MonitorAI – Digitalized Risk Assessment

PROJECT

MonitorAI – Digitalized Risk Assessment

Digitalized Risk Assessment

PROJECT LEAD

CONCEPT

The MonitorAI project develops an advanced Digital Twin system for monitoring ergonomics and human well-being in the workplace. It leverages low-cost cameras integrated with microcontrollers (e.g., Raspberry Pi), and combines RGB data with information from advanced sensors such as infrared and depth cameras.
This integration enhances both accuracy and processing speed compared to traditional methods. Based on Computer Vision and Artificial Intelligence algorithms, the system enables real-time 3D posture estimation, overcoming issues like occlusions and environmental constraints, while remaining non-invasive and scalable.

CONTEXT

Led by the University of L’Aquila, MonitorAI – Digitalized Risk Assessment aims to create an innovative Human Digital Twin (HDT) model using non-invasive, commercial sensors to improve postural risk assessment for workers in manufacturing environments.
The goal is to optimize worker well-being and performance by providing real-time data on health and posture, helping to reduce musculoskeletal disorders and enhance ergonomic conditions.
The project includes the development of a digital framework, prototypes, industrial testing, and a risk management plan to ensure sustainable and transferable results for both industry and future academic research.

Beneficiari

OBJECTIVES AND EXPECTED RESULTS

The MonitorAI research project aims to develop an innovative technological framework based on a Human Digital Twin model for monitoring human performance and well-being in industrial workplaces.

Main objectives:

Development of an advanced HDT model: Design and implementation of a digital twin capable of integrating real-time ergonomic parameters from commercial, non-invasive sensors
Integration of advanced algorithms: Use of innovative Human Pose Estimation (HPE) models for automated ergonomic analyses and postural risk assessments
Prototype creation and industrial testing: Development of a low-cost hardware-based system, validated in real environments for accuracy and effectiveness
Framework optimization: Definition of data management methods and integration into industrial workflows, enabling real-time decision-making in production processes

Expected results:

New HDT model: A theoretical and practical framework for accurately managing dynamically updated ergonomic data, ready for industrial digitalization
Proof of concept: Experimental validation of a hardware-software solution outperforming traditional tools (gold standards) in terms of accuracy and cost
Industrial impact: Reduction in musculoskeletal disorders, improved worker ergonomics, and overall increased safety and efficiency
Scientific dissemination: Results shared in open-source repositories and published in high-impact journals, encouraging further research and industrial adoption

The proposed technological system aims to drive innovation in ergonomic monitoring methodologies, promoting the integration of human-centric models in the factories of the future.

KEY FIGURES

MonitorAI – Digitalized Risk Assessment

PROJECT

MonitorAI – Digitalized Risk Assessment

4

3000

15

4

2

5

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