THE ROLE OF COLLABORATIVE SOFTWARE AND DECISION SUPPORT SYSTEMS IN THE SMARTER CITIES

The transition from the traditional city to the smart city is made by supported efforts regarding the achievement of a more steady, more efficient, more responsible city, through convergent strategies that deal with Smart Transportation Systems, Energy and Utilities Management, Water Management, Smart Public Safety, Healthcare Systems, Environmental Management, Educational Systems, Telecommunications (ITC Support),etc. and Positive Thinking. Service Oriented Architecture (SOA) meets the customers’ needs and the administration, the management of data, information, knowledge and decisions through Collaborative Systems and Decision Support Systems have a major impact both at the level of the smart city and the level of subsystems/services, and the information technology within smart cities becomes a major direction of research in the field of ITC.Smart City, Collaborative Systems, Decision Support Systems (DSS), Service Oriented Architecture (SOA), Portal technology

Trends in Smart City Development

This report examines the meanings and practices associated with the term 'smart cities.' Smart city initiatives involve three components: information and communication technologies (ICTs) that generate and aggregate data; analytical tools which convert that data into usable information; and organizational structures that encourage collaboration, innovation, and the application of that information to solve public problems

Will Smarter Marketing End Social Discrimination? A Critical Review

Purpose - There are two claims made by the web marketing/advertising industry. 1) By collecting, managing, and mining data, companies serve consumer’s best interests and 2) by adopting sophisticated analytics web marketers avoid discriminations that disserve individuals. Although we share an interest in ending social discrimination, we are more circumspect about pronounced individualism and technological fixes. Despite its appeal, or perhaps because of it, we should not accept the claim at face value. In this paper we argue that social discrimination may not disappear under smarter marketing; more overt forms may wane only to be replaced by more subtle forms. Design/methodology/approach - We compare the two most important techniques of smarter marketing- predictive analytics and Facebook\u27s social graph- with current discriminatory practices of weblining and e-scoring. While noting advances against overt discrimination we describe how smarter marketing allows for covert forms. Findings - Innovative strategies to record and mine users’ tastes and social connectivity for marketing purposes open the way for covert social discrimination. Originality/value - We provide a critical assessment of two claims made by the web marketing/advertising industry: 1) By monitoring consumer web activity and collecting, managing, and mining data, companies serve consumer’s best interests and 2) by adopting sophisticated analytics web marketers avoid discriminations that disserve individuals

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

Illuminating Smart City Solutions – A Taxonomy and Clusters

With urban problems intensifying, Smart City solutions are recognized by researchers and practitioners as one of the most promising solutions to make urban areas economically, environmentally, and socially sustainable. While many elements of Smart City solutions have been explored, existing works either treat Smart City solutions as technical black boxes or focus exclusively on Smart City solutions’ technical or non-technical characteristics. Therefore, to conceptualize the unique characteristics of Smart City solutions currently available, we developed a multi-layer taxonomy based on Smart City solution literature and a sample of 106 Smart City solutions. Moreover, we identified three clusters, each covering a typical combination of characteristics of Smart City solutions. We evaluated our findings by applying the Q-sort method. The results contribute to the descriptive knowledge of Smart City solutions as a first step for a theory for analyzing and enable researchers and practitioners to understand Smart City solutions more holistically