Mining Vehicle Collision Avoidance System Deployed at an Indonesian Industrial Mining Site

A mining vehicle collision avoidance system must do more than detect nearby people or vehicles. In harsh mining and industrial environments, the system also needs to handle dust, poor visibility, complex traffic routes, and mixed vehicle-pedestrian operations. In June 2026, WTSAFE deployed an AI vision + UWB collision avoidance solution at an industrial mining site in Indonesia for multi-scenario POC testing.

The project covered an open-pit processing area, sulfur workshop, magnesium oxide workshop, and finished-product yard. Different technologies were tested according to the operating conditions of each area, providing a practical approach to improving mining vehicle safety and pedestrian protection in complex industrial environments.

Three Challenges for Mining Vehicle Safety

Industrial mining sites often have a combination of heavy vehicles, pedestrians, production equipment, and changing traffic routes. This creates several challenges for a conventional safety system.

1. High Risk of Vehicle-Pedestrian Collisions

Heavy vehicles such as loaders and forklifts frequently operate in the same areas as workers, inspectors, and maintenance personnel.

In open processing areas, vehicles may travel on slopes or around material piles where visibility is limited. Inside workshops, narrow roads, dense equipment layouts, turning areas, and intersecting traffic routes can create additional blind spots.

For drivers, simply having a camera or rear-view mirror is often not enough. A person may enter a blind area or cross the vehicle's path faster than the driver can react.

2. Dust, Heat, Humidity and Corrosion

Mining and industrial processing environments can be significantly harsher than standard warehouses.

The Indonesian site included areas with:

• High levels of dust

• High temperature and humidity

• Corrosive conditions

• Heavy vehicle traffic

• Obstructed visibility

• Complex operating routes

These conditions place higher requirements on a mining vehicle safety system. A solution that performs well in a clean warehouse may require a different sensor configuration when used in a dusty outdoor yard.

3. Driver Management Across Different Languages

The project also involved operators from different backgrounds, creating additional challenges for safety communication and standardized operation.

Unsafe behaviors such as speeding, distraction, and inconsistent compliance with site rules can increase collision risk.

This means that technology should not only detect external hazards. Where applicable, a complete industrial vehicle collision avoidance system should also support driver warnings and operational control.

AI + UWB: Two Technologies for Different Mining Scenarios

Instead of using one technology throughout the entire site, WTSAFE tested two complementary approaches: an AI collision avoidance system and a UWB collision avoidance system.

The objective was to match the technology to the environmental and operational conditions of each area.

Application Area	Main Challenge	Technology Tested	Main Function
Processing area	Pedestrian-vehicle interaction	AI vision	Pedestrian detection and collision warning
Production workshops	Blind spots and mixed traffic	AI vision	AI detection and driver warning
Finished-product yard	Heavy dust and visibility limitations	UWB	Proximity detection and warning
Heavy-vehicle operation	Large blind zones	AI/UWB	Risk detection and active protection

This type of multi-technology architecture can be useful when different areas of the same site have very different operating conditions.

AI Collision Avoidance System for Processing Areas and Workshops

For the processing area and production workshops, where pedestrian activity was relatively high and dust levels were more manageable, WTSAFE deployed an AI-based collision avoidance system.

The system uses AI vision to detect pedestrians around industrial vehicles and assess potential collision risks.

When a person enters a defined risk area, the system can provide graded audible and visual warnings. Depending on the vehicle and integration requirements, the system can also support speed control or braking intervention.

This changes the safety process from simply seeing a hazard to actively responding to it:

AI camera → Pedestrian detection → Risk assessment → Warning → Speed control/braking

WTSAFE's AI collision avoidance technology is designed for applications including forklifts, loaders, excavators, mining vehicles, and other industrial vehicles. Its current product architecture also supports configurable detection and warning zones, with vehicle intervention available according to the integration requirements.

For this Indonesian project, the equipment also used an English-language interface to make operation easier for local and foreign drivers.

UWB Collision Avoidance System for High-Dust Areas

The finished-product yard presented a different challenge.

Heavy dust and obstructed visibility can make camera-based detection more difficult. For this area, WTSAFE tested a UWB collision avoidance system based on high-precision proximity measurement.

Unlike a vision-based system that relies on image recognition, UWB determines proximity through wireless ranging. This makes it useful as a complementary technology in environments where visibility is a major concern.

The basic safety workflow is:

UWB ranging → Distance monitoring → Risk-zone detection → Audible/visual warning → Speed control or stop

UWB-based proximity systems are already used in industrial environments where vehicles, pedestrians, and other assets need to be monitored in relation to each other.

For mining and heavy industrial applications, this distinction matters. The question is not simply whether AI or UWB is better. The more practical question is:

Which technology is more suitable for the specific operating environment?

Why Use Both AI and UWB?

AI vision and UWB have different strengths.

