Sector
Consumer Goods
Industry
Consumer Electronics
Business model
B2C
B2B
Technology
Security & Surveillance Technology
Internet of Things (IoT)
AI / ML
Location
Palakkad, Kerala
Founded
2019
Team
C
CYRIAC PIUS
Co-founder
S
SHALU THOMAS
Co-founder
A
ANEESH KUMAR V R
Other Core Team member
Product 1
OZCARE
Privacy-first IR/thermal fall detection for dementia and elder-care rooms. Wall-mounted sensor with edge AI detects falls, night-time bed exits, and prolonged inactivity, sending instant caregiver alerts via mobile/dashboard with escalation. Designed for high accuracy, low false alarms, and dignity-preserving monitoring without RGB cameras.
Sector
Consumer Goods
Industry
Consumer Electronics
Model
B2C
B2B
Technology
Security & Surveillance Technology
Internet of Things (IoT)
AI / ML
1) What it is
A privacy-first, room-level safety monitoring system for dementia and elder-care. It uses a wall-mounted IR/thermal sensor with edge AI to detect critical events and immediately alert caregivers—without using RGB cameras.
2) What it detects (core functions)- Fall detection: sudden collapse/posture change events
- Bed-exit detection: especially valuable during night hours
- Prolonged inactivity / no-movement: possible fall or medical distress
- Presence & basic activity patterns: to support caregiver context (optional analytics)
- Sensor continuously monitors the room using thermal/IR data (non-identifying).
- On-device AI classifies events (fall / bed-exit / inactivity).
- When thresholds are met, the system pushes an instant alert to caregivers.
- If not acknowledged, it triggers escalation (next caregiver / supervisor / nursing station).
- Events are logged as metadata (time, room, event type, confidence), with privacy controls.
- Hardware: wall-mounted IR/thermal sensing unit, facility-ready power/network options (Wi-Fi/PoE as applicable), device health monitoring
- Software: edge inference engine, alerting service, caregiver mobile notifications, and a web dashboard for room-wise status and event logs
- Mobile alerts (configurable severity and escalation)
- Nursing-station dashboard showing: room status, active alerts, acknowledgement, device uptime, event summaries
- Configurable rules per room/resident (e.g., night-only bed exit alerts; inactivity duration thresholds)
- No RGB video and no identifiable imagery
- Edge processing by default to minimize sensitive data movement
- Role-based access to dashboards and audit logs
- Configurable retention of only necessary event metadata for operations and quality improvement
- Fast detection-to-alert latency (near real-time)
- High sensitivity for falls and high-risk events
- Low false alarms through threshold tuning and workflow confirmation logic (critical for caregiver trust)
- Pilot-first: 3–5 rooms, validate accuracy/false alarms, tune thresholds, document impact
- Scale-out: room-by-room rollout with centralized monitoring
- Support: installation guidance, caregiver onboarding, periodic calibration/tuning, remote diagnostics
- Restlessness / sleep disturbance insights (night-time patterns)
- Pre-fall risk indicators (gait instability proxies where feasible)
- Integration with nurse-call / facility SOP workflows and reporting dashboards
If you paste the exact fields shown under “Product Details” (some forms ask for tech stack, pricing model, deployment requirements), I’ll tailor this into the exact format and length the portal expects.
Sector
Consumer Goods
Industry
Consumer Electronics
Model
B2C
B2B
Technology
Security & Surveillance Technology
Internet of Things (IoT)
AI / ML