Livestock Monitoring System Using Convolutional Neural Networks - Pranjal Borhade, Shweta Kamble, Pratiksha Kate, Priya Newale, Prof. Meghana Lokhande, Aniket Nikam (International Journal of Advanced Science and Technology, 2020)
Farming is the wellspring of salary in numerous nations. So the mixed farming becomes the most critical question. A lot of farmers don’t know how to compromise with several executing maladies and extended rearing expenses. Hence it is principal for the ranchers to utilize the beneficial and specialized way to deal with improve the efficiency and reducing the ailments. In this examination, we use Internet of Things to record dairy steer’s exercises. The reasonable sensors help to expose relevant actions like when a cow is ill or on temperature. The sensors assemble information, for example, temperature and steps tally and hand over it to the Arduino. The Arduino gather the information from sensors and flexibly the data as needs be to the checking site. In case there are any fluctuations in temperature or steps count then proposed system will reveal the farmers to take the images of dairy cattle. Proposed system uses CNN algorithm for image identification and feature extraction. It gives more certainty compared to other algorithms.