research-article

Using smartphones for prototyping semantic sensor analysis systems

Authors:

Hassan Issa,

Ludger van Elst,

Andreas DengelAuthors Info & Claims

SBD '16: Proceedings of the International Workshop on Semantic Big Data

Article No.: 7, Pages 1 - 6

https://doi.org/10.1145/2928294.2928299

Published: 26 June 2016 Publication History

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Abstract

The increasing usage of sensors in modern technical systems and in consumer products necessitates using efficient and scalable methods for storing and processing sensor data. Coupling big data technologies with semantic techniques not only helps achieving the desired storage and processing goals, but also facilitates data integration, data analysis and the utilization of data in unforeseen future applications through preserving the data generation context. In this work, an approach for prototyping semantic sensor analysis systems using Apache Spark is proposed. The approach uses smartphones to generate sensor data which is transformed into semantic data according to the Semantic Sensor Network ontology. Efficient storage and processing methods of semantic data are proposed and a use case where a smartphone is deployed in a transportation bus is presented along with a street anomaly detection application.

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Cited By

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Zhang YHu ZLin JZhang J(2021)Linking data model and formula to automate KPI calculation for building performance benchmarkingEnergy Reports10.1016/j.egyr.2021.02.0447(1326-1337)Online publication date: Nov-2021
https://doi.org/10.1016/j.egyr.2021.02.044
Shimoda KDiefenbach DSingh KTaya ATobe YMaret P(2020)RW-QAnswer: an assisting system for intelligent environments using semantic technologyJournal of Reliable Intelligent Environments10.1007/s40860-020-00112-3Online publication date: 1-Oct-2020
https://doi.org/10.1007/s40860-020-00112-3
Muppalla RLalithsena SBanerjee TSheth AFox PMcGuinness DPoirer LBoldi PKinder-Kurlanda K(2017)A Knowledge Graph Framework for Detecting Traffic Events Using Stationary CamerasProceedings of the 2017 ACM on Web Science Conference10.1145/3091478.3162384(431-436)Online publication date: 25-Jun-2017
https://dl.acm.org/doi/10.1145/3091478.3162384

Index Terms

Using smartphones for prototyping semantic sensor analysis systems
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Ontology engineering
      2. Semantic networks
2. Information systems
  1. Information storage systems
    1. Storage architectures
      1. Distributed storage

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SBD '16: Proceedings of the International Workshop on Semantic Big Data

June 2016

83 pages

ISBN:9781450342995

DOI:10.1145/2928294

Conference Chairs:
Sven Groppe
University of Lübeck, Germany
,
Le Gruenwald
University of Oklahoma

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 26 June 2016

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SIGMOD/PODS'16: International Conference on Management of Data

June 26 - July 1, 2016

California, San Francisco

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Zhang YHu ZLin JZhang J(2021)Linking data model and formula to automate KPI calculation for building performance benchmarkingEnergy Reports10.1016/j.egyr.2021.02.0447(1326-1337)Online publication date: Nov-2021
https://doi.org/10.1016/j.egyr.2021.02.044
Shimoda KDiefenbach DSingh KTaya ATobe YMaret P(2020)RW-QAnswer: an assisting system for intelligent environments using semantic technologyJournal of Reliable Intelligent Environments10.1007/s40860-020-00112-3Online publication date: 1-Oct-2020
https://doi.org/10.1007/s40860-020-00112-3
Muppalla RLalithsena SBanerjee TSheth AFox PMcGuinness DPoirer LBoldi PKinder-Kurlanda K(2017)A Knowledge Graph Framework for Detecting Traffic Events Using Stationary CamerasProceedings of the 2017 ACM on Web Science Conference10.1145/3091478.3162384(431-436)Online publication date: 25-Jun-2017
https://dl.acm.org/doi/10.1145/3091478.3162384

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Exploitation of ontological approaches in Big Data: A State of the Art

A Spark-Based Big Data Platform for Massive Remote Sensing Data Processing

Piglet: Interactive and Platform Transparent Analytics for RDF & Dynamic Data

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