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BAYWATCH: Piattaforma prototipale per il monitoraggio in tempo reale, la sicurezza e la gestione delle interferenze nelle banchine logistiche

Project
The overall objective of the BAYWATCH project is to develop and validate an integrated prototype platform for the safe and proactive management of logistics loading bays, capable of monitoring vehicles and operators in real time, analyzing operational interactions, and supporting dynamic decision-making aimed at reducing occupational safety risks while improving operational efficiency.

To achieve this objective, the project includes the development of a simulation environment for loading bay operations, designed to dynamically represent logistics flows, operational activities, and the operating conditions within the loading bay area. The simulation model uses truck arrival and departure flows, the availability and characteristics of vehicles and operators, the loading bay layout configuration, and operational and safety rules as input variables, enabling a realistic and continuously updated representation of loading bay processes.

Within the simulation environment, algorithms for operational interaction analysis and the computation of dynamic risk indicators are integrated to quantify the level of interaction between vehicles and operators based on their positions, trajectories, and operational characteristics. These algorithms provide the quantitative basis for generating spatial and temporal risk maps.

Building upon the dynamic risk indicators, the simulation environment incorporates an optimization algorithm that iteratively modifies the allocation of activities and resources by exploring alternative operational configurations with the objective of minimizing the level of operational interaction while complying with operational and safety constraints.

The BAYWATCH platform is further based on a real-time localization system for vehicles and operators. The project will evaluate the adoption of UHF RFID, Ultra-Wideband (UWB), radar technologies, and Global Navigation Satellite Systems (GNSS) for outdoor localization within the loading bay area. The localization system provides continuous, reliable, and up-to-date information on the position of resources within the loading bay, forming the information backbone for the real-time assessment of operational interactions.

Localization data are exploited both in the short term, to compare the actual operational situation with the risk maps generated by the simulation environment and to provide real-time alerts or operational guidance to operators, and in the medium to long term, to continuously update the simulation environment with real operational data, thereby supporting scenario updates and model recalibration.

The overall integration of the platform modules is ensured by a central software architecture acting as the system orchestrator, combining the outputs of the simulation and optimization modules with real-time localization data. BAYWATCH enables a continuous cycle of monitoring, assessment, and intervention, supporting both immediate operational decisions and medium- to long-term organizational analyses. As such, it represents an advanced decision support system for improving safety management and operational organization in logistics loading bays.

The added value of the project lies in its integrated, risk-based approach to safety management in logistics loading bays, which goes beyond conventional solutions based solely on event detection or reactive alert generation. Rather than simply monitoring the positions of vehicles and operators, the project introduces a structured and dynamic risk assessment framework based on the analysis of operational interactions and their spatial and temporal representation. The resulting risk maps, generated by the simulation environment, explicitly visualize the level of risk exposure across different areas of the loading bay, providing a concise yet highly informative representation of operational criticalities.
  • Overview
  • Skills

Overview

Contributor (3)

MEZZOGORI DAVIDE   Scientific Manager  
BERTOLINI MASSIMO   Participant  
CASTELLANO DAVIDE   Participant  

Leading department

"Enzo Ferrari" Department of Engineering   Principale  

Term type

BANDI INAIL

Financier

INAIL
Funding Organization

Partner (2)

Univ. Studi Genova
Università degli Studi di MODENA e REGGIO EMILIA

Total Contribution (assigned) University (EUR)

66,000€

Date/time interval

June 15, 2026 - June 14, 2028

Project duration

24 months

Skills

Concepts (2)


PE8_9 - Production technology, process engineering - (2024)

Settore IIND-05/A - Impianti industriali meccanici
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