CITY FEED: A Crowdsourcing System for City Governance

Crowdsourcing is a valuable social sensing for the smarter city. We present an approach for classifying crowdsourced feeds from a threefold point of view, namely image, text, and geography. The main idea is to extract feeds within a specific geographic range, and then analyze similarity of image color and text semantic. The approach enables to identify feeds that report the same issue, hence filtering redundant information. Based on proved methods and algorithms, such approach has been implemented in a software application, called CITY FEED, that is used by the Municipality of Pavia.

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“…A robust and credible crowdsourcing / social sensing brings various benefits for a smart city, as we already underlined [12]:…”

Section: Discussionmentioning

confidence: 98%

“…CITY FEED, that is a module of a larger smart city project, called IRMA, is developed by our department and runs as a pilot installation in the Municipality of Pavia [11] [12].…”

Section: Introductionmentioning

confidence: 99%

A Threefold Similarity Analysis of Crowdsourcing Feeds

Liu

Motta

You

et al. 2015

2015 International Conference on Service Science (ICSS)

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“…For instance, [5] designed a crowdsourcingbased mobile-healthcare system. The paper [12] is a crowdsourcing-based city governance system. The paper [20] is a crowdsourcing-based system for enterprises.…”

Section: Related Workmentioning

confidence: 99%

“…For instance, in mobile-healthcare systems [5], privacy of transmitted data (personal health information) is the most important requirement, while in city governance systems [12], access control has vital significance. The security requirements of parking reservation systems are different from those of other crowdsourcing-based systems too, as discussed in Section 1.…”

Section: Related Workmentioning

confidence: 99%

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SCPR: Secure Crowdsourcing-Based Parking Reservation System

Wan

Zhang

Huang

2017

Security and Communication Networks

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The crowdsourcing-based parking reservation system is a new computing paradigm, where private owners can rent their parking spots out. Security is the main concern for parking reservation systems. However, current schemes cannot provide user privacy protection for drivers and have no key agreement functions, resulting in a lot of security problems. Moreover, current schemes are typically based on the time-consuming bilinear pairing and not suitable for real-time applications. To solve these security and efficiency problems, we present a novel security protocol with user privacy called SCPR. Similar to protocols of this field, SCPR can authenticate drivers involved in the parking reservation system. However, different from other well-known approaches, SCPR uses pseudonyms instead of real identities for providing user privacy protection for drivers and designs a novel pseudonym-based key agreement protocol. Finally, to reduce the time cost, SCPR designs several novel cryptographic algorithms based on the algebraic signature technique. By doing so, SCPR can satisfy a number of security requirements and enjoy high efficiency. Experimental results show SCPR is feasible for real world applications.

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Smart city big data analytics: An advanced review

Soomro

Bhutta

Khan

et al. 2019

WIREs Data Min & Knowl

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With the increasing role of ICT in enabling and supporting smart cities, the demand for big data analytics solutions is increasing. Various artificial intelligence, data mining, machine learning and statistical analysis-based solutions have been successfully applied in thematic domains like climate science, energy management, transport, air quality management and weather pattern analysis. In this paper, we present a systematic review of the literature on smart city big data analytics. We have searched a number of different repositories using specific keywords and followed a structured data mining methodology for selecting material for the review. We have also performed a technological and thematic analysis of the shortlisted literature, identified various data mining/machine learning techniques and presented the results. Based on this analysis we also present a classification model that studies four aspects of research in this domain. These include data models, computing models, security and privacy aspects and major market drivers in the smart cities domain. Moreover, we present a gap analysis and identify future directions for research. For the thematic analysis we identified the themes smart city governance, economy, environment, transport and energy. We present the major challenges in these themes, the major research work done in the field of data analytics to address these challenges and future research directions.

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CITY FEED: A Crowdsourcing System for City Governance

Cited by 25 publications

References 22 publications

A Threefold Similarity Analysis of Crowdsourcing Feeds

A Threefold Similarity Analysis of Crowdsourcing Feeds

SCPR: Secure Crowdsourcing-Based Parking Reservation System

Smart city big data analytics: An advanced review

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