D4.6 – Personalised Alerts, Prediction, and Feedback Tools v2
Creators: name: Teizer, Jochen
name: Hong, Kepeng
name: Apostolidis, Alexandros
Publisher: name: Zenodo
Year: 2023

description: Construction accounts for up to 25% of all occupational fatalities in many countries. Many of the accidents in construction are struck by and caught in/between objects or vehicles resulting from insufficient or delayed detection of pedestrian workers. Research has proposed detecting proximity-based close call detection to proactively alarm the involved personnel and prevent negative consequences at the earliest possible time. Furthermore, data on proximity-based close calls that is recorded can be analysed for design and planning changes of construction site layouts and processes.

Based on the methods and criteria developed in D4.4, D4.6 demonstrates a prototypical tool for personalised alerts, prediction, and feedback, called ProactiveSafety. This tool has three objectives: first, a comprehensive synthesis of close call reporting processes and individual warning/alerting, data gathering, reporting, and analysis technologies. Second, a sensor system focusing on (a) autonomous close call data generation from run-time proactive proximity detection and alerting technology and (b) Digital Twin-based data processing and visualisation in building information models at run time. Lastly, initial field testing demonstrates that the developed system reaches purposes for proactive decision-making in safety engineering and management beyond the scope of existing safety decision-making processes.

Compared to the earlier version in D4.5, the enhanced version in D4.6 further developed the prototypical application based on the framework established in D4.5. The application includes two scenarios: run-time proximity-based close call detection and alerting and after-event proximity-based close call data analysis and assessment. Technology is applied for run-time data acquisition and data exchange. ProactiveSafety includes a web-based user interface (UI) that contains various functions of close call analysis, such as heatmap, trajectory analysis, and close call assessment. The UI allows Health Safety and Environment (HSE) managers to access the proximity-based close call information and provide safety-related information for use in personalised feedback to pedestrian workers, equipment operators, or other important project stakeholders.

In this deliverable, the ProactiveSafety application experimented on the data from a real-life railway construction project in Karlsruhe, Germany, where 15 minutes of timestamped location data of four tags (i.e., three pedestrian workers and one concrete truck) were recorded. On this representative data set, ProactiveSafety was able to detect two proximity-based close call events in run-time. While the purpose of the initial test case was to demonstrate the functionality of individual technology components in the DTP system (note: neither General Data Protection Regulations (GDPR) nor an observation of human behaviour or change were within the scope of D4.6), it was possible to generate new and highly valuable information that otherwise would have not been noticed. In this case, pedestrian workers stepped too close to a heavy piece of construction equipment. The details and analysis of the close call events were visualised in the UI and made available for HSE and construction site managers (note: further control or change through applying suitable measures was not within the scope of D4.6). In brief, this demonstration validates the framework and functionality of ProactiveSafety and provides a reader or potential user with noteworthy walkthrough instructions.