In Sydney’s NorthWest private hospital faced persistent water-related challenges in its multi-story car park, affecting both vehicle and pedestrian safety and causing defects in infrastructure. During heavy rain, water pooling on ramps and walking surfaces created slip hazards, while excessive runoff into the drainage system led to overflows, downstream blockages, and infrastructure strain.

To enhance safety and flood prevention, the hospital deployed Xvision FLOODGUARD™, an AI-powered water monitoring system using CCTV cameras, real-time analytics, and predictive modeling. The objective was twofold:

1. Improve safety within the car park by detecting water pooling, surface rippling, and drainage failures before they created hazards.
2. Predict water volume entering the drainage system to help prevent downstream flooding and stormwater infrastructure failures.

The Challenge: Water Pooling & Drainage System Overload

1. Water Pooling & Slip Hazards

• During rain events, water would accumulate on sloped ramps, pedestrian crossings, and vehicle entry/exit points.
• The pooling water led to slippery surfaces, increasing the risk of falls for patients, visitors, and staff.
• Drivers were unable to see standing water on ramps, causing sudden braking and minor collisions.

2. Drainage System Overload & Downstream Flooding

• The hospital’s stormwater system fed into the local council’s drainage network, which often became overwhelmed during heavy rain.
• Excess water from the car park would enter the system too quickly, exacerbating flooding issues downstream.
• The local stormwater drains were already prone to blockage from debris, meaning any additional runoff increased the risk of backflow into nearby roads and hospital access routes.

3. Infrastructure Monitoring & Leak Detection

• In addition to external water hazards, the hospital faced recurring leaks from internal plumbing and drainage pipes within the car park.
• Underground drainage systems and pipework were difficult to inspect manually, making early leak detection nearly impossible.
• Slow leaks weakened structural components, increasing maintenance costs and the risk of long-term water damage.

The Solution: AI-Powered Water Monitoring with Xvision FLOODGUARD™

To tackle these challenges, the hospital deployed Xvision FLOODGUARD™, a multi-camera, AI-powered monitoring solution designed to:

✅ Detect water pooling and surface hazards using AI-driven CCTV cameras and analytics.
✅ Analyze rippling effects and depth calculations to determine hazard levels for vehicles and pedestrians.
✅ Monitor water flow into the drainage system to predict potential downstream overflows.
✅ Identify leaks from pipework and underground drainage components before they worsened.

1. Water Detection Using AI-Powered CCTV Cameras

The hospital installed a network of CCTV cameras across the multi-story car park, each serving a different role:

• High-angle cameras were positioned over ramps, pedestrian walkways, and entry points to detect water pooling.
• AI analytics scanned for surface rippling, water reflection changes, and accumulation patterns to measure depth and quantity.
• Motion tracking determined if water was flowing abnormally across surfaces, helping to detect slow drainage issues.

2. Predicting Water Volume in the Drainage System

• The system measured the rate at which water disappeared into drains vs. how much remained on the surface.
• AI analyzed whether the drains were handling the volume correctly or if they were nearing capacity, signaling a potential overflow risk.
• Data was shared with council stormwater teams to help predict potential drainage failures downstream.

3. Leak Detection & Infrastructure Monitoring

• Additional CCTV cameras were installed inside the car park, aimed at key drainage components and pipework.
• AI analyzed water flow from pipes and connections, automatically flagging irregular dripping, small leaks, or bursts.
• The system compared water input from rain events to outflow measurements, detecting hidden water retention areas where leaks might occur.

Challenges Encountered During Implementation

1. Camera Placement & Line of Sight Issues

• The multi-level structure of the car park created blind spots, requiring multiple repositioning of cameras to optimize coverage.
• Some water pooling areas only appeared during specific weather conditions, requiring adaptive AI training to recognize dynamic water movement patterns.

2. Differentiating Between Safe & Hazardous Water Levels

• The AI had to be trained to distinguish between:
  • Minor surface wetness (safe to walk/drive on)
  • Shallow pooling (potential hazard for pedestrians)
  • Deep standing water (critical risk for vehicles and slip accidents)
• Lighting conditions also affected how the AI recognized rippling and reflections, requiring adjustments for day vs. night detection.

3. Integration with Stormwater Data

• The system required collaboration with local council drainage teams to synchronize runoff data with real-time monitoring.
• AI models had to account for external factors like heavy rainfall upstream that could contribute to drainage failure even if the car park’s water volume remained stable.

Results & Benefits of the Xvision FLOODGUARD™ Deployment

1. Increased Pedestrian & Vehicle Safety

✔ Water pooling incidents were detected 80% faster, allowing for quicker response times from maintenance teams.
✔ Digital signage was installed at key entry points, alerting drivers when water levels were unsafe on ramps.
✔ Slip and fall incidents were reduced, as staff could preemptively dry or redirect water-prone areas before hazards developed.

2. Drainage System Insights & Flood Prevention

✔ AI successfully predicted drainage overload risks, allowing the hospital to adjust water flow rates and stagger runoff into the stormwater network.
✔ By identifying slow drainage areas, the system helped prevent excessive water from overwhelming local council drains.

3. Long-Term Infrastructure Protection

✔ AI-powered leak detection reduced maintenance costs, as small leaks were fixed before causing major damage.
✔ Structural integrity assessments became more proactive, with CCTV monitoring detecting weak points in drainage infrastructure before failures occurred.

Conclusion

The Xvision FLOODGUARD™ deployment in the private hospital’s car park successfully tackled both safety and drainage management challenges. By combining AI-powered water detection, rippling analysis, and infrastructure monitoring, the system:

✅ Reduced slip hazards and vehicle safety risks.
✅ Helped predict downstream drainage overloads and stormwater system failures.
✅ Identified leaks and prevented long-term infrastructure damage.

This case study highlights how AI-driven water monitoring solutions are transforming flood prevention and urban infrastructure management. By detecting risks before they escalate, hospitals, commercial buildings, and city councils can take a proactive approach to water safety and drainage efficiency.

Want to learn how Xvision FLOODGUARD™ can improve water safety and stormwater management in your facility? Contact us today!