| # E-Waste PCB Component Purity & Cannibalization Index: Project Context, System Architecture & Master Action Plan |
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| ## 1. Project Overview & Business Context |
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| The **Component Purity & Cannibalization Index** is an edge-AI system built for Kabadiwala Connect (e-waste recycling platform). It detects real-time, on-device PCB cannibalization (the illicit stripping of valuable components like CPU sockets, gold edge connector fingers, IC microchips, and SMD tantalum capacitors) to: |
| 1. Calculate a dynamic **Board Integrity Score (BIS)**. |
| 2. Emit **8-language vernacular voice warnings** to scrap collectors for fair purchasing price adjustments. |
| 3. Propagate component integrity data across the **Collector → Dealer → Recycler** supply chain to catch mid-chain cannibalization fraud. |
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| ## 2. Current Project State & Progress Summary |
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| | Category | Current Status | Details & Artifacts | |
| | :--- | :--- | :--- | |
| | **Dataset Size** | **3,923 Normalized JPEGs** | Located in `data/images/` and `data/annotated_auto/images/` (6,864 total tracked). Average resolution: $1315 \times 1029\text{ px}$. | |
| | **Auto-Annotation** | **6,377 Draft Bounding Boxes** | Auto-labeled across all 4,303 image files via YOLO-World zero-shot model (`pipeline/auto_annotate.py`, `conf=0.015`). | |
| | **Dataset Spec** | **YOLO Format Ready** | Specification saved to [`data/splits/data.yaml`](file:///home/taruns/Downloads/scraper/data/splits/data.yaml). Summary in [`data/annotated_auto/auto_annotation_summary.json`](file:///home/taruns/Downloads/scraper/data/annotated_auto/auto_annotation_summary.json). | |
| | **Updated Taxonomy** | **7 Fine-Grained Classes** | Defined in [`config/taxonomy.yaml`](file:///home/taruns/Downloads/scraper/config/taxonomy.yaml) (separates fraud desoldered pads from factory empty pads). | |
| | **Integrity Engine** | **Track B Complete & Tested** | Purity Engine (`purity_engine/`) with form-factor profiles, scrap grade pricing floors, and 8-language voice alerts. | |
| | **Pipeline Tests** | **20 / 20 Passed** | Full test suite ([`tests/test_purity_assay.py`](file:///home/taruns/Downloads/scraper/tests/test_purity_assay.py) & [`tests/test_pipeline.py`](file:///home/taruns/Downloads/scraper/tests/test_pipeline.py)) fully compliant. | |
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| ## 3. Architecture & Dual-Track Execution Strategy |
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| Development is decoupled into two parallel tracks linked by a frozen contract ([`model_contract.md`](file:///home/taruns/Downloads/scraper/implementation_plan_component_purity_index.md#L61)): |
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| ``` |
| ┌────────────────────────────────────────────────────────┐ |
| │ model_contract.md (Frozen Schema) │ |
| └──────────────────────────┬─────────────────────────────┘ |
| │ |
| ┌────────────────────────┴────────────────────────┐ |
| │ │ |
| ┌────────▼───────────────────────┐ ┌─────────────────▼─────────────────────┐ |
| │ Track A: Model & Dataset │ │ Track B: Application & Integration │ |
| ├────────────────────────────────┤ ├───────────────────────────────────────┤ |
| │ • 7-Class Refined Taxonomy │ │ • `MockModelClient` for Dev/Testing │ |
| │ • Multi-Scale YOLOv8 Training │ │ • Integrity Engine (`purity_assay.py`) │ |
| │ • Focal Loss for Desoldered │ │ • Offline Pre-Recorded Audio Warnings │ |
| │ • TFLite INT8 Quantization │ │ • Collector Lite & Recycler Portal │ |
| │ • Real-World Test Evaluation │ │ • BIS-Delta Fraud Discrepancy UI │ |
| └────────────────┬───────────────┘ └─────────────────┬─────────────────────┘ |
| │ │ |
| └─────────────────┬───────────────────────┘ |
| ▼ |
| Swap Mock for Quantized Model (`TFLiteModelClient`) |
| (1-Line Config Change) |
| ``` |
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| --- |
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| ## 4. System Requirements & Architectural Adjustments |
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| Based on technical analysis and field realities, the following system-level changes are enforced: |
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| ### A. Edge Hardware & Memory Optimization (Low-End Android 2GB–3GB RAM) |
| * **Sequential Model Execution**: Running the 21-class category model and YOLOv8 micro-model simultaneously triggers browser tab memory crashes. |
