Unlocking the Potential of Recycled Fibre Reinforcements in Construction: Automating Quality Assessment through Machine Learning (ML)

英国承诺在2050年前结束对气候变化的贡献，最近还宣布进入气候紧急状态。对碳排放负有相当大一部分责任的建筑业，需要采用更多的回收材料。向循环经济的转变至关重要，建筑业必须采取大胆行动，实现碳减排目标。使用低碳解决方案，如从报废轮胎中回收的回收纤维，对于实现碳中性建筑至关重要。然而，评估这些纤维的质量是具有挑战性的，因为它们的几何形状不同，这阻碍了它们的市场接受度。为了解决这个问题，该项目的目标是使用机器学习技术自动进行质量评估。通过提高效率和提供质量证据，这一合作旨在促进在钢筋混凝土应用中采用再生纤维，减少可持续建筑中的废物和二氧化碳排放。

The UK has pledged to end its contribution to climate change by 2050 and recently declared a climate emergency. The construction industry, which is responsible for a significant portion of carbon emissions, needs to adopt more recycled materials. The shift towards a circular economy is crucial, and the construction sector must take bold action to meet carbon reduction targets. The use of low carbon solutions like recycled fibres recovered from End-of-Life tyres is essential for achieving carbon-neutral construction. However, assessing the quality of these fibres is challenging due to their varying geometries and this impedes their market acceptance. To address this, the project aims to automate the quality assessment using machine learning techniques. By improving efficiency and providing evidence of quality, this collaboration seeks to promote the adoption of recycled fibres in reinforced concrete applications, reducing waste and CO2 emissions in sustainable construction.