检测到并清除了危险字符!
Home> News> Scaling Proactive Safety: Streamax Transforms Mining Fleet Risk Management at the World’s Highest Copper Mine

Scaling Proactive Safety: Streamax Transforms Mining Fleet Risk Management at the World’s Highest Copper Mine

2026 01-21

High-Altitude Operations: The Ultimate Test for Mining Safety

Managing heavy-duty fleets in high-altitude open-pit mines presents extreme challenges: Oxygen deficiency affecting driver fatigue, sub-zero temperatures impacting hardware reliability, and vast blind spots on ultra-class haul trucks.

To address these, Streamax has deployed a systemic Mining AI Safety Management Solution. This implementation achieves a closed-loop management cycle—integrating risk identification, real-time alerting, and intelligent dispatching—across over 2,000 vehicles.

As of 2026, this system has achieved over two years of continuous, stable operation at the world’s highest altitude copper mining site. This long-term deployment serves as a definitive validation of Streamax hardware’s structural integrity and algorithm adaptability in the one of the most extreme tectonic and climatic conditions on Earth.

Technical Architecture & Core Specifications

The Streamax Mining Solution is built on a "Sensor-to-Cloud" architecture, utilizing Edge AI to process complex environmental data in real-time.

Feature Category

Technical Specification

Benefit

Edge Computing

High-performance NPU with Multi-channel AI processing

Real-time analysis of 10+ risk behaviors

Sensing Technology

Radar-Vision Fusion (Millimeter-wave + HD CMOS)

Zero-blind-spot coverage for ultra-large mining trucks

Connectivity

CAN-Bus Integration & V2X Support

Real-time SOC monitoring & Manned-Unmanned mixed traffic safety

Environmental Durability

Operating Temp: -40℃ to +70℃; High-altitude (5,000m+) optimization

Reliable performance in extreme tectonic/climatic conditions

Algorithms

DMS, ADAS, BSD, and Bucket Tooth Detection

>80% reduction in fatigue-related risk behaviors

Problem-Solution Mapping: Overcoming Complex Mining Challenges

1. Combating Driver Fatigue & Blind Spot Risks

Challenge: Long shifts in monotonous high-altitude environments lead to severe fatigue, while the sheer size of mining trucks creates lethal blind spots.

Solution: Streamax AI-driven Driver Monitoring System (DMS) and Blind Spot Detection (BSD) utilize deep learning to identify microsleep, distraction, and personnel proximity.

  • Result: Fatigue-related incidents dropped by over 80% since deployment.

2. Manned & Autonomous Mixed Traffic Safety

Challenge: Safety risks during the transition phase where autonomous haulers and manually driven vehicles coexist.

Solution: By implementing V2X (Vehicle-to-Everything) communication, Streamax system ensures sub-50ms latency in vehicle-to-vehicle coordination, providing a safety buffer for mixed-flow operations.

3. Preventing Brake Failure via CAN-Bus Monitoring

Challenge: Overcharging of batteries (SOC anomalies) in electric/hybrid trucks during downhill hauls can lead to braking system failure.

Solution: Streamax system integrates directly with the vehicle's CAN-Bus, providing real-time telemetry on State of Charge (SOC) and other critical mechanical health indicators to mitigate severe safety risks.

Global Compliance & Strategic Expansion

Smart Mining solution is not just a localized success but a global benchmark for "Belt and Road" initiatives. It has been successfully replicated in Tier 1 mining projects across:

  • Europe & Asia: Serbia, Tajikistan.

  • South America: Suriname.

The hardware stack is designed to align with international mining safety standards, supporting our AI for Industrial Safety vision in addressing the rigorous operational requirements of global markets. This commitment to reliability is underscored by our existing certifications, including ISO 26262 for functional safety, which validates our systematic approach to hardware and software integrity.

FAQ: Operational Insights for Smart Mining Safety

Q: How does the system perform in extreme low-light or dusty mining conditions?

A: We use Infrared (IR) Sensing for DMS to ensure 24/7 visibility regardless of cabin lighting. For external sensing, our Radar-Vision Fusion technology uses millimeter-wave radar to "see" through heavy dust and fog where standard cameras might fail.

Q: Can the system be integrated with existing fleet management software?

A: Yes. Our system supports standard protocols and provides open APIs for seamless integration with third-party dispatch and ERP systems used in the mining industry.


Fleet of heavy-duty mining trucks equipped with Streamax AI safety systems operating at a high-altitude open-pit copper mine.


All performance data and statistics are based on internal testing under controlled conditions and are for informational purposes only. They do not constitute a legal guarantee or warranty. Actual results may vary depending on environment, configuration, and operation.

Compliance with international standards is based on specific configurations and use cases. Customers are responsible for ensuring their specific implementation meets all applicable local regulations.


Streamax is committed to the responsible and ethical deployment of technology. Our solutions are developed with a privacy-by-design and security-first architecture. All data processing occurs locally on the edge device, ensuring that personally identifiable information, including biometric data, is neither stored nor transmitted to the cloud, thereby adhering to global data sovereignty regulations.

The AI features and performance metrics referenced in our materials are based on data from extensive internal testing and validation under controlled, laboratory-style scenarios. These results are provided to demonstrate our technological capabilities and direction; however, actual performance may vary in real-world operating environments and should be validated by the end-user.

Our AI models are trained on diverse, legally sourced datasets and are designed to function strictly as decision-support tools for human operators, not as autonomous systems. We actively mitigate algorithmic bias and our development process aligns with emerging global standards for AI ethics and functional safety.