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Revolutionizing Road Quality Assessment with AI Mobile Platform

AS
Amarjot Singh • January 24, 2025
Road Quality Assessment

In an innovative step towards ensuring road durability and vendor accountability in Riyadh, Skylark Labs introduces its state-of-the-art vehicle-mounted camera road inspection system. This initiative is part of a strategic move to monitor road conditions post-construction, ensuring that vendors meet their guarantees of road longevity and quality. The system is a blend of high-definition camera technology and AI algorithms, offering a meticulous approach to inspecting road conditions and holding constructors accountable for their work.

"Our AI-powered road inspection system ensures that every kilometer of road meets the highest quality standards, holding vendors accountable for their contractual obligations."

— Dr. Amarjot Singh, CEO of Skylark Labs

Problem: Ensuring Road Longevity and Vendor Accountability

Riyadh’s expanding road infrastructure, while crucial for its growth, faces unique challenges:

Vendor Guarantees:

Roads constructed by vendors are under contractual obligations to last a specific duration, requiring strict quality assurance.

Diverse Conditions:

The city’s roads, stretching from urban to desert areas, face varied maintenance needs.

Heavy Traffic and Safety Concerns:

High traffic volumes and unaddressed road damages pose significant safety hazards.

Natural and Human-Induced Wear:

Roads are subject to damage from environmental factors and intense urban activities.

Solution: Skylark Labs’ Inspection System for Vendor Accountability

Advanced Surface Analysis:

Utilizing AI and high-definition cameras for detailed road condition assessment.

Real-Time Damage Detection:

Instant identification of defects, ensuring vendors adhere to quality standards.

Integrated Mapping and Documentation:

GPS-based mapping and detailed documentation facilitate pinpointing areas where vendors may have fallen short of their guarantees.

Responder Safety Enhancement

Provides live hazard detection, minimizing risks for first responders.