Toward Enabling Convenient Urban Transit through Mobile Crowdsensing

International audienceThe smart cities of the future are expected to be serviced by advanced, personalized multimodal transit systems, charged with timely transport of citizens. Optimizing routes on such networks is a complex problem, in part due to the fact that simple metrics such as latency by themselves are not sufficient to find the best routes. In this paper, we focus on the problem of providing commuters with personalized routes with the most convenience. We present our mathematical model of user convenience during a multi-leg journey, and the overview of a middleware for enabling convenient transit (including ensuring acceptable network connectivity to mobile apps) by using crowdsourcing. We also report on initial insights obtained through empirical studies on network connectivity and user-perception of convenience in Delhi, India, and Paris, France

ComfRide: A smartphone based system for comfortable public transport recommendation

Passenger comfort is a major factor influencing a commuter's decision to avail public transport. Existing studies suggest that factors like overcrowding, jerkiness, traffic congestion etc. correlate well to passenger's (dis)comfort. An online survey conducted with more than 300 participants from 12 different countries reveals that different personalized and context dependent factors influence passenger comfort during a travel by public transport. Leveraging on these findings, we identify correlations between comfort level and these dynamic parameters, and implement a smartphone based application, ComfRide, which recommends t

Succeeding with Smart People Initiatives: Difficulties and Preconditions for Smart City Initiatives that Target Citizens

Smart City is a paradigm for the development of urban spaces through the implementation of state-of-the-art ICT. There are two main approaches when developing Smart Cities: top-down and bottom-up. Based on the bottom-up approach, the concepts of Smart People and Smart Communities have emerged as dimensions of the Smart City, advocating for the engagement of citizens in Smart People initiatives. The aim of this research is both to find the types of Smart People initiatives and to identify their difficulties and preconditions for success. However, such initiatives that aim to (1) leverage the citizens intellectually and (2) use citizens as a source of input for ideas and innovation, are understudied. Therefore, this research proposes a concentrated framework of Smart People initiatives from an extensive literature review. On one hand, this framework contributes with a common ground and vocabulary that facilitates the dialogue within and between practitioners and academia. On the other hand, the identification of difficulties and preconditions guides the academia and practitioners in how to successfully account for citizens in the Smart City. From the literature review and the conduct of case studies of five European cities, participation came out as the key difficulty across both types of Smart People initiatives and cases, closely followed by awareness, motivation and complexity

Towards Building Real-Time, Convenient Route Recommendation System for Public Transit

International audiencePublic transportation is essential for sustainable and economical development of cities. Several transport organizations aim to provide service information to commuters through web and mobile apps. This information includes possible routes between two stations, estimated travel and arrival times, and real-time updates about traffic conditions. However, this information is currently not personalized according to commuter preferences. In this work, we emphasize the need for personalized transit service information to commuters and present a vision of our work in this direction. Our final goal is to develop a fully-functional personalized route recommendation system for public transit commuters. This involves identifying commuter preferences and suitable recommendation techniques, and developing a platform to communicate this information to the commuters. We identify the requirements for the development of this platform, and propose an architecture for our system. As a proof of concept, we present an Android participatory sensing application - MetroCognition, which acquires feedback on convenience experienced by commuters in public transit

Survey of smart parking systems

The large number of vehicles constantly seeking access to congested areas in cities means that finding a public parking place is often difficult and causes problems for drivers and citizens alike. In this context, strategies that guide vehicles from one point to another, looking for the most optimal path, are needed. Most contributions in the literature are routing strategies that take into account different criteria to select the optimal route required to find a parking space. This paper aims to identify the types of smart parking systems (SPS) that are available today, as well as investigate the kinds of vehicle detection techniques (VDT) they have and the algorithms or other methods they employ, in order to analyze where the development of these systems is at today. To do this, a survey of 274 publications from January 2012 to December 2019 was conducted. The survey considered four principal features: SPS types reported in the literature, the kinds of VDT used in these SPS, the algorithms or methods they implement, and the stage of development at which they are. Based on a search and extraction of results methodology, this work was able to effectively obtain the current state of the research area. In addition, the exhaustive study of the studies analyzed allowed for a discussion to be established concerning the main difficulties, as well as the gaps and open problems detected for the SPS. The results shown in this study may provide a base for future research on the subject.Fil: Diaz Ogás, Mathias Gabriel. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Fabregat Gesa, Ramon. Universidad de Girona; EspañaFil: Aciar, Silvana Vanesa. Universidad Nacional de San Juan. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; Argentin

