Accurate detection of building defects and communication to stakeholders with prudent use of invested resources, e.g., time, manpower, and money, increases value delivery to all stakeholders involved in the building delivery. This paper presents a prototype developed to facilitate enhanced value delivery for building defects inspection during building construction and management. With image classification and cloud database technologies, this study proposes a mobile (phone-based) machine learning application to raise awareness of building defects located in buildings and the implications to motivate building stakeholders to promptly reduce the risk level. The benefits of the developed prototype can further be enhanced when the developed prototype is integrated with drones. The adoption of the developed prototype will vary depending on the cause and context of the defined building defects detection and communication problems to be addressed.
Keywords: Building defects, Defects detection, Defects communication, Mobile cloud computing, Machine learning
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Cite as: “Kng JHJ and Fadeyi MO (2022). Development of a mobile phone-based application for detection and communication of building defects. Built Environment Applied Research Sharing #10 (Technical Note). ISSUU Digital Publishing.”