Research team
Expertise
My research centers on using data analysis and artificial intelligence to tackle complex urban problems. I specialize in urban mobility, with a focus on service operations and control, topological assessment of public transport networks, accessibility and equity, and passenger demand analysis.
AI-driven modular platform for emission-reduction & efficient shipping (AIMPERES).
Abstract
AIMPERES addresses one of the major challenges in European waterborne transport: reducing greenhouse gas emissions and air pollution from existing inland, coastal, and deep-sea vessels. While alternative fuels and new propulsion technologies are emerging, most ships currently in operation will remain active for decades, making retrofit-friendly energy efficiency solutions essential. The project will develop and demonstrate an AI-powered, modular Energy Management System (EMS) that combines real-time sensor data, hybrid digital twins, low-cost emission monitoring, and crew-oriented decision support. The platform integrates physics-based models with machine learning and reinforcement learning techniques to create adaptive digital twins capable of accurately representing vessel behaviour while remaining computationally efficient for real-time operation. AIMPERES will introduce affordable onboard emission monitoring solutions capable of measuring multiple pollutants in real time, enabling continuous compliance assessment and operational feedback. Using operational data, weather information, vessel characteristics, and energy system models, the EMS will optimize energy production, storage, and consumption across a wide range of propulsion architectures. The system will provide actionable recommendations to crews regarding speed, manoeuvring, engine loading, routing, and energy management without increasing operational complexity. The project will validate its approach through three complementary case studies covering inland waterway transport, coastal shipping, and deep-sea shipping. AIMPERES will assess both operational improvements and retrofit opportunities, considering technical, environmental, and economic factors. The project is expected to deliver measurable reductions in fuel consumption and emissions, support compliance with evolving European and international regulations, and provide performance-based design and retrofit guidelines for future vessel developments. By combining advanced AI, digital twins, modular energy architectures, and user-centred decision support into a practical retrofit-ready solution, AIMPERES aims to accelerate the maritime sector's green and digital transition while creating a viable business case for sustainable shipping.Researcher(s)
- Promoter: Hellinckx Peter
- Co-promoter: Massobrio Renzo
Research team(s)
Funding
- EU-KADER
Project type(s)
- Research Project