PROBLEM STATEMENT:
Modern buildings are technologically advanced, but still dangerously reactive.
Current Critical Gaps:
1. Fire alarms trigger only after flames escalate.
2. Gas leaks remain undetected until human exposure.
3. Crowd stampedes are detected after panic spreads.
4. Industrial accidents go unnoticed in blind spots.
5. Elderly falls inside homes remain undiscovered for hours.
6. Most AI surveillance systems fail without internet.
7. Cloud-based systems raise privacy and latency concerns.
The Core Problem:
There is no unified, fully offline, predictive emergency intelligence system that:
•Integrates vision + audio + environmental data
•Confirms events using multi-sensor validation
•Predicts risk before escalation
•Operates independently of cloud infrastructure
•Ensures privacy while maintaining safety.
LIFEGRID is a fully offline, edge-AI-powered emergency intelligence layer designed for buildings.
It transforms passive infrastructure into proactive safety systems.
1. Analyze real-time video streams from 4 cameras
2. Process acoustic anomalies locally
3. Integrate environmental sensor inputs
4. Fuse multi-modal data for high-confidence alerts
5. Trigger automated emergency responses instantly
6. Generate dynamic building risk scores
7. Operate 100% offline with local network only
All processing runs on:
•Orange Pi 5 Plus
•Axlera Metis AI Accelerator
No cloud required.
1. Cross-Modal Verification Engine (Major Differentiator)
Instead of single-event triggers: Event is confirmed only when multiple signals align.
1. Smoke detected (Vision AI) AND
2. Crackling sound detected (Audio AI) AND
3. Temperature spike detected (Sensor)
THEN -> High Confidence Fire Alert
This dramatically reduces false alarms.
No conventional CCTV system does this fully offline.
2. Predictive Crowd Panic Detection
Not just crowd counting.
✓System analyzes:
✓Motion velocity changes
✓Directional compression
✓Sudden density spikes
✓Panic acceleration patterns
✓This enables early-warning before stampede conditions.
Predictive safety > reactive detection.
3. Dynamic Risk Scoring Model
Each monitored zone receives:
✓Fire Risk Index
✓Gas Risk Index
✓Occupancy Risk Score
✓Behavioral Anomaly Score
✓These scores update continuously.
This shifts the system from detection-based to intelligence-based.
4. Silent Distress Recognition
On-device audio model detects:
✓Screams
✓Explosions
✓Glass breaking
✓Aggressive shouting
✓Help signals
✓Even when cameras miss the event.
5. Fall + Inactivity Monitoring
Using posture tracking and temporal analysis:
✓Detect sudden falls
✓Detect prolonged inactivity
✓Trigger medical alert logic
✓Critical for elderly care environments.
SYSTEM ARCHITECTURE
Hardware:
•Orange Pi 5 Plus (Edge Host)
•Axlera Metis AI Accelerator
•4x ONVIF/RTSP Cameras
•Microphone Input
•Optional Gas/Temperature Sensors
•Local WiFi Mesh Router
Software Stack:
•YOLO-based object detection optimized for Axlera
•Lightweight Audio Classification Model
•Multi-Sensor Fusion Decision Engine
•Local Web Dashboard
•Emergency Alert Module
•All inference occurs locally.
LIFEGRID is designed to:
✓Operate during internet outages
✓Function during network shutdowns
✓Eliminate cloud latency
✓Ensure data privacy
✓Prevent data leaks
✓Reduce bandwidth dependency
✓Wireless connectivity is limited to local mesh only.
✓This aligns directly with edge-AI deployment requirements.
LIFEGRID can be deployed in:
•College hostels
•Industrial workshops
•Residential apartments
•Laboratories
•Smart classrooms
•Event halls
•Religious spaces
•Small factories
•Scalable from single-room to campus-wide networks.
LIFEGRID directly addresses:
Preventable fire-related casualties
•Gas exposure risks
•Stampede disasters
•Industrial blind-spot accidents
•Delayed emergency response
•Elderly unattended emergencies
By shifting from reactive alerts to predictive intelligence, LIFEGRID acts as a proactive safety guardian
