Purpose
This podcast introduces the concrete, real‑world use cases that can be modeled using the Open SGI Minimum Viable Model (MVM) for edge‑primary Personal Event Recognition (PER) in the context of aging in place.
The intent of this podcast is not to define products or deployments. Instead, it demonstrates how the eight OAII subclasses defined by the MVM are sufficient to model a meaningful and defensible set of use cases while preserving privacy, governance, and auditability.
Each use case is framed to show:
- what the system can recognize
- what it can not and does not claim
- how interpretation progresses across Worlds
- how policy mediation constrains outcomes
Design Constraints on Use Cases
All modeled use cases conform to the following constraints:
- Edge‑primary processing only
- No diagnostic or medical claims
- No behavioral scoring or profiling
- All evaluations are policy‑mediated and logged
- Non‑action is the default outcome
The system recognizes events, not intentions or health states.
Core MVM Capabilities
With the eight MVM subclasses, the system can:
- recognize object‑level events from sensor data
- contextualize events relative to a known Primary User
- evaluate outcomes using configurable beneficial–detrimental policies
- log decisions and deliver notifications when permitted
This enables a family of low‑risk, high‑value assistive scenarios.
Modeled Use Case 1: Primary User Arrival
Description
The system recognizes when the Primary User enters the home.
World Interpretations
- Subject–Object World: Something passed through the entry boundary
- PrimaryUser–Environment World: The Primary User entered the home
- Beneficial–Detrimental World: Entry is consistent with normal context
Policy Outcome
- Log confirmation of normal arrival
- No notification required
Why This Matters
This establishes baseline presence without tracking or surveillance.
Modeled Use Case 2: Unexpected Entry
Description
An entry occurs that does not match the Primary User profile.
World Interpretations
- Subject–Object World: Object detected entering
- PrimaryUser–Environment World: Entry does not match Primary User
- Beneficial–Detrimental World: Entry flagged as uncertain
Policy Outcome
- Log event with elevated attention level
- Optional local notification, depending on policy
Boundaries
No identity assertion is made. No threat classification occurs.
Modeled Use Case 3: Routine Movement Pattern
Description
The system observes movement consistent with established routines.
World Interpretations
- Subject–Object World: Motion detected in defined zones
- PrimaryUser–Environment World: Movement aligns with Primary User routine
- Beneficial–Detrimental World: No deviation detected
Policy Outcome
- Silent log update
- Reinforcement of baseline knowledge
Why This Matters
Supports reassurance without constant alerts.
Modeled Use Case 4: Prolonged Inactivity
Description
No movement is detected during an expected active interval.
World Interpretations
- Subject–Object World: Absence of motion over time
- PrimaryUser–Environment World: Primary User inactivity detected
- Beneficial–Detrimental World: Event flagged for review
Policy Outcome
- Log contextual concern
- Optional low‑priority notification
Critical Constraint
This is not a diagnosis or fall detection claim.
Modeled Use Case 5: Device or Sensor Degradation
Description
A sensor becomes unavailable or unreliable.
World Interpretations
- Subject–Object World: Sensor signal anomaly
- PrimaryUser–Environment World: Environmental perception degraded
- Beneficial–Detrimental World: System integrity concern
Policy Outcome
- Log maintenance condition
- Notify maintenance or caregiver if permitted
Why This Matters
Maintains trust in system interpretations.
Modeled Use Case 6: Routine Reintegration After Change
Description
A learned routine is updated following sustained, consistent change.
World Interpretations
- Subject–Object World: Stable change in detected patterns
- PrimaryUser–Environment World: New routine inferred
- Beneficial–Detrimental World: Change deemed acceptable
Policy Outcome
- Reintegration of updated knowledge
- Logged update with revision history
Safety Feature
Reintegration is gradual and reversible.
Modeled Use Case 7: Quiet Confirmation for Caregivers
Description
A caregiver receives confirmation that no intervention is required.
World Interpretations
- Subject–Object World: Events processed normally
- PrimaryUser–Environment World: Primary User accounted for
- Beneficial–Detrimental World: No concern detected
Policy Outcome
- Periodic confirmation notification
- Full audit trail retained locally
Value
Reduces anxiety without increasing surveillance.
What the MVM Explicitly Does Not Model
The Open SGI MVM does not attempt to model:
- medical diagnosis or health assessment
- emotional or psychological state
- intent or motivation
- compliance or behavioral scoring
- continuous remote monitoring
These exclusions are intentional and essential.
Why These Use Cases Are Sufficient
Together, these use cases demonstrate that:
- meaningful assistance does not require opaque AI
- personalization can be policy‑governed
- edge‑primary systems can remain accountable
- open models can support real human needs
They provide enough coverage to justify the technical feasibility and social value of the OAII / Open SGI approach without overreach.
Next in This Series
The following podcasts will specify how each use case is supported by a concrete OAII subclass, starting with the EdgePERDevice and proceeding through Sensors, Signals, Events, Policies, Agents, Interfaces, and Logs.
Each specification will show exactly how these use cases are made possible — and constrained — by design.
Open Autonomous Intelligence Initiative 
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