DRISHTI-UAV: AI-Powered Autonomous Surveillance & Rescue Drone�
“Enhancing disaster response and defence surveillance using intelligent UAV systems.”
Objective: Enhance mission efficiency and reduce human risk
Team name: SKYFORGE
Team Members : Harshini R, N Anuja ,Abinaya S
Problem Statement
• Manual search operations are slow and risky
• Poor visibility (fog, rain, night) reduces human detection
• Large areas like borders and disaster zones require faster monitoring
Motivation & Need
Many disaster victims remain undetected for long periods, reducing survival chances
• Rescue teams and soldiers face high risk while searching in dangerous environments
• Poor visibility and complex terrains make human detection very difficult
• Traditional surveillance systems rely heavily on manual monitoring, causing delays
• AI-powered drones can improve detection speed and support faster rescue operations
• Large disaster areas and border regions require faster and more efficient monitoring systems
Proposed Solution – DRISHTI-UAV
• Uses RGB camera and thermal camera to detect humans even in low-visibility conditions
• Sensor fusion technology improves detection accuracy by combining multiple sensor data
• On-board AI processing enables real-time object detection without cloud dependency
• Autonomous search path planning helps the drone cover large areas efficiently
• Sends real-time alerts and location data to the control station for faster response
System Architecture
2. Intelligence & Processing� • AI object detection using YOLOv8
� • Sensor fusion combines data from multiple sensors for higher accuracy
� • Navigation support using Simultaneous Localization and Mapping (SLAM)
Working Methodology
WORKFLOW
Mission Start
↓
UAV Deployment
↓
Multi-Sensor Environment Scan
↓
AI Object Detection
↓
Sensor Fusion Verification
↓
Location Mapping (GPS + Depth)
↓
Live Alert to Control Station
↓
Rescue / Defence Response
AI & Technologies Used
• The drone is deployed in the target area for surveillance or rescue missions
• Sensors continuously scan the surroundings and collect environmental data
• The onboard AI analyzes the images using YOLOv8 for object detection
• Sensor fusion verifies detection using camera, thermal, and distance data
• The system records GPS location of the detected target
• Real-time alert is sent to the control station for immediate response
Implementation Strategy
PROTOTYPE MODEL & VIDEO
“This simulation demonstrates the working of our DRISHTI UAV detection system. An ultrasonic sensor is used to detect objects or humans in the search area. When the sensor detects a person within a certain distance, the system activates an alert using LEDs and sends a signal indicating a possible victim location. This represents how the drone would identify victims during a rescue mission.”
Unique Innovation – DRISHTI-UAV
thermal imaging, and LiDAR/ultrasonic sensors for higher
detection accuracy.
scans large areas using optimized search patterns.
.
Competitive Comparison
Feature | Traditional Surveillance Drones | DRISHTI-UAV (Proposed System) |
Human Detection | Mostly manual monitoring | AI-based detection using YOLOv8 |
Low Visibility Detection | Limited or not available | Thermal camera detects body heat |
Sensor Integration | Single camera system | Multi-sensor fusion (RGB + Thermal + Distance) |
Autonomous Operation | Mostly manual control | Autonomous search path planning |
Real-Time Alerts | Limited monitoring | Instant alerts to control station |
Detection Accuracy | Depends on operator | AI improves detection accuracy |
Application Areas | General surveillance | Defence + Disaster Rescue missions |
Cost Efficiency | High-cost advanced systems | Low-cost intelligent UAV solution |
Advantages
• Reduces risk to soldiers and rescue teams by using unmanned aerial surveillance
• Detects humans and vehicles even in low-light, fog, or night conditions using thermal sensing
• Covers large and difficult terrains quickly compared to ground patrol systems
• AI-based object detection enables faster and more accurate monitoring
• Multi-sensor fusion improves reliability by combining camera, thermal, and distance sensors
• Low-cost intelligent UAV system compared to traditional surveillance technologies
Cost Analysis
Project Cost (Estimated)
• Drone frame and motors – ₹15,000 – ₹40,000
• Flight controller and GPS module – ₹8,000 – ₹20,000
• RGB camera and thermal camera – ₹10,000 – ₹80,000
• Sensors (Ultrasonic / LiDAR / Weather sensor) – ₹5,000 – ₹20,000
• AI processing unit (Raspberry Pi / Jetson Nano) – ₹5,000 – ₹20,000
�
Total Prototype Cost
₹40,000 – ₹1,80,000 (depending on sensors used)
Target Users
Market Opportunity
Business Model
Applications & Use Cases
Border infiltration detection
Post-earthquake survivor detection
Border surveillance and intrusion detection Search & rescue during landslides and floods
Battlefield reconnaissance Disaster damage assessment
Support in GPS-challenged environments
Impact �
Challenges & Solutions
Challenge | Solution |
Battery limitation | High-capacity Li-Po battery |
Weather conditions | Weather-resistant sensors |
False detection | Multi-sensor verification |
Conclusion And Future Scope