A Bibliometric Diagnosis and Analysis about Smart Cities

[EN] This article aims to present a bibliometric analysis of Smart Cities. The study analyzes the most important journals during the period between 1991 and 2019. It provides helpful insights into the document types, the distribution of countries/territories, the distribution of institutions, the authors' geographical distribution, the most active authors and their research interests or fields, the relationships between principal authors and more relevant publications, and the most cited articles. This paper also provides important information about the core and historical references and the most cited papers. The analysis used the keywords and thematic noun-phrases in the titles and abstracts of the sample papers to explore the hot research topics in the top journals (e.g., 'Smart Cities', 'Intelligent Cities', 'Sustainable Cities', 'e-Government', 'Digital Transformation', 'Knowledge-Based City', etc.). The main objective is to have a quantitative description of the published literature about Smart Cities; this description will be the basis for the development of a methodology for the diagnosis of the maturity of a Smart City. The results presented here help to define the scientific concept of Smart Cities and to measure the importance that the term has gained through the years. The study has allowed us to know the main indicators of the published literature in depth, from the date of publication of the first articles and the evolution of these indicators to the present day. From the main indicators in the literature, some were selected to be applied: The most influential journals on Smart Cities according to the general citation structure in Smart Cities, Global Impact Factor of Smart Cities, number of publications, publications on Smart Cities around the world, and their correlation.Pérez, LM.; Oltra Badenes, RF.; Oltra Gutiérrez, JV.; Gil Gómez, H. (2020). A Bibliometric Diagnosis and Analysis about Smart Cities. Sustainability. 12(16):1-43. https://doi.org/10.3390/su12166357S1431216Guo, Y.-M., Huang, Z.-L., Guo, J., Li, H., Guo, X.-R., & Nkeli, M. J. (2019). Bibliometric Analysis on Smart Cities Research. Sustainability, 11(13), 3606. doi:10.3390/su11133606Mora, L., Bolici, R., & Deakin, M. (2017). The First Two Decades of Smart-City Research: A Bibliometric Analysis. Journal of Urban Technology, 24(1), 3-27. doi:10.1080/10630732.2017.1285123Albino, V., Berardi, U., & Dangelico, R. M. (2015). Smart Cities: Definitions, Dimensions, Performance, and Initiatives. Journal of Urban Technology, 22(1), 3-21. doi:10.1080/10630732.2014.942092Li, C., Liu, X., Dai, Z., & Zhao, Z. (2019). Smart City: A Shareable Framework and Its Applications in China. Sustainability, 11(16), 4346. doi:10.3390/su11164346Merigó, J. M., & Yang, J.-B. (2016). Accounting Research: A Bibliometric Analysis. Australian Accounting Review, 27(1), 71-100. doi:10.1111/auar.12109Garg, K. C., & Sharma, C. (2017). Bibliometrics of Library and Information Science research in India during 2004-2015. DESIDOC Journal of Library & Information Technology, 37(3), 221-227. doi:10.14429/djlit.37.3.11188Metse, A. P., Wiggers, J. H., Wye, P. M., Wolfenden, L., Prochaska, J. J., Stockings, E. A., … Bowman, J. A. (2016). Smoking and Mental Illness: A Bibliometric Analysis of Research Output Over Time. Nicotine & Tobacco Research, 19(1), 24-31. doi:10.1093/ntr/ntw249Broadus, R. N. (1987). Toward a definition of «bibliometrics». Scientometrics, 12(5-6), 373-379. doi:10.1007/bf02016680Hood, W. W., & Wilson, C. S. (2001). Scientometrics, 52(2), 291-314. doi:10.1023/a:1017919924342Thelwall, M. (2008). Bibliometrics to webometrics. Journal of Information Science, 34(4), 605-621. doi:10.1177/0165551507087238Bar-Ilan, J. (2008). Informetrics at the beginning of the 21st century—A review. Journal of Informetrics, 2(1), 1-52. doi:10.1016/j.joi.2007.11.001Narin, F., Olivastro, D., & Stevens, K. A. (1994). Bibliometrics/Theory, Practice and Problems. Evaluation Review, 18(1), 65-76. doi:10.1177/0193841x9401800107Zupic, I., & Čater, T. (2014). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429-472. doi:10.1177/1094428114562629OSAREH, F. (1996). Bibliometrics, Citation Analysis and Co-Citation Analysis: A Review of Literature I. Libri, 46(3). doi:10.1515/libr.1996.46.3.149Merigó, J. M., Gil-Lafuente, A. M., & Yager, R. R. (2015). An overview of fuzzy research with bibliometric indicators. Applied Soft Computing, 27, 420-433. doi:10.1016/j.asoc.2014.10.035Blanco-Mesa, F., Merigó, J. M., & Gil-Lafuente, A. M. (2017). Fuzzy decision making: A bibliometric-based review. Journal of Intelligent & Fuzzy Systems, 32(3), 2033-2050. doi:10.3233/jifs-161640Björneborn, L., & Ingwersen, P. (2004). Toward a basic framework for webometrics. Journal of the American Society for Information Science and Technology, 55(14), 1216-1227. doi:10.1002/asi.20077Gupta, B. . M., & Dhawan, S. (2019). Electronic books A scientometric assessment of global literature during 1993 2018. DESIDOC Journal of Library & Information Technology, 39(5), 251-258. doi:10.14429/djlit.39.5.14573Kokol, P., Blažun Vošner, H., & Završnik, J. (2020). Application of bibliometrics in medicine: a historical bibliometrics analysis. Health Information & Libraries Journal, 38(2), 125-138. doi:10.1111/hir.12295Michalopoulos, A., & Falagas, M. E. (2005). A Bibliometric Analysis of Global Research Production in Respiratory Medicine. Chest, 128(6), 3993-3998. doi:10.1378/chest.128.6.3993Lefaivre, K. A., Shadgan, B., & O’Brien, P. J. (2011). 