Fall, Hazardous-Action and Workstation-Behavior Analytics

Scope and project-specific requirements

Critical decision conditions

Sample falls, crouching and maintenance poses separately; output review candidates, not medical or intent judgments.

Candidate technical approach

These are candidate implementation paths. Establish a baseline on real samples, then select or combine methods for imaging, speed and deployment constraints. Model names do not imply measured project results.

Inputs for assessment

Provide camera layouts, authorized video, target sizes, day/night samples, region/event definitions, concurrent streams, alert-review workflows and retention periods.

Deliverables and interface agreement

Action model, event definitions, alerts and replay tools

Specify input formats, output fields, coordinates/units, error states, versions and invocation methods. Define review and failure handling. The statement of work determines the exact scope of source code, executables, model files or analysis reports.

Acceptance method and measures

Evaluate events rather than only frames: misses, false alerts per hour, duration error, alert latency and recovery after occlusion. Include empty scenes and hard negatives.

These are measures to agree and test, not achieved-performance claims. Freeze samples, reference truth, thresholds and hardware/software versions before acceptance; report subgroup results and failures, identifying under-sampled conditions as uncovered.

Implementation and procurement stages

1. Define scope

   Agree targets, stations, inputs and responsibilities in a statement of work, separating required and excluded conditions.

2. Sample validation

   Use representative samples to test critical risks, document feasibility/failures and scope the next-stage estimate.

3. Development and integration

   Implement agreed functions and interfaces with configuration/change records; use offline replay before authorized device or site integration.

4. Acceptance and handover

   Retest against individual measures and hand over contracted artifacts with known limits; manage maintenance, expansion and changeovers as subsequent work packages.

Scope limits and licensing

Use data minimization, anonymization and access controls as needed. Do not infer sensitive traits, emotions or medical status from appearance; review alerts and retain existing safety measures.

Candidate technologies are not license clearance. Check code, model weights, training data and dependency versions separately. Replace, license or exclude components unsuitable for the intended commercial delivery. Customer data is not used for public training by default.

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