Linker Vision ← All products / Flooding

Flooding

Road Flooding Detection

Upgrade existing cameras at intersections, on buses, and across transportation and environmental agencies into a 24/7 proactive flood monitoring system. The system provides real-time detection of flooded areas, water depth, and road passability, while extending coverage to locations beyond the reach of conventional water-level monitoring stations. This enables emergency response centers to identify flood hotspots at an early stage and make timely decisions on dispatching field crews and closing affected roads—building a more responsive and comprehensive urban flood resilience system.

VLM output

A rural two-lane road is surrounded by extensive brown floodwater covering the adjacent agricultural fields on both sides. Floodwater has reached the edges of the road and partially covered the road shoulders. Several cars, a van, and an orange utility truck are stopped on the raised section of the road, while several people and cyclists are standing on the wet pavement near the water's edge.

  • Road Flooding DetectedYes
  • Flood Water On RoadwayYes
  • Flood SeveritySevere
  • Water Depth On RoadShallow
  • Road PassablePartially
  • Stopped Vehicles Count5
  • Pedestrians On RoadYes
  • Weather ConditionOvercast

Customer challenges

1

Flood monitoring relies on a limited number of water-level stations and sensors, leaving large monitoring gaps between them

2

Flooding is mostly discovered through manual patrols or citizen reports, so detection lags behind reality

3

Manually watching every city camera 24/7 isn't feasible — the staffing cost is too high

4

Recession isn't tracked systematically, making it hard to tell normal drainage from a drainage-system malfunction

5

Both the city government and residents expect faster and faster flood-response times

Customer benefits

No new hardware needed — existing cameras upgrade directly into flood sensors, extending coverage to locations gauge stations can't reach

Proactive AI flood monitoring — flooding and recession are reported in real time, so status is always known

Dispatch, road-closure, and traffic-control decisions happen earlier

Full flood-lifecycle logging, with automatic alerts when recession looks abnormal

Key features

Standing Water Detection

Detects standing water on the road surface.

Flood Depth Classification

Classifies flood depth on affected roads.

Passability Assessment

Assesses whether the road remains passable.

Before & after

Before Monitoring limited to water-level stations, with major gaps between them After — with Linker AI Nexa Full AI camera coverage reaching locations gauges can't — 121x wider monitoring coverage than water-level stations alone
Before Relies on manual patrols and citizen reports After — with Linker AI Nexa 24x7 proactive AI monitoring, cutting monitoring labor cost by roughly 90%
Before Flooding's impact on traffic discovered too late, slowing dispatch and road-closure decisions After — with Linker AI Nexa Decisions made roughly 30 minutes earlier
Before No systematic record of recession After — with Linker AI Nexa Recession time logged automatically, with alerts when drainage looks abnormal