Smart cities can be viewed as complex adaptive systems that can be described by the theory of entropy and the theory of complexity, and the given models can be applied to evaluate the management of Smart cities. Smart cities function as datasets-driven organizations enabled by open datasets frameworks and IoT sensor networks. This chapter proposes an entropy-based framework to evaluate smart city efficiency in European cities. In this way of evaluating management, one of the big problems is the problem of datasets visualization and the way datasets are presented to either human or industrial users. The regulatory framework for the use of smart materials is still emerging, and, in most cases—at least in the EU—it is oriented toward the ethical application of artificial intelligence. For turning datasets into insights and insights as a basis for action (actions based on insights), digital twin models were developed, geospatial tools are used to link certain measurable datasets from the environment with the location of origin for easier understanding and management, and defined triggers are used for initiation of adequate management actions. The security analysis shows that cybersecurity will play an increasingly important role in the management of cities. The text verifies and defines the best world practice in the field and evaluates the efficiency of datasets processing methods in smart cities.