AI vision can identify people based on visual information and does not require every pedestrian to carry a positioning tag. It is particularly useful where pedestrian recognition, blind-spot monitoring, and visual evidence are important.

UWB provides proximity information through wireless ranging and can serve as an additional protection layer in areas where dust, lighting, or visual obstruction creates challenges.

For complex industrial sites, combining technologies can therefore provide more flexible protection than relying on a single detection method.

Technology	Key Strength	Typical Application
AI Vision	Pedestrian and object recognition	Workshops, processing areas, mixed traffic
UWB	Proximity/ranging detection	Heavy-duty yards, high-dust areas
Radar	Distance and object detection	Outdoor vehicles and blind spots
AI + UWB	Complementary protection	Complex mining and industrial sites

The choice should ultimately depend on vehicle type, pedestrian traffic, environmental conditions, required detection method, and whether active vehicle control is required.

POC Testing: From Technology Selection to Real-World Validation

The two systems are currently undergoing trial operation at the Indonesian site.

The POC focuses on comparing the suitability, stability, and protection performance of AI vision and UWB technology under high-dust, high-temperature, humid, and potentially corrosive operating conditions.

This testing approach provides more than a product demonstration. It helps the site evaluate:

• Which technology is suitable for each operating area

• How detection performs under actual site conditions

• How warning zones should be configured

• Whether vehicle speed control or braking should be integrated

• How different vehicle types should be equipped

• How the solution can be expanded across the site

The results can provide data for future site-wide safety upgrades and help establish a more standardized approach to mining vehicle collision avoidance.

What This Indonesia Case Means for Other Mining Sites

Every mining or industrial site has its own combination of vehicles, traffic patterns, environmental conditions, and safety requirements.

A forklift operating inside a workshop may face a very different risk profile from a loader working in an outdoor material yard. Similarly, a camera-based system that works effectively in one area may not be the only technology required for a high-dust environment.

For this reason, a practical mining vehicle collision avoidance system should start with a site assessment rather than simply selecting a single device.

A typical deployment process can include:

1. Map vehicle and pedestrian routes

2. Identify blind spots and high-risk interaction areas

3. Assess dust, lighting, weather, and visibility conditions

4. Select AI, UWB, radar, or a combination of technologies

5. Define warning and intervention zones

6. Conduct on-site POC testing

7. Optimize the configuration before large-scale deployment

This approach allows the safety system to be adapted to the actual operating environment instead of forcing every area into the same technical configuration.

WTSAFE Mining Vehicle Collision Avoidance Solutions

WTSAFE provides AI vision, UWB, radar, and other vehicle safety technologies for forklifts, loaders, mining vehicles, and industrial equipment.

Its AI collision avoidance solutions can detect pedestrians and vehicles, issue graded warnings, and support speed limitation or braking according to the vehicle integration configuration. WTSAFE also provides mining and heavy-vehicle solutions designed around different combinations of AI vision, UWB, radar, and other sensing technologies.

The Indonesia POC demonstrates one important principle: there is no single sensor technology that is ideal for every mining environment. Effective vehicle-pedestrian protection depends on matching the detection technology to the vehicle, work area, environmental conditions, and required level of intervention.

FAQ: Mining Vehicle Collision Avoidance Systems

What is a mining vehicle collision avoidance system?

A mining vehicle collision avoidance system detects pedestrians, vehicles, or other hazards around mobile equipment and provides warnings or active intervention to reduce collision risk. Depending on the system, technologies may include AI cameras, UWB, radar, or multiple sensors.

Can AI collision avoidance systems be used on loaders and forklifts?

Yes. AI-based collision avoidance systems can be configured for forklifts, loaders, excavators, mining vehicles, and other industrial equipment. Camera configuration and warning zones should be adapted to the vehicle and working environment.

Is UWB suitable for dusty mining environments?

UWB can be used as a proximity-detection technology in environments where visual visibility is a major challenge. Its suitability should be evaluated according to the site layout, required detection range, personnel equipment, and vehicle integration requirements.

Should a mining site use AI or UWB?

The answer depends on the application. AI vision is useful for visual pedestrian and vehicle recognition, while UWB provides proximity/ranging information. For complex sites, the two technologies can be evaluated or combined according to different operating areas.

Conclusion

A reliable mining vehicle collision avoidance system needs to address both collision risk and environmental conditions. The Indonesia project shows how AI vision and UWB can be tested and deployed according to different site requirements, rather than applying one technology uniformly across the entire operation.

For mining plants, processing facilities, material yards, and other industrial sites facing vehicle-pedestrian interaction risks, a combination of AI collision avoidance, UWB proximity detection, and active vehicle control can provide a flexible foundation for upgrading site safety.

Tag：mining vehicle collision avoidance system AI collision avoidance system UWB collision avoidance system mining vehicle safety system loader collision avoidance system Prev：Forklift anti collision warning system Next：Already the last piece