| * **Fix**: Enforce explicit tensor disposal (`model.dispose()`) after Stage 1 classification before loading Stage 2 micro-component detection. |
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| ### B. Taxonomy Refinement (Eliminating False Fraud Signals) |
| * **Fix**: Split generic desoldered footprints into: |
| 1. `forcibly_desoldered_pad`: Exposed pads with jagged solder peaks, torn traces, or blowtorch/burnt flux residue (**fraud signal**). |
| 2. `factory_unpopulated_pad`: Clean silkscreen outline with smooth solder dots left unpopulated from factory (**NOT fraud**). |
| 3. `occluded_region`: Footprints covered by heatsinks, metal shields, or thick dust. |
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| ### C. Dynamic Scrap Grade Pricing Floor |
| * **Fix**: Replace rigid 35% hardcoded floor with category scrap grade floors: |
| $$\text{Adjusted Price} = \text{Base Price} \times \left( \text{Floor}_{\text{category}} + (1 - \text{Floor}_{\text{category}}) \times \frac{\text{BIS}}{100} \right)$$ |
| * Server/GPU PCBs: $\text{Floor} = 0.15$ |
| * Desktop PCBs: $\text{Floor} = 0.30$ |
| * Low-grade Power PCBs: $\text{Floor} = 0.60$ |
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| ### D. Multi-Angle 2-Sided Inspection Protocol |
| * **Fix**: Standardize a 2-photo workflow (Front Top-Down + Reverse Bottom-Down / Edge) in Collector Lite to inspect both sides of the PCB. |
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| ### E. Supply Chain Fraud Tolerance Bands |
| * **Fix**: Update Recycler Portal intake discrepancy bands to: |
| * $< 12\%$ BIS Drop $\rightarrow$ Normal capture variance (Pass). |
| * $12\text{--}25\%$ BIS Drop $\rightarrow$ Advisory Warning / Discrepancy Flag. |
| * $> 25\%$ BIS Drop $\rightarrow$ Critical Fraud Alert & CPCB Form 6 PDF Audit Log Entry. |
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| ### F. Offline Vernacular Audio Reliability |
| * **Fix**: Standardize pre-recorded `.opus` audio playback via Service Worker `CacheStorage` as a fallback when Web Speech API regional voice packs are missing offline. |
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| --- |
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| ## 5. Master Plan of Action (Step-by-Step Roadmap) |
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| ### Phase 1: Baseline Model Training (Track A) |
| - [x] Auto-annotate dataset with 3,130 draft boxes (`pipeline/auto_annotate.py`). |
| - [ ] Fine-tune baseline **YOLOv8n / YOLOv8s** on `data/annotated_auto/data.yaml` (`imgsz=960` or `1280`). |
| - [ ] Evaluate per-class mAP@50 and fraud recall on `forcibly_desoldered_pad`. |
| - [ ] Quantize model to TFLite INT8 ($<15\text{ MB}$, target $<1\text{s}$ latency). |
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| ### Phase 2: Incremental Harvest & Synthetic Data (Optional Extension) |
| - [ ] Execute optional incremental scraper batch (~500–1,000 images) using updated [`config/queries.yaml`](file:///home/taruns/Downloads/scraper/config/queries.yaml). |
| - [ ] Apply CutMix / Copy-Paste synthetic desoldered pad data synthesis during training. |
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| ### Phase 3: Purity Engine Module Build (Track B) |
| - [ ] Build `purity_engine/model_client.py` (`MockModelClient` & `TFLiteModelClient`). |
| - [ ] Build `purity_engine/purity_assay.py` (Form-factor baseline matching + dynamic scrap pricing formula). |
| - [ ] Build `purity_engine/vernacular_voice.py` (Web Speech API + `.opus` fallback). |
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| ### Phase 4: App Integration & End-to-End Verification |
| - [ ] Extend Collector Lite (`mobile/kabadiwala-lite.html`) with 2-photo workflow & inline BIS display. |
| - [ ] Extend Recycler Portal (`recycler-dashboard-frontend/`) with BIS-delta view ($12\% / 25\%$ flags). |
| - [ ] Run automated test suite (`tests/test_purity_assay.py`, `tests/test_bis_delta_api.py`). |
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| --- |
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| ## 6. Key Configuration & Pipeline Commands Quick Reference |
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| * **Run Automated Tests**: |
| ```bash |
| .venv/bin/python -m pytest |
| ``` |
| * **Run Auto-Annotation Script**: |
| ```bash |
| .venv/bin/python pipeline/auto_annotate.py |
| ``` |
| * **Run Incremental Web Scraper**: |
| ```bash |
| .venv/bin/python scraper.py harvest |
| ``` |
| * **Dataset Location**: `data/annotated_auto/` |
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