"Save crops from locust attacks"
Web App: https://locustlocator.vercel.app 🔗
Live Demo: https://youtu.be/C1QmCuzrBw8 🔗
LLAM tracks the realtime locusts location and visualizes wind patterns on earth. Predicts the probability of locust attacks on a particular given position through satellite imagery using machine learning models.
This project is designed keeping the problems that farmers face due to locusts in mind. We aim to reduce the destruction of crops caused by locusts which leads to massive effect on socio-economic interests of farmers.
The inspiration behind L.L.A.M was that locusts are increasingly becoming a great threat to the vegetation and this threat is reportedly going to increase each year. To safeguard crops and farmers from this plague we needed some solution that could tackle the problem well.
- The first challenge we ran into was how will we collect the relevant data.
- Then we had to decide how will we visualize the frontend with that data.
- Changing code to fit our Next js frontend framework.
- Populate data with efficiency because alot of gpu power was required.
- Rendering terrains and maps in Cesium Js.
- Visualizing the data on 3d earth.
- Rendering the satellites on earth from which the data is retrieved.
- ML model predictions from satellite imagery.
- Team did phenomenal job at helping each other and integrating stuff together.
- Using Microsoft Azure services for creating sick APIs.
- Cesium Js framework to render and perform functions on 3D earth.
- Amazing Next Js features.
- More optimization have to be made.
- Improve accuracy
- Add layer to predict locust movement using wind data
Web App: https://locustlocator.vercel.app 🔗
Live Demo: https://youtu.be/C1QmCuzrBw8 🔗
- NextJS
- Node.js 10+
- Command Line Tools
- Mac OS X: Xcode (or OS X 10.9+:
xcode-select --install
) - Windows: Visual Studio OR Visual Studio Code + Windows Subsystem for Linux - Ubuntu
- Ubuntu / Linux Mint:
sudo apt-get install build-essential
- Fedora:
sudo dnf groupinstall "Development Tools"
The easiest way to get started is to clone the repository:
# Cloning the repo
git clone https://github.com/Jappan07/LLAM
# Change directory
cd LLAM
# Install NPM dependencies
npm install
# Then simply start your app
npm run dev
# project will start at localhost:3000
visit https://localhost:3000 on any browser.
Note: GPU intensive features are added into this project so it is suggested to run this application on a machine having dedicated gpu so that it could run smoothly.
The MIT License (MIT)