100 Most Cited Articles in Orthopaedic Surgery. Clinical Orthopaedics & Related Research, 469(5), 1487-1497. doi:10.1007/s11999-010-1604-1Kelly, J. C., Glynn, R. W., O’Briain, D. E., Felle, P., & McCabe, J. P. (2010). The 100 classic papers of orthopaedic surgery. The Journal of Bone and Joint Surgery. British volume, 92-B(10), 1338-1343. doi:10.1302/0301-620x.92b10.24867Zhang, M., Zhou, Y., Lu, Y., He, S., & Liu, M. (2019). The 100 most-cited articles on prenatal diagnosis. Medicine, 98(38), e17236. doi:10.1097/md.0000000000017236Zou, Y., Luo, Y., Zhang, J., Xia, N., Tan, G., & Huang, C. (2019). Bibliometric analysis of oncolytic virus research, 2000 to 2018. Medicine, 98(35), e16817. doi:10.1097/md.0000000000016817Svider, P. F., Choudhry, Z. A., Choudhry, O. J., Baredes, S., Liu, J. K., & Eloy, J. A. (2012). The use of theh-indexin academic otolaryngology. The Laryngoscope, 123(1), 103-106. doi:10.1002/lary.23569Poskevicius, L., De la Flor-Martínez, M., Galindo-Moreno, P., & Juodzbalys, G. (2019). Scientific Publications in Dentistry in Lithuania, Latvia, and Estonia Between 1996 and 2018: A Bibliometric Analysis. Medical Science Monitor, 25, 4414-4422. doi:10.12659/msm.914223Ahmad, P., Asif, J. A., Alam, M. K., & Slots, J. (2019). A bibliometric analysis of Periodontology 2000. Periodontology 2000, 82(1), 286-297. doi:10.1111/prd.12328Kostoff, R. N., Toothman, D. R., Eberhart, H. J., & Humenik, J. A. (2001). Text mining using database tomography and bibliometrics: A review. Technological Forecasting and Social Change, 68(3), 223-253. doi:10.1016/s0040-1625(01)00133-0Grant, J. (2000). Evaluating «payback» on biomedical research from papers cited in clinical guidelines: applied bibliometric study. BMJ, 320(7242), 1107-1111. doi:10.1136/bmj.320.7242.1107Vergidis, P. I., Karavasiou, A. I., Paraschakis, K., Bliziotis, I. A., & Falagas, M. E. (2005). Bibliometric analysis of global trends for research productivity in microbiology. European Journal of Clinical Microbiology & Infectious Diseases, 24(5), 342-346. doi:10.1007/s10096-005-1306-xSuárez Roldan, C., Chaparro, N., & Rojas-Galeano, S. (2019). Análisis Bibliométrico de la Revista Ingeniería (2010-2017). Ingeniería, 24(2). doi:10.14483/23448393.14678Ratten, V., Pellegrini, M. M., Fakhar Manesh, M., & Dabić, M. (2020). Trends and changes in Thunderbird International Business Review journal: A bibliometric review. Thunderbird International Business Review, 62(6), 721-732. doi:10.1002/tie.22124Baker, H. K., Kumar, S., & Pattnaik, D. (2020). Fifty years of The Financial Review  : A bibliometric overview. Financial Review, 55(1), 7-24. doi:10.1111/fire.12228Charlesworth, M., Klein, A. A., & White, S. M. (2019). A bibliometric analysis of the conversion and reporting of pilot studies published in six anaesthesia journals. Anaesthesia, 75(2), 247-253. doi:10.1111/anae.14817Van Noorden, R., Maher, B., & Nuzzo, R. (2014). The top 100 papers. Nature, 514(7524), 550-553. doi:10.1038/514550aNicoll, L. H., Oermann, M. H., Carter‐Templeton, H., Owens, J. K., & Edie, A. H. (2020). A bibliometric analysis of articles identified by editors as representing excellence in nursing publication: Replication and extension. Journal of Advanced Nursing, 76(5), 1247-1254. doi:10.1111/jan.14316Liu, W., Wang, Z., & Zhao, H. (2020). Comparative study of customer relationship management research from East Asia, North America and Europe: A bibliometric overview. Electronic Markets, 30(4), 735-757. doi:10.1007/s12525-020-00395-7Cronin, B. (2001). Bibliometrics and beyond: some thoughts on web-based citation analysis. Journal of Information Science, 27(1), 1-7. doi:10.1177/016555150102700101Durieux, V., & Gevenois, P. A. (2010). Bibliometric Indicators: Quality Measurements of Scientific Publication. Radiology, 255(2), 342-351. doi:10.1148/radiol.09090626Guerola Navarro, V., Oltra Badenes, R. F., Gil Gomez, H., & Gil Gomez, J. A. (2020). Customer Relationship Management (CRM): A Bibliometric Analysis. International Journal of Services Operations and Informatics, 10(3), 1. doi:10.1504/ijsoi.2020.10030517Vicedo, P., Gil-Gómez, H., Oltra-Badenes, R., & Guerola-Navarro, V. (2020). A bibliometric overview of how critical success factors influence on enterprise resource planning implementations. Journal of Intelligent & Fuzzy Systems, 38(5), 5475-5487. doi:10.3233/jifs-179639Daim, T. U., Rueda, G., Martin, H., & Gerdsri, P. (2006). Forecasting emerging technologies: Use of bibliometrics and patent analysis. Technological Forecasting and Social Change, 73(8), 981-1012. doi:10.1016/j.techfore.2006.04.004Fersht, A. (2009). The most influential journals: Impact Factor and Eigenfactor. Proceedings of the National Academy of Sciences, 106(17), 6883-6884. doi:10.1073/pnas.0903307106Fu, H.-Z., Wang, M.-H., & Ho, Y.-S. (2013). Mapping of drinking water research: A bibliometric analysis of research output during 1992–2011. Science of The Total Environment, 443, 757-765. doi:10.1016/j.scitotenv.2012.11.061Fu, H., Ho, Y., Sui, Y., & Li, Z. (2010). A bibliometric analysis of solid waste research during the period 1993–2008. Waste Management, 30(12), 2410-2417. doi:10.1016/j.wasman.2010.06.008Wang, H., He, Q., Liu, X., Zhuang, Y., & Hong, S. (2012). Global urbanization research from 1991 to 2009: A systematic research review. Landscape and Urban Planning, 104(3-4), 299-309. doi:10.1016/j.landurbplan.2011.11.006Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact? Scientometrics, 105(3), 1809-1831. doi:10.1007/s11192-015-1645-

