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fazeZEROApplication Atlas

Demo listing. This page uses illustrative seed metadata to demonstrate the Atlas. Claims shown here are not verified product facts.

AlertStride

Internet of Things & Edge

Demo

A streaming fall-detection service for retirement homes and rehab clinics that scores wearable accelerometer feeds in real time and notifies care staff when irregular activity patterns indicate a fall.

Deployment-Ready FoundationfazeZERO VerifiedProprietary

Last verified 15 Sept 2026 · Updated 23 Sept 2026 · Metadata v4

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Configuration + implementation engagement

Problem

Senior-living and rehab operators with high patient-to-nurse ratios where falls are reported late — or not at all — until injury is discovered.

Outcome

A deployment-ready foundation that teams can configure into production.

Who uses it

  • Operations Analyst
  • Solution Architect

Key capabilities

  • Core workflow

    AI-assistedIncluded

    Primary operating workflow for this foundation.

  • Document intelligence

    AI-assistedIncluded

    Extract and ground decisions from operating documents.

Typical workflow

Primary operating flow

Trigger: An operator starts the primary use case

  1. Task

    Stage 1: Capture inputs

    Operator

  2. AI-assisted

    Stage 2: Assist with draft

    System

  3. Human checkpoint

    Stage 3: Human approval

    Approver

Task Automated AI-assisted Human checkpoint Decision

About this foundation

Irregular-pattern detection as a care ops product. The source frames falls as anomalies against regular activities (walk/sit), achieves 98.75% accuracy on MobiAct accelerometer data with an ANN, and describes a streaming deployment path (model → streaming analytics) for wearable health sensors in facilities.

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