SPECIAL SESSION #03

Michelangelo-Santo Gulino

Department of Industrial Engineering of Florence, Italy

• michelangelo.gulino@unifi.it

This session focuses on the critical role of metrology, advanced sensing, and data analytics in optimising the performance and sustainability of electric micromobility systems as well as lightweight electric vehicles, including quadricycles and L category platforms (e.g., L6e and L7e). Central to this discussion is the assessment of energy efficiency and battery health, including state-of-charge estimation and degradation modelling under diverse environmental conditions. The session also explores the deployment of advanced sensor architectures and IoT-enabled telematics, which facilitate real-time performance monitoring, predictive maintenance, and fleet management. A significant portion of the session is dedicated to the application of Artificial Intelligence (AI) and Machine Learning for anomaly detection, energy optimisation, and the development of assisted driving safety systems, such as collision avoidance and stability control. By leveraging large-scale behavioural analytics and precise measurement frameworks, this session aims to bridge the gap between technological innovation and the practical requirements for reliable, eco-friendly urban mobility solutions.

Topics of Interest include (but are not limited to):

1. Energy Efficiency and Battery Performance Assessment
• Quantifying energy consumption and battery performance, including state-of-charge estimation, degradation modelling, and the influence of duty cycles and environmental conditions.
2. Sensor Technologies and Data Acquisition in Micro and Light Mobility Systems
• This topic explores advanced sensing architectures and data acquisition strategies, addressing sensor fusion, calibration procedures, and the reliability of embedded measurement systems in dynamic operating environments.
3. Real-World Usage Data and Behavioural Analytics
• This topic focuses on the analysis of large-scale operational datasets to extract mobility patterns, characterise user behaviour, and support data-driven optimisation of micro and light mobility services.
4. Integration of IoT and Telematics for Performance Monitoring
• This topic addresses the implementation of IoT-enabled monitoring systems, including data communication architectures, edge/cloud processing, and applications in predictive maintenance and fleet management.
5. Artificial Intelligence and Performance Optimisation
• Application of artificial intelligence techniques to enhance measurement, modelling, and decision-making in micro and light mobility systems. It includes machine learning for state estimation, anomaly detection, predictive maintenance, and optimisation of energy usage and operational performance.
6. Assisted Driving and Safety Systems in Micro and Light mobility
• Evaluation of assisted driving functionalities for micro and light mobility devices, including stability control, collision avoidance, and rider/driver assistance systems.

Michelangelo-Santo Gulino Ph.D., is a researcher at the University of Florence, specialising in mechanical design, metrology, and data-driven analysis for electric micro and light mobility. He has contributed to EU-funded projects like LIFE2M and H2020 LEONARDO, focusing on innovative vehicle design and advanced sensing technologies. Author of 55 scientific publications, he is actively involved in international research collaborations and standardisation committees.