How Technology Is Transforming TSF Risk Management: From Sensors to AI

How Technology Is Transforming TSF Risk Management: From Sensors to AI

Tailings Storage Facilities (TSFs) have traditionally relied on manual inspections, periodic surveys, and basic instrumentation to monitor performance. But with rising safety expectations, climate pressures, and the increasing complexity of mining operations, this approach is no longer enough.

Today, technology is reshaping how engineers design, monitor, and manage TSFs, making risk management faster, smarter, and more proactive. From drones to digital twins, this article explores how modern tools are transforming TSF safety in Africa and beyond.

1. Smart Sensors & Real-Time Instrumentation

Instrumentation has moved from basic measurement tools to intelligent devices capable of delivering live performance data.

Examples include:

• Wireless piezometers – tracking pore pressure continuously

• Inclinometers – detecting lateral movement

• Settlement sensors – monitoring vertical changes

• Digital flow meters – measuring seepage in real time

• Vibrating wire instruments – capturing stress and load variations

These tools allow engineers to react not days later, but immediately, strengthening the early-warning system for stability issues.

2. Satellite Monitoring & InSAR Technology

Satellite-based InSAR is becoming essential for large TSFs or remote sites.It provides:

• Millimetre-level detection of surface deformation

• Regional-scale coverage

• Independent verification of ground movement trends

InSAR helps identify subtle shifts that may not be visible during routine inspections, giving engineers critical lead time to act.

3. Drones & Aerial Intelligence

Drones now play a major role in TSF inspections, delivering high-resolution geospatial data with speed and accuracy.

They support:

• Thermal imaging

• LiDAR scans

• Photogrammetry

• Rapid identification of erosion, seepage, or unusual patterns

Aerial intelligence allows teams to monitor large areas in minutes, a task that once required days of manual fieldwork.

4. AI, Predictive Analytics & Machine Learning

TSFs generate massive amounts of geotechnical and hydrogeological data.AI and machine learning tools are now used to:

• Predict rising pore pressures

• Identify abnormal patterns in instrument data

• Forecast slope behaviour under different scenarios

• Rank risks based on probability and severity

This shift moves operations from reactive to predictive, helping mines stay ahead of potential failures.

5. Digital Twins for TSF Management

One of the most powerful emerging tools is the digital twin, a virtual model that mirrors the real-world performance of the TSF.

Digital twins integrate:

• Real-time sensor data

• Predictive models

• Material behaviour

• Climate inputs

• Water balance information

This allows engineers to simulate how the facility will respond under different loads, storms, or deposition strategies, long before any risk materializes.

6. Automation & Remote Monitoring

Modern TSF systems allow engineers and operators to:

• Access dashboards remotely

• Receive automated alerts

• Track trends using cloud-based platforms

• Improve decision-making with centralized data

This reduces human error, enhances compliance, and keeps teams informed regardless of location.

Conclusion: Technology Is Becoming Central to TSF Safety

The next generation of TSF management will be defined by:

• Better data,

• Faster decision-making,

• More accurate predictions, and

• Stronger, more transparent reporting.

Mining companies across West Africa are increasingly adopting these tools not just for compliance, but because they deliver safer, more cost-effective, and more responsible operations.

At African Engineering Services (AES), we integrate modern technology into every stage of TSF design and monitoring, ensuring our clients benefit from resilient, intelligent, and future-ready solutions.