In recent years, smart cities have been significantly developed and have greatly expanded their potential. In fact, novel advancements to the Internet of things (IoT) have paved the way for new possibilities, representing a set of key enabling technologies for smart cities and allowing the production and automation of innovative services and advanced applications for the different city stakeholders. This paper presents a review of the research literature on IoT-enabled smart cities, with the aim of highlighting the main trends and open challenges of adopting IoT technologies for the development of sustainable and efficient smart cities. This work first provides a survey on the key technologies proposed in the literature for the implementation of IoT frameworks, and then a review of the main smart city approaches and frameworks, based on classification into eight domains, which extends the traditional six domain classification that is typically adopted in most of the related works.

The Internet of Things (IoT) paradigm enables computation and communication among tools that everyone uses daily. The vastness and heterogeneity of devices and their composition offer innovative services and scenarios that require a new challenging vision in interoperability, security and data management. Many IoT frameworks and platforms claimed to have solved these issues, aggregating different sources of information, combining their data flows in new innovative services, providing security robustness with respect to vulnerability and respecting the GDPR (General Data Protection Regulation) of the European Commission. Due to the potentially very sensible nature of some of these data, privacy and security aspects have to be taken into account by design and by default. In addition, an end-to-end secure solution has to guarantee a secure environment at the final users for their personal data, in transit and storage, which have to remain under their full control. In this paper, the Snap4City architecture and its security solutions that also respect the GDPR are presented. The Snap4City solution addresses the full stack security, ranging from IoT Devices, IoT Edge on premises, IoT Applications on the cloud and on premises, Data Analytics, and Dashboarding, presenting a number of integrated security solutions that go beyond the state of the art, as shown in the platform comparison. The stress test also included the adoption of penetrations tests verifying the robustness of the solution with respect to a large number of potential vulnerability aspects. The stress security assessments have been performed in a piloting period with more than 1200 registered users, thousands of processes per day, and more than 1.8 million of complex data ingested per day, in large cities such as Antwerp, Helsinki and the entire Tuscany region. Snap4City is a solution produced in response to a research challenge launched by the Select4Cities H2020 research and development project of the European Commission. Select4Cities identified a large number of requirements for modern Smart Cities that support IoT/IoE (Internet of Things/Everything) in the hands of public administrations and Living Labs, and selected a number of solutions. Consequently, at the end of the process after 3 years of work, Snap4City has been identified as the winning solution.

The specification of reactive and real-time systems must be supported by formal, mathematically-founded methods in order to be satisfactory and reliable. Temporal logics have been used to this end for several years. Temporal logics allow the specification of system behavior in terms of logical formulas, including temporal constraints, events, and the relationships between the two. In the last ten years, temporal logics have reached a high degree of expressiveness. Most of the temporal logics proposed in the last few years can be used for specifying reactive systems, although not all are suitable for specifying real-time systems. In this paper we present a series of criteria for assessing the capabilities of temporal logics for the specification, validation, and verification of real-time systems. Among the criteria are the logic's expressiveness, the logic's order, presence of a metric for time, the type of temporal operators, the fundamental time entity, and the structure of time. We examine a selection of temporal logics proposed in the literature. To make the comparison clearer, a set of typical specifications is identified and used with most of the temporal logics considered, thus presenting the reader with a number of real examples.

Looking for available parking slots has become a serious issue in contemporary urban mobility. The selection of suitable car parks could be influenced by multiple factors—e.g., the walking distance to destination, driving and waiting time, parking prices, availability, and accessibility—while the availability of unused parking slots might depend on parking location, events in the area, traffic flow, and weather conditions. This paper presents a set of metrics and techniques to predict the number of available parking slots in city garages with gates. With this aim, we have considered three different predictive techniques, while comparing different approaches. The comparison has been performed according to the data collected in a dozen of garages in the area of Florence by using Sii-Mobility National Research Project and Km4City infrastructure. The resulting solution has demonstrated that a Bayesian regularized neural network exploiting historical data, weather condition, and traffic flow data can offer a robust approach for the implementation of reliable and fast predictions of available slots in terms of flexibility and robustness to critical cases. The solution adopted in a Smart City Apps in the Florence area for sustainable mobility has been welcomed with broad appreciation or has been praised as successful.

Many software systems built in recent years have been developed using object-oriented technology and, in some cases, they already need adaptive maintenance in order to satisfy market and customer needs. In most cases, the estimation and prediction of maintenance effort is performed with difficulty due to the lack of metrics and suitable models. In this paper, a model and metrics for estimation/prediction of adaptive maintenance effort are presented and compared with some other solutions taken from the literature. The model proposed can be used as a general approach for adopting well-known metrics (typically used for the estimation of development effort) for the estimation/prediction of adaptive maintenance effort. The model and metrics proposed have been validated against real data by using multilinear regression analysis. The validation has shown that several well-known metrics can be profitably employed for the estimation/prediction of maintenance effort.