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Newsletter N°90 - June 2026
🏗️ Construction: AI Slump Tracker: Real-Time Concrete Quality Monitoring with Artificial Intelligence
Concrete slump is one of the most critical indicators of concrete workability and directly impacts the quality and durability of construction projects. However, traditional slump management on construction sites relies on periodic sampling tests and visual inspections by engineers, making it difficult to monitor the entire volume of concrete continuously.
To address this challenge, Obayashi Corporation and M-Soft developed the AI Slump Tracker, an AI-powered monitoring system designed to provide real-time concrete quality control.
The solution uses a smartphone camera to record concrete being discharged from a mixer truck. Artificial intelligence then analyzes the video feed and automatically estimates the slump value in real time throughout the entire unloading process.
Unlike conventional spot-check inspections, the system performs continuous monitoring of all delivered concrete, providing a complete overview of quality conditions during placement. The AI automatically detects the concrete flow and measures slump values without requiring manual intervention. One of the key features of the technology is its ability to generate instant alerts whenever measured values fall outside the target range.
This allows site teams to react quickly and prevent issues such as poor filling performance, cold joints, or other defects that may affect structural quality. The collected data is uploaded to the cloud every second, enabling remote monitoring from site offices or headquarters. Project managers and quality control teams can track concrete performance in real time and review historical data for further analysis.
The implementation of AI Slump Tracker provides several benefits:
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Improved quality assurance through full-volume concrete monitoring.
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Enhanced durability and reliability of concrete structures.
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Reduced risk of rework and project delays caused by concrete defects.
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Lower labor requirements by automating visual inspections and manual measurements.
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Better traceability and digitalization of construction quality management.
AI Slump Tracker reflects a growing trend in the construction industry toward AI-powered quality control. Similar research and industry developments are demonstrating how computer vision and machine learning can analyze concrete flow and predict slump values automatically from video footage, enabling more efficient and data-driven construction practices.
By combining artificial intelligence, computer vision, cloud technology, and mobile devices, AI Slump Tracker helps construction companies improve concrete quality management while reducing manual workload, supporting the ongoing digital transformation of the construction sector.
When ready-mixed concrete flowing down the chute is photographed, the slump value is measured in real time.