418 research outputs found

    Smart city : How smart is it actually?

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    The global megatrends of population growth and fast urbanisation are negatively impacting the life in the cities. Smart city is the high-level concept by which the cities try to address the need to improve their social, economic and environmental sustainability. This thesis studies how the smart city concept is defined, what are the underlying hypotheses and assumptions on which the smart city research is based on, what are the latest results and innovations of the smart city research, how the smart city initiatives are meeting their objectives, and how the hypotheses and assumptions may vary between the smart city initiatives. The objective of this study is to critically review the smart city research paradigm to find possible pitfalls, conflicting results and topics for further study and improvement. This research is conducted as a traditional critical literature review, covering the current academic literature on the smart city topic, the websites presenting the smart city initiatives around the world, and the latest popular literature for contrasting views. A qualitative comparison of the smart city initiatives in selected cities – Helsinki, Singapore and London – complements the literature review. The research strategy in this study approximates the grounded theory, utilising inductive reasoning to generate arguments and conclusions about the form, validity and future of the smart city. This study produced the following key findings: there are many different and overlapping definitions of smart city; the smart city development is mostly seen as the responsibility of smart ICT implementations, while simultaneously demanding for a more focused human viewpoint; the smart city initiatives form complex, multidisciplinary platforms that require holistic evaluation; the current evaluation methods and rankings of the smart cities vary considerably, making the evaluation of the success of the smart cities difficult; some of the existing smart city elements and proposed solutions are ineffective or even counterproductive for the smart city objectives. The main conclusions of this study were that the complex nature of the smart city initiatives and the conflicts and interdependencies of the smart city objectives are not fully addressed in the current smart city research, and that the current smart city research is not adequately multidisciplinary in nature. For the future, this research argues for the increased utilisation of research methods used in information systems science for their ability to address socio-technical and multidisciplinary problems. Also, the need for a future research on the efficacy of the multidisciplinary research of smart cities is identified.Väestönkasvu, siitä aiheutuva muuttoliike ja nopea kaupungistuminen ovat maailmanlaajuisia megatrendejä, jotka usein vaikuttavat kielteisesti elämisen ja asumisen laatuun kaupungeissa. Älykaupunki on ylemmän tason konsepti, jonka avulla kaupungit yrittävät muokata sosiaalista, taloudellista ja ympäristönsä kehitystä kestävämmälle pohjalle. Tässä tutkielmassa tarkastellaan, miten älykaupungin konsepti on määritelty, mitkä ovat ne taustaolettamukset ja perusteet, joiden varaan älykaupunkien tieteellinen tutkimus pohjautuu, mitkä ovat älykaupunkitutkimuksen viimeisimmät tulokset ja innovaatiot, miten älykaupunkihankkeet saavuttavat tavoitteensa ja miten niiden perusteet ja taustaolettamukset vaihtelevat älykaupunkien välillä. Tämän tutkimuksen tavoitteena on kriittisesti tarkastella älykaupunkien tutkimusparadigmaa ja löytää mahdollisia sudenkuoppia sekä ristiriitaisia tutkimusaiheita ja -tuloksia, joita voitaisiin käyttää älykaupunkien jatkotutkimukseen ja -kehittämiseen tulevaisuudessa. Tämä tutkimus on toteutettu perinteisenä kriittisenä kirjallisuustutkimuksena. Lähdeaineistona on käytetty älykaupunkien viimeisimpiä akateemisia tutkimustuloksia ja julkaisuja, älykaupunkihankkeiden omia nettisivustoja ympäri maailman sekä kontrastin vuoksi myös viimeisimpiä populaarin lähdekirjallisuuden käsittelemiä aiheita ja ilmiöitä. Kirjallisuustutkimusta on täydennetty kvalitatiivisella älykaupunkivertailulla, jossa Helsingin, Singaporen ja Lontoon älykaupunkihankkeita on vertailtu keskenään. Työn tutkimusstrategia muistuttaa ankkuroitua teoriaa, jossa induktiivisen päättelyn avulla pyritään lähdeaineistosta löytämään ja luomaan väitteitä, perusteluja ja johtopäätöksiä älykaupunkien muodosta, olemassaolon oikeellisuudesta ja tulevaisuudesta. Tutkimuksessa havaittiin seuraavat pääkohdat: älykaupunki voidaan määritellä usealla, myöskin samanaikaisesti päällekkäisellä tavalla; älykaupunkien kehittäminen nähdään yleensä tieto- ja viestintäteknologisten innovaatioiden kehittämisenä, vaikka samanaikaisesti usein vaaditaan myös inhimillisemmän näkökulman korostamista; älykaupunkihankkeet muodostavat monitahoisia, monia tieteenaloja koskettavia alustoja, jotka vaativat nykyistä kokonaisvaltaisempaa tarkastelua ja arvi-ointia; nykyiset älykaupunkien menestyksen mittarit ja arviointitavat vaihtelevat huomattavasti, jolloin älykaupunkien älykkyyden ja onnistumisen yhteismitallinen arviointi on vaikeaa; jotkut havaituista älykaupunkien ominaisuuksista ja ratkaisuista ovat tehottomia tai jopa kielteisesti älykaupunkien tavoitteisiin vaikuttavia. Tässä tutkimuksessa päädyttiin seuraaviin johtopäätöksiin: älykaupunkihankkeiden monimutkaisen ja ristiriitaisen luonteen takia nykyinen älykaupunkitutkimus- ja kehitys ei täysin pysty vastaamaan näiden ristiriitaisuuksien ja keskinäisriippuvuuksien tuomiin haasteisiin; nykyinen älykaupunkitutkimus ei myöskään ole tieteellisesti riittävän monialaista. Tämän tutkimuksen pohjalta voidaan suositella, että tulevaisuudessa älykaupunkien kehitys voisi pohjautua enemmän tietojärjestelmätieteiden tutkimusmetodologioiden hyödyntämiseen, jolloin älykaupunkien vaatimat sosiotekniset ja monitieteelliset näkökulmat saataisiin paremmin havaittua, katettua ja arvioitua tutkimustuloksissa. Tulevaisuudessa tarvitaan myös tutkimusta siitä, kuinka tehokkaasti monitieteellinen älykaupunkitutkimus onnistuu

