**4. Discussion**

The perspective of implementing sensor cities based on IoT and on different urban technologies that permit the collection, monitoring, analysis and integration of large amounts of urban data has developed new opportunities for policymakers regarding the ability to plan, combine and evaluate social, environmental and economic aspects in a holistic manner [34,158,159].

The expansion of urban technologies has stimulated local authorities, technology companies, start-ups, citizens, municipal companies, and other actors involved, to develop increasingly innovative and sophisticated projects, devices, platforms, algorithms, systems, initiatives, and so on, especially in technologically and ecologically developed cities. Consequently, the use of advanced techniques such as real-time monitoring stations for energy consumption, location systems to guide urban traffic, cloud computing systems for sharing sensitive data between governmen<sup>t</sup> departments, urban infrastructures such as smart bins, smart street lamps, and surveillance cameras, have grea<sup>t</sup> potential in transforming the way we understand and evaluate the urban context and, at the same time, highlight a multitude of challenges related to the quality of the data used, the level of protection of traditional and cybernetic

urban security, the necessary data integration between the various urban infrastructures and the ability to transform feedback from citizens and other stakeholders into innovative urban policies (Figure 8). In that perspective, sensor cities represent a sophisticated paradigm shift in the concept of the technical-urban context, necessary for a transition towards disruptive urban development [160–162].

**Figure 8.** Future urban data challenges (source: authors).

The first challenge refers to the development of innovative urban policies in line with the needs of citizens, local authorities, companies, organizations, and so on. Hence, to use a significant amount of urban data according to the needs of the stakeholders involved, it is necessary to identify the relevant information and understand its consistency and validity. For example, in a survey, citizens of the well-known German tourist destination, Heidelberg, identified traffic as the most urgen<sup>t</sup> issue to be solved. In this sense, the efforts of local policymakers have been focused on how to improve urban mobility. Thus, the identification, collection and processing of information provided by the actors involved are crucial in the development of urban sensor projects [163–165].

The second challenge concerns the need to guarantee a certain level of data quality in order to develop efficient and innovative urban policies. For example, data collection sensors can produce incorrect, partial or missing values as they use different standards or protocols, generating inconsistencies and differences between the data. For example, CityPulse described by Puiu et al. [166] is a real-time monitoring framework supported by the European Union (EU) that processes, integrates and adapts uncertain and incomplete data through quality of information techniques in order to develop reliable information capable of satisfying user requests. In this regard, the urban project represents a practical model of how to move from vertically to horizontally interconnected services [167].

Cities with concentrated IoT and sensor networks may provide unreliable communications due to incorrect data transmission. Specifically, the incorrect transmission of urban data does not only require time, but also retransmits the information flow, which negatively affects the quality of the data [168]. As a result, the quality of data and the technologies to overcome problems of inconsistency, partiality, and unreliability should be considered in the development and implementation of sensor city projects [169,170].

The third challenge concerns the integration of different types of data, collected, processed and analyzed by different institutions, companies and/or independent authorities. One of the main tasks of public decision-makers, and urban managers, planners, and policymakers is to implement infrastructures, models, and networks capable of connecting data deriving from different urban sectors, promoting better communication between the various stakeholders involved [171]. For example, the dashboard implemented by Alibaba, illustrated in Figure 5, requires an information flow and a

systemic communication between government, security and emergency service institutions. Hence, the holistic combination of data is necessary to plan and better understand the potential of sensor cities.

The fourth challenge involves the security of sensitive data. In this regard, ensuring maximum privacy protection is indispensable for developing urban policies based on sensors, video surveillance cameras, monitoring stations, cloud computing, and so on. Data security issues not only have isolated effects, but also often a ffect all the urban dimensions (analyzed in the previous section). Thus, data security is treated as a fundamental issue in the managemen<sup>t</sup> of sensor cities [172–174]. Through the collection and use of large amounts of data and technological solutions that analyze human behavior, it is possible to influence not only the fight against crime through sensors that analyze movements or facial expressions, but also urban governance in terms of planning and the attractiveness of the city [175–177]. Nonetheless, the corresponding interventions are particularly controversial in terms of privacy, emphasizing ethical requirements in the urban safety planning process [178,179]. Therefore, integrating the problems related to traditional and cybernetic urban security into the planning and implementation projects of sensor cities is necessary to guarantee safe and digitalized urban development [180,181].

The challenges explained in this section are related because the collection, processing and analysis of data through IoT solutions, sensors and big data analysis refer to interdependent urban dimensions (e.g., governance, environment, mobility, economy, life and people). Nevertheless, this perspective requires a change in the structural paradigm of technical-scientific skills, greater organizational flexibility of governmen<sup>t</sup> institutions and a more aware and involved citizenship in the urban administration.
