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Newsletter N°83 - December 2025
🏗️ Construction: Kajima’s AI-Powered Bridge Inspection and Lifecycle Management System
BMStar AI is a web-based AI system developed by Kajima in collaboration with Aomori Prefecture to support damage assessment and condition evaluation of bridges using simple photos taken on-site with a smartphone or tablet. The service is offered as a cloud platform connected to the existing BMStar bridge management system, with limited free trials available for local authorities that wish to test the tool before full deployment.ng-term repair strategies.
Open the “BMStar AI” application on your smartphone or tablet, then take a photo of the damaged area
What BMStar AI Is?
BMStarAI is the AI extension of the BMStar lifecycle management system for bridges, designed to cover the full range of maintenance tasks: inspection, structural health evaluation, degradation forecasting, mid-term budget simulation, and planning of life-extension works. The AI model is trained on years of inspection data collected by experienced inspectors, enabling it to reproduce expert-level diagnoses and reduce variability in assessments between technicians.
How It Works in the Field?
During a periodic inspection, the technician opens BMStar AI on a smartphone or tablet, photographs the damaged areas of the bridge, and the system instantly analyzes the image and displays the diagnostic results.
On concrete bridges, the AI detects cracks, delamination, exposed reinforcement, water leakage traces, and lime efflorescence. It also classifies the severity of each defect to support the overall condition evaluation of the structure.
The damage assessment results are then displayed instantly
Damage Types and Technical Scope:
The core technology is based on still-image analysis: the AI segments damaged areas on superstructure elements (main girders, crossbeams, deck) and substructure elements (piers, abutments, foundations) to measure the affected surface. The targeted categories include at minimum delamination, exposed reinforcement, and water leakage areas associated with calcium deposits—critical indicators for predicting corrosion and long-term deterioration.
Integration Into Bridge Management:
BMStar_AI connects seamlessly to the BMStar system, which centralizes inspection histories, diagnostic results, degradation forecasts, and lifecycle cost calculations for each bridge. The AI-generated results therefore directly support work prioritization decisions, multi-year budget planning, and the preparation of long-term repair strategies.