The number of people living in cities is growing dramatically. According to IBM, in 1900, only 13% of the world's population lived in cities. By 2050, that number will have risen to 70%. The huge growth of cities places a great strain on infrastructure and city leaders, in terms of traffic and transportation, safety and security, commerce, etc. Algorithmic methods are helping city officials to make their cities work better. As IBM SmartCities says: ``With recent advances in technology, we can infuse our existing infrastructures with new intelligence. By this, we mean digitizing and connecting our systems, so they can sense, analyze and integrate data, and respond intelligently to the needs of their jurisdictions. In short, we can revitalize them so they can become smarter and more efficient.
Management problems from today's large and complex metropolitan areas are characterized by the availability of extremely large amounts of data not always used or usable; heterogeneous information sources; strong uncertainties and rapid evolution of data; and conflicting preferences and conflicting interpretations of data. Algorithmic Decision Theory (ADT) can help. Through ADT, support for optimizing vehicle routing in waste collection could be integrated with general decision support tools. Providing information to citizens concerning services (e.g., through info-mobility terminals) could be improved through feedback, customization, and learning features 2E Information about the preferences, habits, opinions and behaviors of users of public services, available through social networks, polls and focus groups, could be utilized in managing services. Precise decision making based on Geographical Information Systems could result from methods to synthesize information that now is only available analytically.20
Providers of public services need to understand the increasing diversity of the needs of citizens, diversify their offerings, and do so in the best possible way, thus offering ``smart services.'' The overall objective of the workshop is to study the use of decision sciences and technologies through the creation of such ``smart services,'' their management, and assessment. We will explore tools of operations research, data mining, social choice theory, recommender systems, classification, distributed computing and information systems, and study methods of ADT to aid city government to manage services such as traffic management and emergency services in a better and smarter way.
The workshop aims at contributing in defining a ``smart city'' in terms of using and providing a city's services. It will seek algorithms for real-time information fusion and integrated data management, dissemination strategies, project management tools, and algorithms to aid in making decisions about provision of ``smart services.'' It will explore how ADT could aid citizens to use public services in a better and smarter way, including emphasis on mobility, culture, and participation in policy making. In traffic, for example, the workshop will consider such issues as: merging of heterogeneous information sources concerning traffic; a market of mobility credits for diversified mobility services (mass transit, car pooling, bike sharing, dial-to-ride etc.); facility user profiling; and dynamic re-allocation of mobility resources under traffic disruptions. Participants in the workshop will include city and regional planners, computer scientists, operations researchers, economists, and decision theorists. As part of the COST strategic workshops the meeting also aims at shaping the research agenda for the coming years in this critically important area.20
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