Computer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste Concrete

Computer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste Concrete

In the context of an urgent global shift toward green materials and sustainable development, recycling concrete from demolished structures has become a significant trend. Instead of being discarded, this old concrete is processed and reused as aggregate for new concrete, contributing to waste reduction and minimizing environmental impact. However, to ensure the quality and accuracy of the recycling process, it is essential to thoroughly understand the characteristics and properties of these “new aggregates” when used in fresh concrete mixtures. In this context, the application of computer vision technology emerges as an innovative approach—allowing for precise analysis and evaluation of material features, thereby enhancing the efficiency and reliability of recycled concrete processing.

Computer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste Concrete

What is Computer Vision?

Computer vision is a technology that allows machines to automatically recognize and describe images accurately and efficiently. Today, computer systems have access to a vast amount of image and video data derived from or generated by smartphones, traffic cameras, security systems, and other devices. Applications of computer vision use artificial intelligence and machine learning (AI/ML) to process this data precisely for object identification and facial recognition, as well as for classification, recommendation, monitoring, and detection tasks [1].

Main Tasks of Computer Vision:

Image Recognition:
This is one of the most common applications of artificial intelligence in the field of computer vision. This technology enables systems to identify and distinguish a specific object, person, or action in an image or video. For example, it can identify animals in the wild, distinguish types of fruits in a supermarket, or detect situations in security surveillance systems.

Computer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste Concrete

Object Detection:
This task extends image recognition by not only identifying one object but also recognizing multiple objects in a single image and more importantly, determining their exact locations using bounding boxes. This technology is widely applied, especially in self-driving car systems, which must continuously recognize all vehicles, pedestrians, traffic signs, or other objects to make precise decisions ensuring safety.

Computer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste Concrete

Image Segmentation:
This technology goes further in image analysis by dividing the image into different regions or segments based on features such as color, shape, or texture. This helps reduce complexity, clarifies parts of the image, and facilitates easier processing and analysis. In medicine, image segmentation plays a crucial role in identifying pathological areas in diagnostic images, such as segmenting tissues, organs, or cancers in CT or MRI scans.

Computer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste Concrete

Facial Recognition:
This technology enables the system to identify or verify a person’s identity based on facial features in images or videos. It is widely applied in access control systems, security monitoring, and personalized services such as phone unlocking or automatic attendance systems in schools or businesses.

Computer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste Concrete

Motion Analysis:
This is a technology for tracking the trajectory and behavior of moving objects in video. It enables the detection, analysis, and prediction of the motion of objects accurately. Motion analysis is crucial in fields such as security, surveillance, and sports, helping with tactical analysis, detecting abnormal behaviors, or tracking athletes during competitions.

Computer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste Concrete

Machine Vision:
This involves integrating artificial intelligence with robotics, allowing robots or automated systems to process image data to perform tasks such as product quality inspection, sorting goods, or guiding precise movements on production lines. In industry, this system improves efficiency, minimizes errors, and optimizes automation processes.


The Role of Computer Vision in Determining Mortar Ratio

Image Segmentation plays an important role in determining the mortar ratio of aggregate in construction and material science contexts. Specifically, its functions include:

  • Distinguishing components in the image: Separating parts of the image such as mortar, aggregates (stones or grains), and other components based on color, brightness, or morphological features.

  • Determining the area of each component: After segmentation, it calculates the area of distinct regions corresponding to mortar and aggregates to obtain accurate data on the proportion of each component in the sample.

  • Optimizing analysis accuracy: Helps eliminate noise or unwanted parts to ensure that the measurements of mortar and aggregate ratios are accurate and reliable.

  • Supporting mortar ratio calculation: Based on the segmented area or volume data, the mortar-to-aggregate or total sample ratio can be calculated in percentage or proportion form.

Computer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste ConcreteComputer Vision in Construction – Enhancing the Processing of Recycled Aggregates from Waste Concrete


Bibliography

[1] Amazon, “Thị giác máy tính là gì” [Online]. Available: https://aws.amazon.com/vi/what-is/computer-vision/

[2] 200LAB, “Computer Vision là gì? Những ứng dụng của Thị giác máy tính,” [Online]. Available: https://200lab.io/blog/computer-vision-la-gi


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