Norco Driving
Norco Driving approached us with a simple requirement: to enable live video streaming from their vehicles back to base over the internet.
Norco Driving approached us with a simple requirement: to enable live video streaming from their vehicles back to base over the internet.
Initially, this was for internal monitoring purposes, but the long-term vision included creating a public-facing live stream showcasing their operations.
The solution needed to handle multiple cameras installed in each vehicle, operate across mobile networks using multiple SIM cards, and maintain stream continuity even when vehicles encountered 4G blackspots.
This was a technically demanding brief, requiring a robust, low-latency architecture that could adapt to variable network conditions without compromising reliability.
Project details
- Client: Norco Driving
- Website URL: Visit website
- Services: Cloud Infrastructure / Software Development / Hardware Integration
- Year:
The challenge
Streaming live video from moving vehicles presents several inherent challenges:
- Network Instability: Mobile networks are prone to fluctuations, and vehicles frequently pass through areas with poor or no coverage. A conventional streaming setup would drop the feed entirely during these blackspots.
- Multi-Camera Complexity: Each vehicle required multiple camera feeds (e.g., forward-facing, cabin view), all of which needed to be transmitted simultaneously without overwhelming available bandwidth.
- Latency Requirements: For monitoring to be effective, the solution had to deliver near real-time video, not buffered or delayed streams.
- Scalability and Cost: The system had to be cost-effective and scalable across a fleet, avoiding expensive proprietary hardware.
- Future-Proofing: The architecture needed to support future plans for public streaming without requiring a complete redesign.
These constraints meant that a simple RTMP or HLS-based approach would not suffice. We needed a solution that could dynamically adapt to changing conditions and maintain session continuity under adverse network scenarios.
The solution
Our team designed and implemented a resilient streaming architecture built around WebRTC, chosen for its low-latency capabilities and robust congestion control mechanisms. Key elements of the solution included:
- WebRTC Transport Layer: Each camera feed was encapsulated in a WebRTC session, providing sub-second latency and adaptive bitrate control. This ensured the stream had smooth playback even when bandwidth fluctuated.
- Video Compression and Adaptive Bitrate: We utilized H.264/H.265 encoding with dynamic bitrate adjustments based on real-time network conditions.
- Multi-SIM Uplink Strategy: Vehicles were equipped with Teltonika routers supporting multiple SIM cards. Our implementation leveraged multiple network paths, enabling rapid failover when one connection degraded.
- VPS-Based Orchestration: A central VPS server handled session negotiation, media routing, and outbound stream creation. This allowed us to buffer short windows during connectivity drops, preventing stream termination and displaying a “signal degraded” overlay instead of killing the outbound stream.
- Future Streaming Capability: Alongside the real-time WebRTC feed for internal monitoring, the server was configured to generate HLS/DASH outputs for future public streaming initiatives.
- Observability and Control: We built a browser-based dashboard for operators, featuring live metrics (bitrate, jitter, packet loss) and remote controls for adjusting stream parameters on the fly.
This architecture ensured that even when vehicles hit 4G blackspots, the live stream remained logically continuous, and base operators retained situational awareness.
The results
The implementation delivered some great operational benefits:
- Continuous Monitoring: Streams no longer dropped during blackspots. Operators saw either a temporary quality reduction or a clear “signal degraded” indicator, rather than losing the feed entirely.
- Low Latency: Under normal conditions, glass-to-glass latency averaged between 400–800 ms.
- Scalability: The VPS orchestration layer allowed easy onboarding of additional vehicles and cameras without major infrastructure changes, if the situation was required.
- Operational Efficiency: The dashboard provided actionable insights into network health and stream performance, reducing troubleshooting time and improving fleet oversight.
By combining adaptive technologies with a resilient architecture, we transformed a complex technical challenge into a practical, scalable solution that meets Norco Driving’s current needs and future ambitions.
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