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Making cities smart represents a major potential for sustainable development, where both the quality of life and the economy improve. Implementing new and efficient solutions in a smart city involves a large spectrum of uncertainties related to the size and project complexity. Characterization and assessment of the variables uncertainty in planning methodology seem necessary to reach the best decision about the best approach to achieve favorable realization outcomes for planned projects. By including uncertainties in the planning, assessment makes it possible to calculate result uncertainties for all expectations, and project cost-effectiveness. In this way, planning can be improved, if the most important parameters of result uncertainties are identified, better defined, and controlled. This study describes a parameter uncertainty characterization methodology applied on the cost-benefit analysis of smart city development with a case study, focused on smart metering infrastructure. Parameter uncertainty characterization is performed based on its variable nature (epistemic and aleatory), time-dependency, and the available information. Cost-benefit analysis results are given as both point value and as uncertainties. Uncertainty is considered for 25 variables of investment and operating costs, and benefits estimation. The presented methodology in smart city planning provides a way to better identify the critical parameters for achieving the defined objectives.

Characterization of Uncertainties in Smart City Planning: A Case Study of the Smart Metering Deployment