xxrokia/marawildlife

A web application focussing on wildlife tracking in maasai mara that uses IoT sensor data for real-time tracking, efficiently managed in MongoDB, with simulations mimicking real-world scenarios and predictive capabilities for wildlife conservation efforts. Documentation instructions Running the Web Application Visit the GitHub repository link: github.com Download the code as a zip file and open it in your code editor (e.g., Visual Studio Code). In the terminal of your code editor in the frontend directory, run the command: npm start. In the terminal of your code editor in the backend directory, run the command: node server.js Ensure the server is running, then open your web browser and navigate to: localhost. The application will now be successfully launched. For training and evaluation of the model, in the terminal of your code editor in the script directory, run the command: train_model.py You can access the database, download it and add it to your MongoDB compass. Here is the link to the Maasai Mara Mongo db database folder link: drive.google.com and Maasai Mara Mongo db database zip file link : drive.google.com Go to the database zip file link and click "Download" to save maasai_mara_backup.zip. Navigate to the download directory and unzip the file to create the maasai_mara_backup folder: unzip maasai_mara_backup.zip. Open MongoDB Compass and connect to your MongoDB instance (mongodb://localhost:27017) to restore the database In the terminal, navigate to the backup folder and restore the database: cd /path/to/maasai_mara_backup mongorestore --db maasai_mara ./maasai_mara_backup Then Refresh MongoDB Compass to see maasai_mara and ensure all collections and data are restored correctly.