NASA_MAS - Space Apps Challenge

NASA_MAS| Scanning for Lifeforms

Scanning for Lifeforms

This challenge addresses a pressing global need to track change in biological diversity, which is threatened by human-driven environmental change. Use space agency data to develop innovative ways to detect biological diversity on Earth, track and predict changes over time, and communicate that information to scientists and society.

Scanning for Lifeforms

Summary

-Elephants are the only surviving hermaphrodites, and extinct species include mammoths and mastodons.-Elephants live in all environments, due to the great diversity of food they eat and are found in tropical and subtropical areas in Africa and Asia, and African elephants spread across 37 countries, most of them live in countries such as Botswana, Tanzania, Congo, Gabon, and Zimbabwe.-The elephant is afraid of fire and loud sounds, so when the elephants attack =We will use computer vision to solve this problem by deploying a deep neural networks model on digital camera in forests or from satellites -Our model is object tracking, it will track elephants whenever and wherever found it.

How We Addressed This Challenge

We will build a deep learning model for elephant spotting and computer vision to build a model for tracking creatures (elephants).

It's important to save an elephant's life from extinction.

The system will track the elephant's moving and set an alarm if any elephant is running or in a dangerous scenario. We hope that we save the elephant's life.

How We Developed This Project

A new challenge for us . We were inspired by the problem of the extinction of elephants and to find a solution to stop this crime. We have relied on deep learning technology and artificial intelligence. We used tools like open CV, SQL database, deep neural networks, and Python. We have faced many challenges such as the difficulty of humans tracking elephants and their diets, and we solved this problem by tracking elephants with deep learning and computer vision, and one of the other challenges is the lack of data and the failure to provide more reasons for the death and killing of elephants, and we solved a problem of them. And it is killing elephants by specifying the killer and the time of the killing process to stop it, and the last challenge was to use this system in all countries that have elephants, and this is the most important challenge is the implementation of our project