AIECS
by Allocate Space
This case study shows how Allocate Space combines AI-assisted inspection with secure data capture and traceable workflows to support regulatory compliance in road maintenance operations.
Road inspections are a critical requirement for civil engineering contractors maintaining public infrastructure. Inspectors must identify defects such as potholes, cracks, damaged guardrails, and faded road markings, while ensuring findings are properly documented and reported to meet regulatory requirements.
Traditionally, inspections rely heavily on manual observation and post-inspection reporting, making it difficult to guarantee consistency, completeness, and traceability across large road networks.
Full Traceability and Audit Readiness
Improved Inspection Coverage
Better Compliance Confidence
Challenge
Manual road inspections present several challenges:
High risk of missed defects during inspections.
Time-consuming manual classification and reporting.
Limited visibility into inspection coverage and historical changes.
Difficulty linking detected defects to follow-up works.
Increasing regulatory expectations around auditability and data integrity.
For contractors operating under authority oversight, incomplete records or inconsistent documentation can lead to compliance risks and operational inefficiencies.
The client needed a solution that could support inspectors during on-road inspections, improve defect detection accuracy without removing human oversight, capture inspection data securely with full traceability, maintain a clear audit trail from inspection to rectification, integrate inspection findings with execution workflows, and ensure compliance with authority reporting requirements.
Solution
Allocate Space implemented AIECS, an AI-assisted inspection system integrated into the existing Inspection, Execution and Claim System (IECS) platform.
AIECS introduces AI as a co-pilot to inspectors, detecting potential defects from video footage captured during inspections. Detected defects are synchronised with the IECS system, where inspectors can review, validate, and follow up on findings.
AI-Assisted Detection with Human Verification
AI models analyse road inspection video footage to identify common defect classes such as potholes, cracks, faded markings, and damaged roadside structures. Inspectors remain in control, with the ability to verify, correct, or add defects captured during inspections.
This approach improves coverage while maintaining accountability.
Secure Data Capture and Traceability
Every inspection record includes timestamped images or video frames, GPS location, inspector identity, and defect classification. All data is securely stored and synchronised when connectivity is available, ensuring no data is lost during offline inspections.
Closed-Loop Inspection to Execution
Detected defects automatically generate records within IECS, enabling teams to assign rectification works, track progress, and maintain a complete historical record. This creates a closed-loop workflow from inspection to execution and reporting.
Impact
Improved Inspection Coverage
AI assistance reduces the likelihood of missed defects and supports inspectors in identifying issues consistently across large road networks.
Full Traceability and Audit Readiness
Each defect is traceable from detection to resolution, with complete metadata including location, time, and inspection history. This strengthens compliance with authority requirements and simplifies audits.
Higher Productivity
Inspectors spend less time on manual reporting and rework. Reports are generated faster, without the need for additional personnel.
Better Compliance Confidence
With secure data capture and structured workflows, clients gain confidence that inspections and follow-up works are conducted in accordance with regulatory standards.
