Graph Representation of Linear Infrastructure in Smart City IoT Systems

Author(s):  
Michal Gorawski ◽  
Krzysztof Grochla
2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Michał Gorawski ◽  
Krzysztof Grochla

Abstract The infrastructure managed by Smart City systems includes mainly linear structures, such as pipelines, electric power lines, railway lines, etc.. In this paper, we propose the transcription of linear infrastructure to graph representation and storing needed meta-data in a graph database, merged with the traditional relational database used for device management. Such an approach enables fast acquisition of data about infrastructure’s properties and allows merging information about the structure of the managed infrastructure with information devices’ properties and statistics. We develop a graph generator that generates virtual network basing on representative examples of linear infrastructure, incorporation of a data from existing metering systems with the generated structure, which automates the deployment and allows to evaluate the performance of Smart City monitoring and management system. We present results of performance tests that show and the creation time of graph database structures in Neo4j and the difference between the performance of the Microsoft SQL Server database and the Neo4j database in a few Smart City use cases. The results show that the use of the graph database to execute queries related to linear infrastructure allows decreasing the response time up to 9 times.


Author(s):  
Rosaria Battarra ◽  
Carmela Gargiulo ◽  
Rosa Anna la Rocca ◽  
Laura Russo
Keyword(s):  

2015 ◽  
Vol 33 ◽  
pp. 35-39
Author(s):  
Donatella De Rita
Keyword(s):  

Author(s):  
Jin-Woo Hyun ◽  
◽  
Kyung-Sun Yoo ◽  
Dong-Hoon Hyun ◽  
Chang-kyu Kim
Keyword(s):  

2018 ◽  
pp. 60-67
Author(s):  
Henrika Pihlajaniemi ◽  
Anna Luusua ◽  
Eveliina Juntunen

This paper presents the evaluation of usersХ experiences in three intelligent lighting pilots in Finland. Two of the case studies are related to the use of intelligent lighting in different kinds of traffic areas, having emphasis on aspects of visibility, traffic and movement safety, and sense of security. The last case study presents a more complex view to the experience of intelligent lighting in smart city contexts. The evaluation methods, tailored to each pilot context, include questionnaires, an urban dashboard, in-situ interviews and observations, evaluation probes, and system data analyses. The applicability of the selected and tested methods is discussed reflecting the process and achieved results.


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