Computer Vision and IoT for Personalised Site Monitoring Analytics in Real-Time (CV-SMART) towards Behaviour-Based Safety

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The "One Death is too Many" (Donaghy, 2009) catchphrase for the UK zero-harm agenda shows that no fatal accident is admissible on construction sites. Modern H&S problems can only be solved from a combination of cultural, social and technical perspectives. A lot of work has been done from cultural and social perspectives, but the technical perspective has been massively ignored (particularly the use of digital technologies). There is a need to take a closer look at how social and technical systems overlap, and how the growing overlap influences H&S on construction sites. However, current approaches address the socio-technical overlap of H&S management separately despite the evidence that suggests that the Zero Harm target and H&S best practices cannot be achieved without effective digitisation in addition to appropriate social interventions (NBS, 2018). The consortium will, therefore, leverage state-of-the-art in computer vision and deep learning (convolutional neural networks and recurrent neural networks) to develop a Computer Vision and IoT for Personalised Site Monitoring Analytics in Real-Time (CV-SMART) for behaviour-based safety in confined construction sites.CV-SMART will automatically detect, recognise and track diverse interacting heavy machines, building components, site activities, and site workers in real-time to (i) enforce H&S best practices and (ii) identify H&S risks and unsafe site practices such as failure to wear safety gadgets (helmets, harness, and personal protective equipment PPE), congested work areas, improper movement of heavy equipment, and improper working positions). CV-SMART will provide a digital visualisation platform, which will employ state-of-the-art in advanced visualisation for Intuitive user interaction and reporting. CV-SMART will alert on-site workers, safety managers, and site managers of H&S best practices and impending risks at the forefront of onsite operations with a minimal human intervention using IoT-enabled devices.