We are few engineering students from India, from an Agricultural based country, we would like to give out a helping hand to the farmers of the agricultural sector to prevent the damage from wild animals attack. For the past few months, our farmers lost a lot of crops due to elephant attacks, like cardamom, Banana tree etc, costing their hard-worked crops. Along with our technological advancements, we aim to protect crops from attacks of wild animals like elephants. We are on a mission that could save acres of crops, thereby improve the livelihood of our farmers. The death of farmers because of wild animal attacks was one of the main reasons for our idea. Through this system, we can reduce human and elephant conflict.
What it does
It helps the farmers and protects their crops from the attack of elephants. If any animal like elephants cross or enter the farm, We will drive it away. We are using the camera module to take the input from the agriculture field and passed to the MobileNet object detection model that is running in the raspberry pi. The object detection model performs inference on the input frame given to the model and produce the output. Then it sorts out which animal has entered and an alarm is triggered . The alarm is followed by the generation of ultrasonic sound waves, which could make the animals run away back to deep forest.
How we built it
We have a camera module to capture the images and we sent the images to a Raspberry Pi module, the module is programmed with our codes. Whenever an elephant comes nearby, it triggers an alarm, then the protection system gets activated. Generating ultrasonic waves makes the elephant go away.
Challenges we ran into
The main challenge was to detect wild elephants crossing zone/locality. Then we applied object detection to our project. we learned more object detection from the TensorFlow website and other tutorials help us to build the project easily.
Accomplishments that we're proud of
- We are happy to see the smiles of our farmers.
- Farmers were able to get some sleep.
- We were able to learn more about the agriculture sector.
- After a long time, we were able to solve the problem.
- Dedication to solving an agricultural-based problem.
- We were able to go into deep forest exploration.
- Ability to go nocturnal. (sleepless nights).
What we learned
We learned how to use machine learning in the field of agriculture. we could apply machine learning to protect our farmers and agricultural fields. We believe by using our project we could elevate the agriculture sector, raise the standards of crop protection. Reduce the tension faced by farmers.
What's next for ELEPHANT DETECTOR
We are planning to implement the same idea in reserved forests, preferably the borders of the forest. so that we can prevent wild animals from entering villages. At the same time, Illegal hunting and poaching can be prevented in reserved forests by using the same idea, instead of detecting animals we detect humans and trigger alarm. In this project we used object detection to detect the presence of the elephant in the future we are adding the feature that detects the presence of elephants forms the sounds of elephants. In the future, we are on our way to implementing sound detection to improve the efficiency of our system. Moreover, we will be using this with sound, find even if we are blind at night. Our project is live on Github, as public suggestions are welcomed.