9MANUFACTURING TECHNOLOGY INSIGHTSMAY 2024In monitoring road conditions, artificial intelligence (AI) leverages image and sensor technologies data, allowing for more efficient and accurate targeted repair actions than the human eye can achieveARTIFICIAL INTELLIGENCE ENABLES TIMELY ACTIONSIn monitoring road conditions, artificial intelligence (AI) leverages image and sensor technologies data, allowing for more efficient and accurate targeted repair actions than the human eye can achieve. For road maintenance, AI analyses images sent by weather and traffic cameras, providing real-time information to supervisors and reducing the need for physical inspections.The amount of collected data is immense. To derive concrete benefits from it, efficient analysis and identification of essential components are crucial. This is where AI comes into play. Machine vision can independently recognise areas requiring attention and indicate which observations need human assessment. As a result, the need for manual inspections decreases, minimising unnecessary travel-related carbon emissions and equipment wear. ROBOTS: INTEGRAL TO FUTURE INFRASTRUCTURE PROJECTSIn the future, AI that utilises high-quality data will play an increasingly significant role in the entire infrastructure lifecycle. As development progresses, AI will become more adept at solving various tasks independently. Robotics will likely also find their place in many infrastructure projects.Data extracted from the infrastructure lifecycle, refined using AI, enables intelligent and autonomous machines and devices--robots--to be utilised throughout different phases of infrastructure lifecycles. This facilitates more efficient resource management and reduces human errors and delays. Robotics holds great potential for enhancing construction site operations and streamlining tasks such as data collection and reporting.Data also drives emissions calculations in model-based construction. The focus lies on production data, utilised through a digital platform for modelling project plans and transitioning to model-based execution and monitoring. When a project understands the progression of work stages, it becomes possible to improve processes and approaches.In model-based production, we can practically track accomplished performance based on production data obtained from the construction site, machinery, and measuring devices. This serves as the foundation for emissions calculations.Recognising the current situation enables progress. In automated emissions calculations based on production data, the principle is to understand the existing state and its potential for development before creating low-emission operational models. To achieve carbon neutrality goals, companies need to be aware of the emissions caused by their current operations, followed by realistic efforts to reduce them. Monitoring production data provides insights into fuel consumption, work stage progress, and the quality of work.One ongoing development area is collecting even more detailed data directly from equipment manufacturers. In a broader context, collaborative efforts involve multiple stakeholders. The objective is to create comprehensive, low-impact contracting methods and new procurement models.The true utilisation of data materialises when we digitise production processes from start to finish on a platform that forms a situational overview for projects, enabling responsiveness to changes. This streamlines and enhances production processes.
< Page 8 | Page 10 >