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Semantic Modelling of Smart City Data

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TLDR
Examples of data that can be collected from cities are presented, issues around this data are discussed, and some preliminary thoughts for creating a semantic description model to describe and help discover, index and query smart city data are put forward.
Abstract
Recent advancements in communication technologies for providing ubiquitous Internet access as well as advancements on reduction of cost and form-factor of mobile devices and sensors are seen as an enabler for the Internet of Things (IoT). The industry predicts an interconnected world of 50 billion devices by 20201. The Web of Things (WoT) relies on the connectivity service of IoT to create services and applications exploiting the IoT data [1]. Cities present an opportunity for rendering WoT-enabled services. According to the World Health Organization, population in cities will double by the middle of this century2, while cities deal with increasingly pressing issues such as environmental sustainability, economic growth and citizen mobility. In this paper, we propose a discussion around the need for common semantic descriptions for smart city data to facilitate future services in “smart cities”. We present examples of data that can be collected from cities, discuss issues around this data and put forward some preliminary thoughts for creating a semantic description model to describe and help discover, index and query smart city data.

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Citations
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Journal ArticleDOI

Urban planning and building smart cities based on the Internet of Things using Big Data analytics

TL;DR: A combined IoT-based system for smart city development and urban planning using Big Data analytics, consisting of various types of sensor deployment, including smart home sensors, vehicular networking, weather and water sensors, smart parking sensors, and surveillance objects is proposed.
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Exploiting IoT and big data analytics: Defining Smart Digital City using real-time urban data

TL;DR: This paper has established an IoT-based Smart City by using Big Data analytics while harvesting real-time data from the city by using existing smart systems and IoT devices as city data sources to develop the Smart Digital City.
Book ChapterDOI

CityBench: A Configurable Benchmark to Evaluate RSP Engines Using Smart City Datasets

TL;DR: Performance, correctness and technical soundness of few existing RSP engines have been evaluated in controlled settings using existing benchmarks like LSBench and SRBench, but these benchmarks focus merely on features of the RSP query languages and engines and do not consider dynamic application requirements and data-dependent properties.
Journal ArticleDOI

Towards Disaster Resilient Smart Cities: Can Internet of Things and Big Data Analytics Be the Game Changers?

TL;DR: The proposed architecture offers a generic solution for disaster management activities in smart city incentives and the evaluation of the system efficiency is measured in terms of processing time and throughput that demonstrates the performance superiority of the proposed architecture.
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SMART TSS: Defining transportation system behavior using big data analytics in smart cities

TL;DR: This work proposes a big data analytics architecture for Intelligent Transportation Systems (ITS), which has a built-in storage and analysis capability to work with ITS data and is composed of four modules, namely (1) Big Data Acquisition and Preprocessing Unit (2)Big Data Processing Unit (3) Big data Analytics Unit and (4) Data Visualization Unit.
References
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From Data to Actionable Knowledge: Big Data Challenges in the Web of Things [Guest Editors' Introduction]

TL;DR: The guest editors describe the Big Data issues in the WoT, discuss the challenges of extracting actionable knowledge and insights from raw sensor data, and introduce the theme articles in this special issue.
Proceedings ArticleDOI

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TL;DR: This paper describes a semantic modelling scheme, a naming convention and a data distribution mechanism for sensor streams, and demonstrates an annotation and data distribution framework and evaluates the solutions with a set of sample datasets.
Proceedings ArticleDOI

The web of things

TL;DR: The aim is to show how small devices can be connected to the Web at various levels of abstraction and transform them into "first-class" Web residents.
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