This project is to prevent Elephant poaching using an effective ML model that detects the presence of humans near the Wild Elephants
There has been an upsurge in poaching and illegal ivory trafficking in recent years across the world. One of the main reasons for this increase is Insufficient anti-poaching capacity, weak law enforcement, lack of use of effective technologies, and corruption undermine efforts to stop poaching and trafficking in some countries.
My project is mainly made for preventing Elephant poaching by monitoring and detecting the presence of human beings in the areas where wild Elephants live and by alerting the wildlife rangers using an alert Multimedia Messaging Service(MMS) along with the detected details. The cameras and other sensors will always monitor the area where the wild Elephants are more found and detect the presence of humans by using effective Machine Learning(ML) models. The given below is the complete functioning flow diagram of this project.
Once if humans are detected in the areas near Elephants, an alert message with the captured image and location will be sent to the wildlife rangers' phone
Detection of elephants and humans is done with the help of an efficient Machine Learning(ML) model. Machine Learning(ML) model is mainly programmed using the Python programming language and TensorFlow framework.
Edge Impulse Studio is used for creating an efficient ML model to classify and detect the presence of humans in the wildlife. Using the Edge Impulse Studio the model can be easily converted to a Lite model that can be also used on Android applications with the help of TensorFlow Lite. Also, it helps to interface and deploy model with any hardware components like Arduino, Xilinx, Raspberry, OpenMV, Web Assembly, and also on the web applications by converting it into supporting libraries. Version control and Deployment are very easy using Edge Impulse Studio.
The image classification model has been developed using Edge Impulse Studio. The various steps involved in the Edge Impulse Studio for building an efficient ML model includes:
- Devices Edge
- Data Acquisition
- Impulse Design
- Retrain Model
- Live Classification
- Model Testing
- Versioning
- Deployment
Here I have used an online platform called Twilio (twilio.com). Twilio allows software developers to programmatically make and receive phone calls, send and receive text messages, and perform other communication functions using its web service APIs for free for a limited amount of times. In most of the Surveillance cameras used for wildlife-security uses GPS either you can use the maps or geolocation APIs to share the location or we can know the captured image's location using the image's information.
According to WWF, even after the ban on international trade of ivory, in Africa and other countries, elephants are still being poached in large numbers. More than Thousands of elephants are being killed every year for their ivory tusks. The ivory is often carved into ornaments, jewelry, and plays an important role in the black market.
In this current world of Machine Learning(ML), Artificial Intelligence(AI), and other valuable technologies, everything is very easy to develop and deploy. So only most of the problems can be solved by using technologies. The prevention of elephant poaching is possible by using these technologies. My project is an example of using technology effectively for saving or protecting the gentle giants in their natural habitats.