As a risk predictive tool PRESTO is the ﬁrst of its kind
Based on years of incident investigations and the combined experience of the project partners, we believe that there are a number of patterns that explain why incidents happen; in other terms some attributes and conditions if happening at the same time lead to a high likelihood of a negative event happening. They include:
• Conditions of the worker while performing the task that can be tracked through wearables (e.g. Heart Rate Variability – HRV – which can measure the level of stress)
• Weather conditions or events surrounding the worker
• State of mind of the worker (trackable to the social media)
• Pressure from supervisors and managers
• Poor safety culture in the organisation
• Poor health and safety management system
• Financial situation of the company
• Elements of distraction (eg phone calls)
• Level of team interaction
PRESTO analyses a large amount of information including all the input data, statistical information from large safety incidents databases, unstructured information through free text analysis, current information collected through wearables and sensors, in order to understand patterns that explain why incidents happen.
They will be translated in algorithms which using machine learning techniques, when key elements attributes are simultaneously happening (eg when a male worker of a certain age, with a limited period in the position is performing a specific task, while it is raining, at the end of his shift, during the night), will release a risk profile rating. Depending on its level it will trigger actions like:
• STOPPING THE ACTIVITY since the risk of a negative event happening is not tolerable
• CARRYING ON THE ACTIVITY BUT UNDER SOME PRECAUTIONS and will communicate the best course of action to the worker
• CARRYING ON THE ACTIVITY REGULARLY since the conditions are not presenting excessive level of risk
An application will manage the communication with the interested worker, e.g. sending microlearning videos or simplified procedures to confirm the right practices to perform the task in safe conditions.
The tool will be customized to the organisation’s needs.