Innovation Case Study

Krishi Track: Smart Farming for the Future

Empowering farmers with AI-driven insights and real-time environmental monitoring.

Project Overview

Bridging traditional farming with modern technology.

The Challenge

Farmers in Nepal frequent face challenges like unpredictable weather, pest infestations, and lack of real-time soil data, leading to reduced yields and resource wastage. Traditional methods often rely on intuition rather than data.

The Solution

Krishi Track is a comprehensive system combining low-cost hardware sensors with advanced AI algorithms. It monitors soil health, detects early signs of plant disease via camera feeds, and provides actionable insights directly to the farmer's smartphone.

Krishi Track Concept

Technology Stack

Built with robust, open-source technologies for reliability and scale.

Artificial Intelligence

TensorFlow Lite models running on edge devices for real-time disease detection without needing heavy internet bandwidth.

IoT Hardware

ESP32 and Raspberry Pi based sensor nodes collecting data on moisture, humidity, temperature, and NPK levels.

Linux Infrastructure

Powered by custom Linux kernels optimized for low-power ARM devices to ensure long battery life in the field.

Key Features

What makes Krishi Track specific and effective.