    A Survey of Smart Parking Solutions

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    International audienceConsidering the increase of urban population and traffic congestion, smart parking is always a strategic issue to work on, not only in the research field but also from economic interests. Thanks to information and communication technology evolution, drivers can more efficiently find satisfying parking spaces with smart parking services. The existing and ongoing works on smart parking are complicated and transdisciplinary. While deploying a smart parking system, cities, as well as urban engineers, need to spend a very long time to survey and inspect all the possibilities. Moreover, many varied works involve multiple disciplines, which are closely linked and inseparable. To give a clear overview, we introduce a smart parking ecosystem and propose a comprehensive and thoughtful classification by identifying their functionalities and problematic focuses. We go through the literature over the period of 2000-2016 on parking solutions as they were applied to smart parking development and evolution, and propose three macro-themes: information collection, system deployment, and service dissemination. In each macro-theme, we explain and synthesize the main methodologies used in the existing works and summarize their common goals and visions to solve current parking difficulties. Lastly, we give our engineering insights and show some challenges and open issues. Our survey gives an exhaustive study and a prospect in a multidisciplinary approach. Besides, the main findings of the current state-of-the-art throw out recommendations for future research on smart cities and the Internet architecture

    Spaces of innovation : 21st century technopoles

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    Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2004.Page 129 blank.Includes bibliographical references (p. 121-128).Public authorities and private developers around the world are attempting to create and sustain hubs within the innovation-based economy by fostering successful urban environments. These large-scale developments succeed an earlier generation of post-industrial "technopoles" named after the French word popularized by Castells and Hall in Technopoles of the World (1994). In the 1990s, most planned technopoles resembled suburban office environments with generous landscaping, wide roads, and automobile-focused circulation systems. In contrast, today's economic development experts are increasingly emphasizing the need for interaction and cross-fertilization among companies and institutions in an attempt to foster innovation, from which successful communities are assumed to derive their competitive edge in an information- based economy. Parallel shifts in live-work patterns among creative talent groups are being documented in social science and anecdotal observations. These trends have heightened competition for qualified individuals and initiated a talent war among cities globally. And these individuals are living footloose lifestyles supported by mobile devices and wireless connectivity. Entrepreneurial public agencies and private developers have recognized the potential for reconceiving live-work environments as economic hubs. These holistic projects are identified as 21st century technopoles because they directly address and capitalize on the socio-economic shifts described above leading to vastly different ideal urban configurations. The thesis asks how urban form is expected to contribute to innovation; and, how urban form is being reconceptualized in turn at the neighborhood scale.(cont.) Four case studies provide a rich narrative that begins to sketch the range of proposed urban developments: Cyberjaya, Kuala Lumpur, Malaysia; Digital Media City, Seoul, Korea; one-north, Singapore; Lower Manhattan, New York. A narrative ties the four cases together providing "thick descriptions" as a base-line study for a new mode of technopole development. The analysis reaches from (1) "hardware" or the urban built environment and (2) "wiring" or the embedded and supported technologies to (3) "software" or the actors involved. The case studies indicate several emergent themes that are rescripting our urban environments. Dense urban zones with a high level of sensory diversity are being proposed for emerging technopoles that capitalize on the city as a metaphor for human interaction and exchange. Real estate value in this system is measured by the number of serendipitous encounters it facilitates. The dichotomous relationship between spaces of places and spaces of flows set forth by Castells seems inapplicable within the boundaries of these zones that are at once core and periphery, local and global. Finally, these developments are living laboratories for the technologies that support new live-work preferences and shifting lifestyles. Several contradictions become apparent in delving more deeply into the examples, which are still under development. In the promotional materials, diversity - demographic and physical - is embraced, but it is not clear how it will contribute to innovation. More generally, the projects plan for often unpredictable "knowledge accidents." ...by Susanne Seitinger.M.C.P

    IEOM Society International

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    IEOM Society Internationa

