1] TRACKING AGRICULTURE USING QGIS : We aim to track agricultural production using QGIS , a geospatial software to track Rainfall , Temperature , Humidity , Location and other Crop parameters. We can also get location data which would help farmers to know what crops can be grown and in which area.
2]CROP PREDICTION USING ML : Based on parameters like SEASON, LOCATION,TEMPERATURE,RAINFALL , HUMIDITY, we will predict crops and help farmers to grow the crops to gain maximum benefit and yield.
3]PRECISION AGRICULTURE Precision agriculture (PA) is an approach to farm management that uses IT to ensure that the crops and soil receive exactly what they need for optimum health and productivity. The goal of PA is to ensure profitability, sustainability and protection of the environment.
4]SMART FARMING Smart Farming is an emerging concept that refers to managing farms using modern Information and Communication Technologies to increase the quantity and quality of products while optimizing the human labor required.
Tools and technologies that you learnt and used in the project.
- Python
- Machine Learning
- Flask
- Javascript
- HTML
- CSS (basic)
- Bootstrap
- Drive to web(for deployment)
Clone the repo
$ git clone https://github.com/SaminaAttari786/QGIS--CROP-PREDICTION-WEBSITE-USING-ML.git
Run the app.py file using the command -
$ python app.py
We have developed a project which will help the farmers to know about their crop before cultivating onto the agricultural field and thus help them to make the appropriate decisions. It attempts to solve the issue by building a prototype of an interactive prediction system.
Thus we have implemented such a system with a QGIS and Geo referencing and easy-to-use web based graphic user interface and the Random Forest Machine learning algorithm to predict crop results based on the parameters.
- SAMINA ATTARI
- KHUSHI BARJATIA
- PIYUSHA BHARAMBHE
- MANSI KADAM
