A Commentary: Urban Resilience Through Cognitive Computing Systems

Figures & data

Table 1. Types of systems

Type	Purpose	Mechanisms
Engagement	Collaborating and coordinating activities	Touch, gesturing, speech, and writing
Production	Creating products and services	Standard operating procedures to increase efficiency and product consistency
Framing	Justifying the reason for behaving in a particular way or promoting a particular opinion	The use of mental models to focus discussion, justify a viewpoint, and generalize knowledge
Inquiry	Generating knowledge	Use of replicable methods to justify or validate an inference
Record	Recording and retrieving data	Tables, ledgers, and written reports

Source: Watson, 2021

Figure 1. Framework to mitigate UHI through cognitive computing systems

Table 2. Future research guide

	Social	Environment	Economic	Study suggestion	Key approach
Engagement	RQ1: What types of CCSs effectively engage community leaders in reducing UHI?	RQ2: How can a CCS nudge residents toward more sustainable behaviors?	RQ3: How can a CCS inform investors about the losses due to UHI?	Implement system dynamics and agent-based simulations to analyze the overall behavior of urban systems and interactions of individual agents	Establish intelligent communication systems that disseminate critical information effectively
Production	RQ4: How do we introduce CCS-driven procedures to alert urban planners to social vulnerabilities?	RQ5: How do we introduce CCS-driven procedures to address urban design problems?	RQ6: How do we introduce CCS-driven procedures to alert urban planners to economic vulnerabilities?	Perform action design research to improve knowledge dissemination through CCS-driven procedures for urban planning	Create digital solutions by integrating a CCS into a cohesive platform fostering collaboration among stakeholders
Framing	RQ7: How can a CCS be used to design policies to justify distributive energy justice?	RQ8: What form of a CCS will help residents identify practical actions for reducing UHI?	RQ9: How do we create a CCS that enables key stakeholders to understand sustainable urban planning possibilities and reduce intergenerational discounting?	Conduct experimental studies to evaluate the effectiveness of CCS implementation for urban policy and technology interventions	Develop policies to enhance CCS implementation into existing and new urban resilience frameworks
Inquiry	RQ10: How can we design a CCS to identify social vulnerabilities?	RQ11: How can UHI modelling be improved with a CCS?	RQ12: What type of CCS would nudge urban planners and investors to lower UHI outcomes?	Undertake data mining studies for predictive modelling based on historical and real-time data	Identify vulnerable areas and analyze UHI trends and consumption patterns
Record	RQ13: What demographic and psychographic data are needed to build a CCS?	RQ14: What data does a CCS require to estimate UHI environmental outcomes?	RQ15: What economic and natural capital data are needed to build a CCS?	Execute big data analytics to provide a structured and organized representation of relevant data for CCS integration	Apply database management, systems design and implementation, and data analytics for integrated CCS functionality and performance

R. T. Watson, Capital, Systems, and Objects: The Foundation and Future of Organizations (Singapore: Springer, 2021).

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