    Security of Cyber-Physical Systems

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    Cyber-physical system (CPS) innovations, in conjunction with their sibling computational and technological advancements, have positively impacted our society, leading to the establishment of new horizons of service excellence in a variety of applicational fields. With the rapid increase in the application of CPSs in safety-critical infrastructures, their safety and security are the top priorities of next-generation designs. The extent of potential consequences of CPS insecurity is large enough to ensure that CPS security is one of the core elements of the CPS research agenda. Faults, failures, and cyber-physical attacks lead to variations in the dynamics of CPSs and cause the instability and malfunction of normal operations. This reprint discusses the existing vulnerabilities and focuses on detection, prevention, and compensation techniques to improve the security of safety-critical systems

    MOBILITY ANALYSIS AND PROFILING FOR SMART MOBILITY SERVICES: A BIG DATA DRIVEN APPROACH. An Integration of Data Science and Travel Behaviour Analytics

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    Smart mobility proved to be an important but challenging component of the smart cities paradigm. The increased urbanization and the advent of sharing economy require a complete digitalisation of the way travellers interact with the mobility services. New sharing mobility services and smart transportation models are emerging as partial solutions for solving some tra c problems, improve the resource e ciency and reduce the environmental impact. The high connectivity between travellers and the sharing services generates enormous quantity of data which can reveal valuable knowledge and help understanding complex travel behaviour. Advances in data science, embedded computing, sensing systems, and arti cial intelligence technologies make the development of a new generation of intelligent recommendation systems possible. These systems have the potential to act as intelligent transportation advisors that can o er recommendations for an e cient usage of the sharing services and in uence the travel behaviour towards a more sustainable mobility. However, their methodological and technological requirements will far exceed the capabilities of today's smart mobility systems. This dissertation presents a new data-driven approach for mobility analysis and travel behaviour pro ling for smart mobility services. The main objective of this thesis is to investigate how the latest technologies from data science can contribute to the development of the next generation of mobility recommendation systems. Therefore, the main contribution of this thesis is the development of new methodologies and tools for mobility analysis that aim at combining the domain of transportation engineering with the domain of data science. The addressed challenges are derived from speci c open issues and problems in the current state of the art from the smart mobility domain. First, an intelligent recommendation system for sharing services needs a general metric which can assess if a group of users are compatible for speci c sharing solutions. For this problem, this thesis presents a data driven indicator for collaborative mobility that can give an indication whether it is economically bene cial for a group of users to share the ride, a vehicle or a parking space. Secondly, the complex sharing mobility scenarios involve a high number of users and big data that must be handled by capable modelling frameworks and data analytic platforms. To tackle this problem, a suitable meta model for the transportation domain is created, using the state of the art multi-dimensional graph data models, technologies and analytic frameworks. Thirdly, the sharing mobility paradigm needs an user-centric approach for dynamic extraction of travel habits and mobility patterns. To address this challenge, this dissertation proposes a method capable of dynamically pro ling users and the visited locations in order to extract knowledge (mobility patterns and habits) from raw data that can be used for the implementation of shared mobility solutions. Fourthly, the entire process of data collection and extraction of the knowledge should be done with near no interaction from user side. To tackle this issue, this thesis presents practical applications such as classi cation of visited locations and learning of users' travel habits and mobility patterns using historical and external contextual data

    Reports to the President

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    A compilation of annual reports for the 1999-2000 academic year, including a report from the President of the Massachusetts Institute of Technology, as well as reports from the academic and administrative units of the Institute. The reports outline the year's goals, accomplishments, honors and awards, and future plans

    Enhancing vehicle destination prediction using latent trajectory information

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    Intelligent transportation systems have the potential to provide road users with a range of useful applications, including vehicle preconditioning, traffic flow management and intelligent parking recommendations. The majority of these applications can benefit from knowledge of vehicle activities (common situations that a vehicle encounters e.g. traffic), along with the upcoming destinations that a vehicle will visit. We focus on the trajectories that vehicles provide, and the data contained within them, in order to ascertain information about the patterns in individuals' mobility data. Machine learning has been used in many different vehicle applications, and we focus on using these techniques to predict the activity of a vehicle and its future destinations. Clustering methods can be applied at the level of trajectories or the individual instances within them, and we explore both of these alternatives in this thesis. Additionally, we explore several classification approaches to predict activities and destinations. In developing our methods, we make use of a combination of both geospatial and temporal data along with on-board vehicle sensor data. This thesis presents novel methods for filtering stay points to identify points of interest and applying destination prediction to vehicle trajectories. Existing methods for stay point detection are not specific to vehicles, and therefore any region of low mobility is potentially considered to be of interest. We propose a novel method for filtering the extracted stay points to identify points of interest, using vehicle data to predict vehicle activities. The predicted activities are further used to represent trajectories as sequences of annotated locations, to inform the detection of similarities between journeys. Finally, this thesis presents a novel method for using additional properties of a trajectory to cluster trajectories into groupings of similar trajectories with the aim of improving the accuracy of destination prediction. We evaluate our proposed methods on a set of vehicle datasets, varying in purpose and the data available
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