SOLAR TODO deployed a Smart Traffic System across 11 intersections in Karachi, Pakistan (24.86, 67.01), using 6m L-arm hot-dip galvanized steel poles and our 4-in-1 smart traffic hardware. The goal was to improve traffic detection reliability in dense, high-variability road conditions—where manual observation and conventional sensors struggle to maintain consistent accuracy.
Answer Capsule: We installed 11 intersections of 4-in-1 smart traffic poles in Karachi, combining 4K AI (98% accuracy, <50ms) with 77GHz radar and TrafficGPT for real-time, edge-to-cloud traffic intelligence.
Project Background: Karachi’s Real-World Traffic Complexity
Karachi’s road network faces a mix of congestion patterns, lane changes, and unpredictable vehicle behavior—often compounded by uneven camera visibility, varying lighting, and frequent congestion spillback at key junctions. For city operators, the practical challenge is not just “detect vehicles,” but to generate consistent, machine-readable traffic intelligence that can support signal optimization, incident response, and long-term performance analysis.
In this deployment, SOLAR TODO focused on end-to-end traffic sensing and decision support: edge perception (4K AI camera + 77GHz mmWave radar) → Edge AI (NVIDIA Jetson) → communications (5G/fiber) → City Brain (TrafficGPT) → applications. This architecture supports both automated detection (counts, speeds, plates) and natural-language queries via the central TrafficGPT platform—helping traffic teams move from raw data to actionable insights.
Solution Overview: SOLAR TODO Smart Traffic System for 11 Intersections
We configured 11 intersections with 6m L-arm steel poles (dark grey, hot-dip galvanized) to match Karachi’s urban roadside constraints and sightline requirements. Each intersection uses our 4-in-1 Smart Traffic Pole integration, combining:
- 4K AI camera (98% accuracy, <50ms response) for vehicle counting, speed detection, and plate recognition (45+ detection types)
- 77GHz mmWave radar for complementary detection robustness under challenging visual conditions
- LED fill light to stabilize perception in variable illumination
- LED signal light to provide consistent traffic signaling visibility aligned with the sensing zone
The system’s Edge AI runs on NVIDIA Jetson, enabling on-site processing for fast response and reducing latency when traffic conditions change rapidly. For analytics and operations, we connected sites through 5G/fiber backhaul to the TrafficGPT central platform, where operators can query traffic conditions using natural language.
Additionally, the city adopted a BOT (zero upfront) cooperation model, allowing phased rollout and operational continuity without requiring large upfront capital commitments—useful in procurement cycles where multiple departments coordinate infrastructure upgrades.
How the 4-in-1 Pole Works (Edge-to-City Brain Pipeline)
SOLAR TODO’s system is built on a 5-layer architecture:
- Perception: 4K AI camera + 77GHz radar capture vehicles and relevant features at each junction.
- Edge AI: NVIDIA Jetson performs real-time inference for vehicle counting, speed detection, and plate recognition using 45+ detection types.
- Communication: 5G/fiber backhaul links edge devices to the central platform, maintaining data continuity for both monitoring and analytics.
- City Brain (TrafficGPT): The central platform interprets traffic patterns and supports natural language queries (e.g., time windows, approaches, congestion trends, detection confidence summaries).
- Applications: Data feeds operational dashboards and city traffic workflows.
This layered design matters operationally in Karachi: when lighting changes, lane geometry is irregular, or traffic flow is unstable, the radar + AI fusion improves detection stability, while the <50ms response time supports timely updates to traffic intelligence.
Deployment in Karachi: Configuration Details That Fit the Site
For this project, SOLAR TODO standardized a practical and maintainable roadside configuration:
- 11 intersections × 6m L-arm steel pole (dark grey, hot-dip galvanized)
- Each pole integrated the 4-in-1 smart traffic hardware:
- 4K AI camera (98% accuracy, <50ms response)
- 77GHz mmWave radar
- LED fill light
- LED signal light
- Edge AI: NVIDIA Jetson at the pole level for local inference
- Plate recognition capability: supports 45+ detection types and enables license plate recognition alongside counting and speed
- Backhaul: 5G/fiber to the TrafficGPT central platform for city-scale coordination
- Cooperation model: BOT (zero upfront)
- Compliance targets: NTCIP and GB 25280
Local infrastructure considerations were part of the engineering approach. Karachi’s junctions often require careful alignment to ensure reliable coverage of vehicle approaches and turning movements. By using a consistent 6m L-arm geometry and integrating both camera and radar, the deployment achieved stable detection even when visual conditions varied throughout the day.
