Our project aims to offer AI-based solutions in the agricultural sector to increase efficiency for farmers and agriculture professionals while promoting sustainability. As Agrovech, we developed a platform that uses satellite and drone-based technologies to analyze data from agricultural fields to optimize every stage of agricultural production.

The main components of our project are:

AI-Powered Agricultural Analyses: Multispectral data from satellite and drone imagery are processed with AI algorithms to analyze key parameters such as plant health, moisture, crop density, yield estimation, and harvest timing in agricultural fields.

Specialized Analytical Tools: Our project uses various vegetation indices like NDVI, GNDVI, and MSAVI to conduct regional analyses in agriculture. Additionally, segmentation-based AI models allow us to identify plant types, boundaries, and problematic areas.

Data-Based Forecasting and Planning: Using historical data analysis and machine learning models, we can forecast yields and optimize the use of resources such as water, fertilizer, and pesticides. This helps farmers increase efficiency and adopt sustainable agricultural practices.

Satellite and Drone-Based Solutions: Our project offers satellite and drone-based data collection services to farmers. Users can access detailed information about the condition of their fields through our platform and take action when needed.

We are a Startup based on University.
I am a Assistant Prof. and CEO of Agrovech.
We have 12 people in difrerent areas and we have specialised in AI and remote sensing apllication also Drone development for tailored solutions.