Smart Crop Protection Against Animal Encroachment using Deep Learning

In today's world, agriculture faces numerous challenges, one of which is animal intrusion that poses a threat to crop yields and food security. However, with the help of IoT and DL techniques, farmers can now tackle this challenge effectively. By using devices such as LED, Buzzer, Pi Camera, and ESP8266 Wireless Fidelity module, farmers can execute a machine algorithm that is capable of identifying animals and alerting them when they are approaching their fields. The success of this technique lies in the use of Convolutional neural networks that are based on a region and one-shot detection algorithms, both of which use machine learning methods to categorize animals and identify objects in photos. While both techniques are critical, the location-based convolutional neural network is outperformed by the Single Shot Detection approach. This is because it is faster and more accurate. To ensure that farmers receive timely information, the Twilio API-interfaced program provides them with the relevant information they need to take action in their fields. With this system in place, farmers can now safeguard their crops and improve their profits, ultimately contributing to food security.