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An Efficient Scene Understanding System for Digital Farming to Detect Animal and Pest Attack Using Deep Learning 

An Efficient Scene Understanding System for Digital Farming to Detect Animal and Pest Attack Using Deep Learning 

The objective of our project is

  • To provide protection from the attacks of the wild animals and birds and thus minimizing the probable loss to the farmer. This project will detect intrusion around the farm and capture the image of the intruder and classifying them using image processing. Then a suitable action can be taken based on the type of the intruder and send notification to farm owner using GSM. 
  • To design a system that farmers could use as a scale pest detector for early prevention of crop damage. The proposed system is planned to be implemented with the help of smartphones to help farmers by detecting scale pests with high efficiency. In order to accomplish this objective, a mobile application using the trained scale pest recognition model should be developed to facilitate pest identification in farms, which will be helpful in applying appropriate pesticides to reduce crop losses. 

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