Big Data-driven Urban Geopolitics, Interconnected Sensor Networks, and Spatial Cognition Algorithms in Smart City Software Systems
Thomas Mitchell, Tomas KrulickyABSTRACT. This paper analyzes the outcomes of an exploratory review of the current research on big data-driven urban geopolitics, interconnected sensor networks, and spatial cognition algorithms in smart city software systems. The data used for this study was obtained and replicated from previous research conducted by Capgemini, City of Sydney, ESI ThoughtLab, and KPMG. We performed analyses and made estimates regarding how smart cities integrate groundbreaking wireless sensors, big data, and sustainable technologies. Networked and integrated sustainable urban technologies store and transmit significant quantities of sensing data. Data-driven planning technologies and sensor-based big data applications articulate the smart infrastructure of urban governance. Data collected from 5,800 respondents are tested against the research model. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.
Keywords: smart; city; interconnected; sensor; network; system
How to cite: Mitchell, T., and Krulicky, T. (2021). “Big Data-driven Urban Geopolitics, Interconnected Sensor Networks, and Spatial Cognition Algorithms in Smart City Software Systems,” Geopolitics, History, and International Relations 13(2): 9–22. doi: 10.22381/GHIR13220211.
Received 10 June 2021 • Received in revised form 5 October 2021
Accepted 7 October 2021 • Available online 10 October 2021