AI + IoT • Smart Agriculture

AI Powered Drones for Agricultural & Environmental Monitoring

A unified UAV platform integrating AI vision, IoT sensor arrays, and cloud telemetry to deliver high-precision agricultural analytics and environmental surveillance.

Explore Features System Architecture
AI
Real-time Object Detection
Edge & cloud inference
IoT
Multi-sensor Telemetry
Temp, Humidity, Gas, GPS
 System Demo Video
Coverage: 35 acres
Sync: Cloud
Status: Active
Overview

Project Context & Vision

An autonomous drone system that senses, analyses and reports crop and environmental conditions — from microclimate to intrusion detection — using AI, IoT and cloud services.

What the system does

Our drone carries calibrated IoT sensors (temperature, humidity, gas, GPS) and a camera. During flight it gathers multi-modal data, runs AI-based detection, and streams events and telemetry to a secure cloud dashboard.

  • Geo-tagged sensor readings across flight path
  • Onboard/edge image inference for detection
  • Cloud ingestion, storage and alerting

Project Snapshot

  • Team: Ranjith V, Rahul Raveendran, S. Avinash
  • Program: B.Tech — AI & Data Science, Vel Tech
  • Timeline: July 2025 — November 2025
Features

Why it matters + How we solve it

IoT Environmental Sensing

Continuous temperature, humidity and gas monitoring tied to GPS coordinates for spatial analysis.

AI Object Detection

Real-time detection of humans, animals and anomalies using a lightweight detection model optimized for aerial footage.

Cloud Dashboard

Live telemetry, maps, alerts and historical mission playback accessible from any browser.

Secure Telemetry

4G/5G or Wi-Fi connectivity with authenticated endpoints for reliable data transfer.

Mission Planning

Pre-defined GPS waypoints and repeatable coverage patterns for scheduled scans.

Adaptable Payloads

Supports camera, thermal modules and additional sensors for specialized use cases.

Architecture

System Layers & Components

Hardware Stack

  • Drone Frame: Multirotor platform for stable patrols.
  • Companion Computer: Handles camera & inference.
  • Sensors: Temp, Humidity, Gas, GPS modules.
  • Power: Li-Po packs sized for mission duration.

Software & Cloud

  • Cloud Backend: MQTT/REST ingestion & alerts.
  • AI Pipeline: YOLO-style detection model.
  • Dashboard: Maps, charts, mission replay.
  • Security: Encrypted data transfer.
Applications

High-impact Use Cases

Smart Crop Monitoring

Track micro-climate and irrigation across fields for timely interventions.

Forest & Wildlife

Detect intrusions and illegal activity in protected areas.

Disaster Response

Collect aerial imagery and gas readings in risky zones without human exposure.

Pollution Monitoring

Measure gas concentrations around industrial belts and urban hotspots.

Perimeter Security

AI-assisted patrols for farm, plant or border security with fast alerts.

Livestock Tracking

Monitor herd distribution and locate stray animals quickly.

Behind the build

Our Team

A focused team of B.Tech students from AI & Data Science — combining hardware, AI, and cloud expertise.
Rahul Raveendran
Rahul Raveendran
DashBoard Engineer
Expert in data visualization and dashboard UX interfaces for mission control.
Avinash S
Avinash S
Cloud Engineer
Manages cloud infrastructure, database scalability, and secure API endpoints.
Ranjith V
Ranjith V
AI-System Integration Engineer
Leads the AI pipeline architecture and seamless integration of hardware, software, and cloud systems.
Repository

Explore the Code

Project Repository
Access the complete source code, hardware schematics, and simulation scripts.
View Repository
References

Source & Reading

  • Project Report. AI Powered Drones – Agricultural & Environmental Monitoring.
  • Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College - Department of AI & DS.