Abstract: Photographers frequently encounter a variety of issues when taking wildlife photographs. Many local and foreign wildlife photographers struggle with the lack of an efficient tool for detecting and discovering endemic Sri Lankan birds. A mobile application called "Ceylon Birds" was developed as a solution for these issues. It uses birds’ images, voices, and habitats to identify the birds. This mobile application will access the device’s camera, recorder, and Global Positioning System to accurately identify the bird, habitats and provide the bird’s details to the photographer. The concepts of Machine Learning, Natural Language Processing, and Neural Networks are used for this application. The information supplied by the Wildlife Officers, experts in this sector, was used to develop this application. The main goals of the suggested solution are to locate the regions where the majority of birds are present during a relevant time period and to clearly identify endemic birds by their physical characteristics and tones of voice. The trained Machine Learning models have achieved the accuracy of 92%, 90%, and 88% for the voice detection model, image identification model, and location clustering model respectively. After testing this “Ceylon Birds” mobile application among wildlife photographers, we have received positive feedback from them.
Keywords: image identification, voice detection, location clustering, machine learning.
Title: Detection of Endemic Sri Lankan Birds Using AI-Based Software
Author: K.A.S.H Kulathunga, S.A.M Piyabhashitha, S.A.D.H.A Jayatilake, Jeewaka Perera, Dhammika Silva
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
Vol. 10, Issue 4, October 2022 - December 2022
Page No: 10-16
Research Publish Journals
Website: www.researchpublish.com
Published Date: 21-October-2022
