InfraSense.AI

See the road as a continuously changing system.

A dynamic interface that translates raw video and telemetry into geospatial maintenance logic.

Platform Overview

Prototype visualization
Network Segments
SEG-A4-01
Critical
Risk Score92/100
SEG-A4-02
Moderate
Risk Score45/100
SEG-B1-05
Low
Risk Score12/100
SEG-B1-06
Low
Risk Score18/100
SEG-C9-12
High
Risk Score78/100
LAT: 8.7139, LNG: 77.7567
LIVE TELEMETRY
Event Feed
12:41:31Priority updated: CRITICAL. Maintenance alert dispatched.
12:41:18Location locked to SEG-A4-01. Geospatial reconciliation complete.
12:41:12Event confirmed via multi-frame consensus. Severity: High.
12:41:08Potential surface anomaly detected (confidence 87%).
Segment Intelligence
SEG-A4-01
Main Arterial Route
Condition Score
92/100 (Risk)
Detected Defects
Potholes (Deep)4
Alligator Cracking12m²
Edge DeformationNone
Observation Metadata
Passes (7d):
14
Last seen:
2h ago
Confidence:
96.4%

Detection

Continuous edge inference identifies road conditions, discarding unhelpful frames and registering potential defects.

Location & Aggregation

Multiple passes and sensors confirm defects, tying them definitively to precise GPS coordinates and road segments.

Risk Assessment

The system evaluates the density and severity of anomalies on a segment to determine the localized risk profile.

Prioritization

Budgets are finite. The final output is a ranked list of segments where capital allocation will have the greatest impact.