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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: Comprehensive, Precise and real time data regarding the position and characteristics of animals is necessary for safeguarding visitors inside a wildlife sanctuary. Investigations are made on the capability for automated, unambiguous and economical collection of data that are useful to perform rescue operations within the sanctuary because of the absence of other communicational sources. Web camera enables collection of photos relating to wildlife economically, conservatively as well as regularly. Extraction of information from such photos is costly, slow and requires human intervention. The proposed system demonstrates the automatic extraction of such data using Convolutional Neural Network (CNN). Deep CNN is trained for a set of images available in a wildlife dataset.
Keywords: Convolutional Neural Network, Web camera, Extraction.
Scope of the Article: Sensor Networks, Actuators for Internet of Things.