ICAI is an open national network of academic, industrial and governmental partners that is based at Amsterdam Science Park. At present, ICAI has sixteen partners: Ahold Delhaize, Bosch, Delft Imaging Systems, Delft University of Technology, Elsevier, Inception Institute of Artificial Intelligence Ltd. (IIAI), ING, National Police, Qualcomm, Radboudumc, Radboud University, Thirona, TomTom, University of Amsterdam, Utrecht University and Vrije Universiteit Amsterdam. So far eleven research labs have been founded: AI for FinTech Lab, AIM Lab, AIRLab Amsterdam, AIRLab Delft, Atlas Lab, Delta Lab, Elsevier AI Lab, Police Lab AI, QUVA Lab, Radboud AI for Health Lab and Thira Lab, with more to come.
Innovation Center for Artificial Intelligence
The Innovation Center for Artificial Intelligence (ICAI) is a national initiative focused on joint technology development between academia, industry and government in the area of artificial intelligence. The Netherlands has the talent, the world-class research and the longstanding tradition in AI education to be one of the world’s top ranked countries in terms of innovation power. ICAI brings these positive forces together in a unique national initiative.
ICAI’s innovation strategy is organized around industry labs, these are multi-year strategic collaborations with a focus on technology and talent development. ICAI will create innovative AI-applications, distribute AI-knowledge for companies and organizations in the form of technology products and tools, train corporate employees through dedicated courses, and simultaneously maintain a connection with other world-level science centers. ICAI will also facilitate commercialization by enhancing start-up and spin-outs.
Institute for Biodiversity and Ecosystem Dynamics (IBED, UvA)
The Institute for Biodiversity and Ecosystem Dynamics (IBED) is one of eight research institutes of the Faculty of Science at the University of Amsterdam. IBED was founded in 2000 by merging research groups with the expertise in ecology and evolutionary biology, physical geography and environmental chemistry. Research at IBED targets the world around us from the level of molecules and genes to entire ecosystems. We aim to unravel how ecosystems function in all their complexity, and how they change due to natural processes and human activities. At the core of IBED lies the integrated approach to study biodiversity, ecosystems and the environment using methods typical of the disciplines of ecology, physical geography and environmental chemistry.
Ambient monitoring from an elderly-centred design perspective: what, who and how
This paper describes a participatory design-oriented study of an ambient assisted living system for monitoring the daily activities of elderly residents. The work presented addresses these questions 1) What daily activities the elderly participants like to be monitored, 2) With whom they would want to share this monitored data and 3) How a monitoring system for the elderly should be designed. For this purpose, this paper discusses the study results and participatory design techniques used to exemplify and understand desired ambient-assisted living scenarios and information sharing needs. Particularly, an interactive dollhouse is presented as a method for including the elderly in the design and requirements gathering process for residential monitoring. The study results indicate the importance of exemplifying ambient-assisted living scenarios to involve the elderly and so to increase acceptance and utility of such systems. The preliminary studies presented show that the participants were willing to have most of their daily activities monitored. However, they mostly wanted to keep control over their own data and share this information with medical specialists and particularly not with their fellow elderly neighbours.
Kanis M. et al. (2011) Ambient Monitoring from an Elderly-Centred Design Perspective: What, Who and How. In: Keyson D.V. et al. (eds) Ambient Intelligence. AmI 2011. Lecture Notes in Computer Science, vol 7040. Springer, Berlin, Heidelberg
Data-driven Travel Demand Modelling and Agent-based Traffic Simulation in Amsterdam Urban Area
The goal of this project is the development of a large-scale agent-based traffic simulation system for Amsterdam urban area, validated on sensor data and adjusted for decision support in critical situations and for policy making in sustainable city development, emission control and electric car research. In this paper we briefly describe the agent-based simulation workflow and give the details of our data- driven approach for (1) modeling the road network of Amsterdam metropolitan area extended by major national roads, (2) recreating the car owners population distribution from municipality demographic data, (3) modeling the agent activity based on travel survey, and (4) modeling the inflow and outflow boundary conditions based on the traffic sensor data. The models are implemented in scientific Python and MATSim agent-based freeware. Simulation results of 46.5 thousand agents -with travel plans sampled from the model distributions- show that travel demand model is consistent, but should be improved to correspond with sensor data. The next steps in our project are: extensive validation, calibration and testing of large-scale scenarios, including critical events like the major power outage in the Netherlands (doi:10.1016/j.procs.2015.11.039), and modelling emissions and heat islands caused by traffic jams.
Melnikov, V. R., Krzhizhanovskaya, V. V., Lees, M. H., & Boukhanovsky, A. V. (2016). Data-driven Travel Demand Modelling and Agent-based Traffic Simulation in Amsterdam Urban Area. Procedia Computer Science, 80, 2030-2041. DOI: https://doi.org/10.1016/j.procs.2016.05.523