Towards cloud based big data analytics for smart future cities
By Zaheer Abbas Khan, Ashiq Anjum, Kamran Soomro, Muhammad Atif Tahir. Journal of Cloud Computing, 2015
344 citations recorded by the source corpus.
A large amount of land-use, environment, socio-economic, energy and transport data is generated in cities. An integrated perspective of managing and analysing such big data can answer a number of science, policy, planning, governance and business questions and support decision making in enabling a smarter environment. This paper presents a theoretical and experimental perspective on the smart cities focused big data management and analysis by proposing a cloud-based analytics service. A prototype has been designed and developed to demonstrate the effectiveness of the analytics service for big data analysis. The prototype has been implemented using Hadoop and Spark and the results are compared. The service analyses the Bristol Open data by identifying correlations between selected urban environment indicators. Experiments are performed using Hadoop and Spark and results are presented in this paper. The data pertaining to quality of life mainly crime and safety & economy and employment was analysed from the data catalogue to measure the indicators spread over years to assess positive and negative trends.
Subfields: Computer Networks and Communications, Media Technology, Transportation
View Paper: https://www.semanticscholar.org/paper/adf0daa3c4f5e21de8e98ce86dbc6b3d7d299a2d
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Citations in the corpus
- Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges (2017, background): “It can also assist in improving collaboration and communication among various objects in a smart city [9].”
- IoT in Smart Cities: A Survey of Technologies, Practices and Challenges (2021, methodology): “For more complex decision making, the availability of the cloud allows not only for heterogeneous data gathering/storage and processing but also analysis through the use of statistical methods as well as machine and Deep Learning algorithms in real-time [15].”
- A novel big data analytics framework for smart cities (2019, background): “In [39, 32, 40] authors introduced various design scheme based on Spark over Hadoop for real-time data analytics.”
- Internet of Things (IoT) and the Energy Sector (2020, background): “These features of cloud computing enables the big data resulted from the growing applications of IoT to be easily analyzed, controlled and sorted efficiently [109].”
- Big Data Meet Green Challenges: Big Data Toward Green Applications (2016, background): “[87] presented a theoretical perspective on the smart cities with the emphasis”
- Smart governance in the context of smart cities: A literature review (2018, background): “through new technologies by connecting people to places in smart city contexts (Khan et al., 2015).”