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

The value propositions of Smart City Mobility projects

Public city administrators who have been seeking to reduce traffic congestion and pollution, while improving livability and economic competitiveness, via increased investment in promising Smart City (SC) Mobility solutions. However, despite scholarly interest and booming market of solutions and technologies, there is still the need to unlock the value that SC Mobility projects can bring and to understand how these projects define and deliver value. To this end, this study presents an empirical analysis of 300 mobility projects internationally. Projects are scrutinized according to a business model framework and the variety of project characteristics are analyzed. Classification of business modeling characteristics of SC Mobility projects is given, illustrating the main benefits and objectives of smart mobility projects and how such value is generated and distributed among stakeholders. The resulting implications are two-fold. First, it helps scholars with a common business model reference to evaluate SC Mobility projects. Second, it supports the decision-making processes of both public and private organizations and acts as a best practice guide for design and implementation of innovative SC Mobility projects

Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities

Smart cities demand resources for rich immersive sensing, ubiquitous communications, powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of applications, such as public safety, connected and autonomous driving, smart and connected health, and smart living. At the same time, it is widely recognized that vehicles such as autonomous cars, equipped with significantly powerful SCCSI capabilities, will become ubiquitous in future smart cities. By observing the convergence of these two trends, this article advocates the use of vehicles to build a cost-effective service network, called the Vehicle as a Service (VaaS) paradigm, where vehicles empowered with SCCSI capability form a web of mobile servers and communicators to provide SCCSI services in smart cities. Towards this direction, we first examine the potential use cases in smart cities and possible upgrades required for the transition from traditional vehicular ad hoc networks (VANETs) to VaaS. Then, we will introduce the system architecture of the VaaS paradigm and discuss how it can provide SCCSI services in future smart cities, respectively. At last, we identify the open problems of this paradigm and future research directions, including architectural design, service provisioning, incentive design, and security & privacy. We expect that this paper paves the way towards developing a cost-effective and sustainable approach for building smart cities.Comment: 32 pages, 11 figure