Keynotes
Cargo Bikes as a Key Driver for Sustainable Urban Logistics
Christoph Hupfer holds a professorship in traffic engineering and transportation planning at the Hochschule Karlsruhe – University of Applied Sciences. He did his PhD at the University of Kaiserslautern, Germany about “Video based Traffic Safety Analysis of Pedestrian Crossings at Major Urban Roads”. After five years as a consultant for different counties, municipalities and companies in mobility and transport, he was hired for a professorship in traffic engineering and transportation planning at the faculty of architecture and civil engineering at the Hochschule Karlsruhe in 2001.
In 2012 he was elected as founding dean for the Faculty for Information Management and Media. At the same time, he founded the transportation management bachelor program, followed by a transportation management master program in 2015 under his leading ship.
In addition, he works as a senior expert in traffic, transport and mobility for municipalities, state administrations and companies.
Since 2021 he is the founding head of the state institute on sustainable mobility (“Baden-Württemberg Institut für Nachhaltige Mobilität”), a multidisciplinary coalition of applied research located at different universities in the state of Baden-Württemberg. He is successful in transformation related research focusing on tools in decision making for deciders in administration and politician as well as in participation processes, sustainable road infrastructure design, traffic safety and sustainable urban mobility in general..
Abstract
Various transport mobility concepts (such as delivery with electric vans, cargo bicycles, the use of mobile micro-hubs, automated deliveries using robots, drones, or autonomous vehicles) demonstrate approaches to creating a foundation for alternative and environmentally friendly urban logistics. To reduce the negative impact of transport on the climate, important steps are the transition to more sustainable energy sources, the development of public transport, and the promotion of electric and other environmentally friendly modes of transport. For the transport of small loads in the city, the potential advantages of cargo bikes in terms of energy consumption, environmental impact and road load are proposed as an alternative to trucks. In densely populated cities, electric cargo bicycles are becoming increasingly popular as a replacement for vans and cars for delivering goods such as groceries and parcels. The research aims to assess the effectiveness of using cargo bicycles as an alternative to cars for transporting small consignment of goods within the city limits.
A simulation model has been developed for the process of forming cargo transportation routes within the city. The study compared different technologies for serving customers of a supermarket chain (pendulum routes and distribution-assembly routes), while modeling was carried out for the conditions of use of various vehicles (an electric cargo bike and a car). As a result of simulation modeling, distribution routes were formed and operational parameters were optimized on cargo delivery routes in the city for various types of vehicles with different carrying capacities.
Prof. Christoph Hupfer
Hochschule Karlsruhe – University of Applied Sciences, Karlsruhe, Germany
Nicos Maglaveras
Professor of Medical Informatics Aristotle University of Thessaloniki Greece
Personalised health driven by digital health systems and multi-source health/environmental data, ML/AI/DL analytics and predictive models
Nicos Maglaveras received the diploma in electrical engineering from the Aristotle University of Thessaloniki (A.U.Th.), Greece, in 1982, and the M.Sc. and Ph.D. degrees in electrical engineering with an emphasis in biomedical engineering from Northwestern University, Evanston, IL, in 1985 and 1988, respectively. He is currently a Professor of Medical Informatics, A.U.Th. He served as head of the graduate program in medical informatics at A.U.Th, as Visiting Professor at Northwestern University Dept of EECS (2016-2019), and is a collaborating researcher with the Center of Research and Technology Hellas, and the National Hellenic Research Foundation.
His current research interests include biomedical engineering, biomedical informatics, ehealth, AAL, personalised health, biosignal analysis, medical imaging, and neurosciences. He has published more than 500 papers in peer-reviewed international journals, books and conference proceedings out of which over 160 as full peer review papers in indexed international journals. He has developed graduate and undergraduate courses in the areas of (bio)medical informatics, biomedical signal processing, personal health systems, physiology and biological systems simulation.
He has served as a Reviewer in CEC AIM, ICT and DGRT D-HEALTH technical reviews and as reviewer, associate editor and editorial board member in more than 20 international journals, and participated as Coordinator or Core Partner in over 45 national and EU and US funded competitive research projects attracting more than 16 MEUROs in funding. He has served as president of the EAMBES in 2008-2010. Dr. Maglaveras has been a member of the IEEE, AMIA, the Greek Technical Chamber, the New York Academy of Sciences, the CEN/TC251, Eta Kappa Nu and an EAMBES Fellow.
Abstract
The last years saw a steep increase in the number of wearable sensors and systems, mhealth and uhealth apps both in the clinical settings and in everyday life. Further large amounts of data both in the clinical settings (imaging, biochemical, medication, electronic health records, -omics), in the community (behavioral, social media, mental state, genetic tests, wearable driven bio-parameters and biosignals) as well as environmental stressors and data (air quality, water pollution etc.) have been produced, and made available to the scientific and medical community, powering the new AI/DL/ML based analytics for the identification of new digital biomarkers leading to new diagnostic pathways, updated clinical and treatment guidelines, and a better and more intuitive interaction medium between the citizen and the health care system.
Thus, the concept of connected and translational health has started evolving steadily, connecting pervasive health systems, using new predictive models, new approaches in biological systems modeling and simulation, as well as fusing data and information from different pipelines for more efficient diagnosis and disease management.
In this talk, we will present the current state-of-the-art in personalized health care by presenting cases from COVID-19 and COPD patients using advanced wearable vests and new technology sensors including lung sound and EIT, new outcome prediction models in COVID-19 ICU patients fusing X-Rays, lung sounds, and ICU parameters transformed via AI/ML/DL pipelines, new approaches fusing environmental stressors with -omics analytics for chronic disease management, and finally new ML/AI-driven methodologies for predicting mental health diseases including suicidality, anxiety, and depression.
