EdgeSentry-Inspect — Roadmap

Foundation (trilink-core repo)

The following are prerequisites for all EdgeSentry-Inspect milestones. They are tracked and implemented in the trilink-core repository.

Do not start M2 until #30, #31, #32, and #34 are merged.

M2 — IFC Loader and Deviation Engine

Goal: Given a scanned point cloud and an IFC design file, compute a per-point deviation in millimetres.

Deliverables:

• Cargo.toml — workspace root; member: crates/edgesentry-inspect
• src/ifc.rs — load IFC geometry as Vec<Point3D> (design reference cloud)
• src/deviation.rs — k-d tree nearest-neighbour deviation; configurable threshold
• src/report.rs — JSON report serialisation (schema in architecture.md)
• Integration test: load sample IFC fixture → compute deviation against known scan cloud → assert compliant_pct, max_deviation_mm, mean_deviation_mm

M3 — Heatmap Rendering

Goal: Produce a PNG heatmap that maps per-point deviation to colour, positioned in 2D using the depth map projection.

Deliverables:

• src/heatmap.rs — deviation → RGB colour (green ≤ threshold, yellow 2×, red 4×+) → PNG via image crate
• Reuses trilink-core::project_to_depth_map to position each coloured point in 2D
• Integration test: known deviation values → verify expected pixel colours at expected positions in output PNG

M4 — Field PC Pipeline (CLI)

Goal: End-to-end pipeline on the field PC from point cloud to deviation report, runnable as a single CLI command.

Deliverables:

• src/main.rs — CLI: edgesentry-inspect scan --config config.toml
• Wires: point cloud ingress (trilink-core::FrameSource) → project_to_depth_map → AI inference client → unproject → deviation → heatmap → report
• Config: IFC file path, inference.mode (builtin | http), inference endpoint URL (if http), deviation threshold, output directory
• End-to-end test with MockSource + mock inference server: report produced, all fields correct, heatmap PNG written

M5 — Cloud Sync

Goal: Upload the deviation report and heatmap to the immutable audit store; emit structural-change flags.

Deliverables:

• src/sync.rs — S3-compatible upload (Object Lock WORM); structural-change flag → SQS or MQTT when anomaly exceeds 2× threshold
• Integration test: mock S3 + mock SQS → assert report uploaded, flag published for above-threshold anomaly, no flag for below-threshold

M6 — Built-in Inference Model

Goal: Ship a lightweight ONNX defect-detection model with EdgeSentry-Inspect so that inference.mode = "builtin" works out of the box without an external server.

Deliverables:

• src/inference/mod.rs — InferenceBackend trait; dispatches to built-in or HTTP based on inference.mode
• src/inference/builtin.rs — ONNX Runtime runner (ort crate); loads bundled model weights
• src/inference/http.rs — HTTP client extracted from M4 into the same module for parity
• models/detect.onnx — initial model covering surface_void, misalignment, rebar_exposure
• Integration test: run built-in model on a sample depth map → assert detections are non-empty and class labels are valid

Dependency graph

trilink-core #30, #31, #32, #34  (foundation — must be done first)
    └── M2 (IFC loader + deviation engine)
         └── M3 (heatmap rendering)
              └── M4 (field PC pipeline CLI)
                   ├── M5 (cloud sync)
                   └── M6 (built-in inference model)