ABSTRACT. Empirical evidence on computationally networked urbanism and advanced sustainability analytics in Internet of Things-enabled smart city governance has been scarcely documented in the literature. Using and replicating data from China Unicom, CompTIA, Deloitte, ESI ThoughtLab, ICMA, KPMG, Philips, PTI, SCC, SmartCitiesWorld, and The University of Adelaide, I performed analyses and made estimates regarding how smart sustainable city governance and management develop on Internet of Things sensing infrastructures by use of sensor-based big data applications. Sensor-based big data applications harness data-driven planning technologies, machine learning-based analytics, and Internet of Things sensing infrastructures, and thus smart cities manage data by leveraging machine learning-based analytics. Networked and integrated sustainable urban technologies deploy interconnected sensor networks, data-driven Internet of Things systems, and urban big data analytics to optimize smart sustainable city governance and management. Descriptive statistics of compiled data from the completed surveys were calculated when appropriate.

Keywords: sustainability; Internet of Things; network; urban; smart city; governance

How to cite: Mulligan, K. (2021). “Computationally Networked Urbanism and Advanced Sustainability Analytics in Internet of Things-enabled Smart City Governance,” Geopolitics, History, and International Relations 13(2): 121–134. doi: 10.22381/GHIR13220219.

Received 18 June 2021 • Received in revised form 4 October 2021
Accepted 9 October 2021 • Available online 10 October 2021