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Ozak Technologies Private Limited

KSUM recognised
Palakkad, Kerala
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)
3) How it works (workflow)
  1. Sensor continuously monitors the room using thermal/IR data (non-identifying).
  2. On-device AI classifies events (fall / bed-exit / inactivity).
  3. When thresholds are met, the system pushes an instant alert to caregivers.
  4. If not acknowledged, it triggers escalation (next caregiver / supervisor / nursing station).
  5. Events are logged as metadata (time, room, event type, confidence), with privacy controls.
4) System components
  • 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
5) Alerts and caregiver experience
  • 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)
6) Privacy, dignity, and data governance
  • 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
7) Performance targets (pilot-ready)
  • 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)
8) Deployment model
  • 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
9) Roadmap (optional extensions)
  • 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

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Sector Consumer Goods Industry Consumer Electronics Model B2C B2B Technology Security & Surveillance Technology Internet of Things (IoT) AI / ML
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