AT
Autonomous Terrain RoverAutonomous Terrain Rover
Live Soil Dashboard...
Real-time soil monitoring · Autonomous rover · Firebase powered

Smart soil monitoring, built by students for real farms and labs.

The rover travels across the field, inserts the NPK sensor into the soil, and streams N, P, K, pH, EC, moisture and temperature to the cloud. This dashboard, the Flutter app and the lab report all read from the same real-time Firebase data.

ESP32 & Modbus RTU7-in-1 NPK SensorFirebase Realtime DBNext.js · Tailwind · TSXFlutter Mobile AppNeural Network (3-class)
📄 Read Full Report

Course: Measurement of Non-Electrical Quantities · Instructor: Assoc. Prof. Kamala Oghuz · Submitted: 8 December 2025

System at a glance

Robotics

Rover with NPK probe, stepper motor, DC motors and ToF sensors moves autonomously and performs in-situ sampling.

Cloud & Data

ESP32 sends every measurement to Firebase Realtime Database, which feeds both this dashboard and the mobile interface.

ML & Apps

A neural network classifies soil fertility (Good / Moderate / Poor), explained through the Flutter app and this web view.

Team

Ravan Khidirov · Farman Aliyev · Jabrayil Gasimli · Zahid Abdullayev · Hasanali Asadov

For Farmers

See real soil conditions instead of guessing. The rover helps avoid over-fertilizing rich zones and under-fertilizing weak areas.

For Students

A complete lab example: sensors, Modbus, ESP32, LabVIEW, Firebase, machine learning, Flutter and Next.js in one real project.

For Researchers

Bridges the gap between rare lab tests and indirect satellite data, enabling dense in-situ measurements for precision agriculture.

Live Rover Dashboard

Real-time tech view: robot state plus soil parameters directly streamed from Firebase Realtime Database.

Battery (demo)

85%

Demo value for presentation.

Speed

0 m/s

Illustrative rover speed.

Mode

Idle

Controlled via isWorking in Firebase.

Soil Parameters

These values are read from the same JSON that the Flutter app listens to.

Need every detail? The full methodology, hardware list, ML model and references are in the Report page.

Full Story Overview

The report behind this project explains why precision agriculture is critical for Azerbaijan, how the rover architecture is built (hardware, embedded software, Firebase cloud, ML model, Flutter app, and this Next.js dashboard), and what results were obtained during simulation and prototype tests. If a visitor wants academic depth—formulas, references, discussion, and future recommendations—everything is structured in sections 1–5 on the Report page.