Technical Specifications
- Deployment scale: 11 intersections
- Pole: 6m L-arm steel pole, dark grey, hot-dip galvanized
- 4-in-1 Smart Traffic Pole components:
- 4K AI camera: 98% accuracy, <50ms response, 45+ detection types
- 77GHz mmWave radar
- LED fill light
- LED signal light
- Edge AI: NVIDIA Jetson
- Detection features: vehicle counting, speed detection, plate recognition (45+ detection types)
- Backhaul: 5G/fiber to TrafficGPT central platform for natural language queries
- Cooperation model: BOT (zero upfront)
- Standards: NTCIP, GB 25280
Standards & Interoperability Considerations
Traffic systems depend on interoperability, consistent signaling behavior, and reliable communications. This project aligned with internationally recognized traffic and communications practices and local compliance expectations:
- NTCIP for traffic management communications interoperability.
- GB 25280 for traffic signal control system requirements.
- For broader communications and system reliability practices, SOLAR TODO also references international guidance commonly used in smart infrastructure deployments, including:
- ITU recommendations for communications frameworks
- IEEE principles for reliable networked sensing and system engineering
These references support a deployment that can integrate with city operations while maintaining predictable device behavior and data exchange.
Results and Impact
Across the 11 Karachi intersections, SOLAR TODO’s Smart Traffic System delivered measurable operational improvements by upgrading the sensing layer and connecting it to city-level intelligence.
Quantified outcomes
- Faster detection updates: the 4K AI camera’s <50ms response supports near-real-time traffic intelligence under rapidly changing conditions.
- High detection reliability: the camera achieves 98% accuracy, improving confidence in vehicle counting and speed detection workflows.
- Richer analytics for enforcement and operations: built-in plate recognition with 45+ detection types enables more detailed traffic event analysis.
- Robust perception: the combination of 4K AI camera + 77GHz mmWave radar improves detection continuity when visual conditions degrade.
Operational benefits for Karachi traffic teams
- Edge-to-cloud visibility: Edge AI on NVIDIA Jetson processes data locally for speed, while 5G/fiber backhaul ensures consistent delivery to TrafficGPT.
- Natural-language traffic queries: operators can use TrafficGPT to ask for traffic conditions and summaries, reducing time spent translating raw sensor outputs into actionable reports.
- Scalable rollout model: the BOT (zero upfront) cooperation model supported phased deployment planning aligned with city procurement and operational readiness.
Pricing & Quotation
SOLAR TODO offers three pricing tiers for this product line: FOB Supply (equipment ex-works China), CIF Delivered (including ocean freight and insurance), and EPC Turnkey (fully installed, commissioned, with 1-year warranty). Volume discounts are available for large-scale deployments. Configure your system online for an instant estimate, or request a custom quotation from our engineering team at cinn@solartodo.com.
Frequently Asked Questions
Q1: How does the Smart Traffic System handle poor lighting or glare in Karachi?
The system uses a 4K AI camera with an integrated LED fill light for stable perception, and it also includes a 77GHz mmWave radar to maintain detection robustness when visual inputs degrade.
Q2: What traffic data can the system generate at each intersection?
At each pole, the system supports vehicle counting, speed detection, and plate recognition with 45+ detection types, processed by NVIDIA Jetson at the edge.
Q3: How is data sent from the intersections to the city platform?
SOLAR TODO configured 5G/fiber backhaul from the edge devices to the TrafficGPT central platform, enabling natural language queries and city-scale traffic analytics.
Q4: Which standards does the deployment follow?
This Karachi deployment targeted compliance with NTCIP and GB 25280 for traffic communications and control system requirements.
Related Reading
References
- ITU (International Telecommunication Union) recommendations on communications frameworks and network performance guidance.
- IEEE standards and best practices for reliable networked sensing and systems engineering.
- NTCIP (National Transportation Communications for ITS Protocol) for traffic management interoperability.
- GB 25280 (PRC) for traffic signal control system requirements.
- World Bank resources on smart city and transport systems implementation considerations.
For product configuration and deployment planning, visit our Smart Traffic product page: smart traffic and for project discussions: contact us.
Equipment Deployed
- 11 × 6m L-arm steel poles (dark grey, hot-dip galvanized) with integrated 4-in-1 smart traffic hardware
- 4-in-1 Smart Traffic Pole sensors per intersection: 4K AI camera (98% accuracy, <50ms response, 45+ detection types) + 77GHz mmWave radar + LED fill light + LED signal light
- Edge AI compute per intersection: NVIDIA Jetson
- Backhaul connectivity: 5G/fiber to TrafficGPT central platform for natural language queries
- Traffic intelligence platform integration: City Brain (TrafficGPT) with application layer data services
- Compliance targets: NTCIP and GB 25280 interoperability alignment
- Cooperation model: BOT (zero upfront) deployment framework