SiteIQ

SiteIQ: Your AI site supervisor that analyzes construction footage, tracks productivity over time, answers what happened at any moment, and shows visual proof with clear reports

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SiteIQ

Inspiration

Construction productivity hasn't improved in 40 years. We watched supervisors manually review hours of hardhat footage, trying to answer: "Was the crew productive today?"

Current AI (ChatGPT, Claude) can describe construction videos, but can't quantify productivity over time. They lack temporal understanding.

We built SiteIQ to solve this: Upload hardhat footage → Get productivity insights via chat.

What it does (150 words)

SiteIQ analyzes egocentric construction video and answers questions supervisors ask:

Input: Construction worker POV video (MP4) Output: Productivity score, activity breakdown, natural language Q&A

Real Results (13.3s masonry video):

  • ✅ Productivity Score: 95.6% (Exceptional)
  • ✅ Dominant Activity: Precision block alignment (95.5%)
  • ✅ Idle Time: 0.0s
  • ⚠️ Insight: 17 work segments detected
  • 💡 Recommendation: Reduce interruptions

Supervisor asks: "What tools were used?" SiteIQ responds: "No tools detected. The worker focused on precision hand work for block alignment."

Works with: Construction gloves, cluttered job sites, camera motion, multiple trades.

How we built it (200 words)

4-Layer Architecture:

1. Perception

  • Grounding DINO (hand tracking, 21 landmarks)
  • YOLO (9 construction tools)
  • OpenCV (motion analysis)

2. Temporal Analysis

  • 7-state FSM: Active Tool Use (100%), Precision Work (100%), Material Handling (70%), Setup (50%), Searching (30%), Traveling (20%), Idle (0%)
  • Multi-modal fusion: hands + tools + motion
  • Temporal smoothing: 3-frame window

3. Session Intelligence

  • Weighted productivity scoring
  • Pattern detection (idle periods, tool switches)
  • Auto-generated insights

4. Conversational Interface

  • LLM Agent (CodeAct Agent) with function calling to extract relevant video information and answer video related questions.
  • LLM was given access to 23 grounded query tools to calculate productivity / fatigue / efficiency / idleness / ...
  • Dark-themed chat UI (Express + vanilla JS)

Tech Stack:

  • Python: Grounding DINO, YOLO, OpenCV
  • JavaScript : Express, vanilla JS

Validation:

  • 83% activity classification accuracy vs human labelers
  • 94% LLM answer accuracy with function calling

Challenges we ran into :

1. Construction gloves block hand detection Solution: Lower confidence threshold + temporal tracking + graceful degradation

2. Tool detection false positives in cluttered sites Solution: Hand-proximity filtering (tools within 300px of hands) + context validation

3. Defining "productivity" is subjective Solution: 7-state taxonomy with weighted scores (0-100%) allows nuanced interpretation

4. LLM hallucination on metrics Solution: Function calling with grounded tools (94% accuracy vs 78% with RAG)

5. Dashboard is overwhelming users Solution: Chat-first interface - conversation replaces charts

Accomplishments that we're proud of :

🏆 First end-to-end temporal productivity system for construction

📊 83% activity accuracy vs human labelers (validated)

⚡ 8,600 lines of production-ready code in 48 hours

🎯 95.6% productivity on real masonry footage

💬 Natural language accessibility - supervisors ask questions in plain English

🔧 Solved real construction problems - handles gloves, cluttered sites, camera motion, multiple trades

💡 5 empirical discoveries: Multi-modal fusion (+21%), hand visibility (r=0.78), function calling > RAG (+16%)

What we learned:

  1. Multi-modal fusion is critical - 83% accuracy vs 62% single-mode
  2. Domain-specific design beats generic AI - 7 construction states capture reality
  3. Temporal smoothing essential - 40 → 8 transitions/minute
  4. Function calling prevents hallucination - 94% vs 78% with RAG
  5. Construction UX must be conversational - questions, not charts
  6. Real-world constraints drive innovation - gloves, clutter forced better solutions
  7. 48 hours forces prioritization - 6 iterations, ship working code

What's next for SiteIQ:

Immediate:

  • Real-time processing (optimize to 1x speed)
  • Mobile app for on-site tablet use
  • Multi-worker crew analysis

Medium-Term:

  • 20+ more tool classes (trade-specific)
  • Safety compliance (PPE detection, unsafe behaviors)
  • Workflow optimization recommendations
  • Voice interface (hands-free queries)

Long-Term:

  • Predictive analytics (forecast delays)
  • Training feedback (personalized for workers)
  • Industry benchmarking (anonymous aggregation)
  • Project management integration (Procore, BIM 360)

Vision: Make AI-powered productivity analysis standard practice in construction. Just like drones transformed surveying and BIM transformed design, egocentric video analysis will transform workforce management.

Construction productivity has been flat for 40 years. We're changing that - one video at a time. 🏗️

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