For every single construction fatality, there are approximately 3,000 ‘near misses’ on-site, according to a recent publication of Heinrich’s Safety Pyramid. Despite this, industry estimates report that for every major incident, 10 near misses go unreported, highlighting clear inefficiencies and apprehension towards close call reporting. Emerging AI-driven safety solutions such as BuildPrompt, have contributed towards a significant reduction in reported safety incidents, with some construction firms reporting a 20% decrease according to a Deloitte study.
To illustrate this, we’ll be diving into three real-world examples of near misses to highlight how AI safety management solutions can help to prevent future incidents by streamlining your close call data processes.
Example 1: Falling Object
Scenario: A worker narrowly avoided being struck by a falling object from a scaffolding on a public infrastructure project. The object was not properly secured and the incident was reported as a close call.
BuildPrompt’s AI Solution – Secure Safety Workflows for Falling Objects: Following a potential major incident, it is critical that construction firms are able to effectively identify and diagnose system problems through their ‘lessons learnt’ programs, streamlining vast collections of data points. Our AI-powered safety workflows can help analyse previous historical incident data to identify high-risk areas and activities prone to falling object incidents, formulating clear patterns to facilitate decision-making processes for site managers and workers. By continuously refining its predictive capabilities with data from various sensors and reports, BuildPrompt continuously adapts to new safety challenges as they emerge.
Example 2: Crane Operation
Scenario: On a high-rise construction project, a tower crane narrowly avoided colliding with an adjacent building during a lift. Strong wind gusts and operator miscalculation contributed to the near miss, highlighting the potential for catastrophic accidents in crane operations.
BuildPrompt’s AI Solution – Predictive Analytics for Crane Operations: BuildPrompt’s AI-powered predictive analytics can enhance crane operation safety by analysing real-time weather data, crane load metrics, and operational patterns. This technology can predict potential hazards like strong wind gusts and provide actionable insights to crane operators, reducing the likelihood of human error. Workers and supervisors can receive automated, real-time alerts to detect operating system failure, allowing them to promptly alert colleagues and potentially save lives. By incorporating these predictive tools and automated safeguarding measures, construction companies can fortify their safety management system to help prevent similar future incidents.
Example 3: Electrical Hazard
Scenario: On a large infrastructure project, a worker nearly came into contact with a live electrical wire that was not properly insulated or marked.
BuildPrompt’s AI Solution – Automated Hazard Detection and Reporting: Integrating automated safety workflows into hazard detection systems can automatically identify and report unmarked electrical hazards. Using advanced object detection and classification algorithms, BuildPrompt’s system can detect potential electrical risks instantly and alert workers. Connected system sensors allow for a seamless flow of device data for continuous monitoring and real-time hazard detection. This ensures a safer working environment by proactively addressing electrical hazards before they can cause harm.
Conclusion
Integrating AI into close call reporting and hazard detection systems can significantly reduce the likelihood of incidents in construction and infrastructure projects. By leveraging real-time monitoring, predictive analytics, and automated alerts, AI solutions can enhance safety protocols and ensure a proactive approach to risk management. These technologies not only improve immediate safety outcomes but also contribute to a culture of continuous improvement and safety management.