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According to the COVID-19 lockdown and successive reopening a number of facts can be analysed. The main effects have been detected on: mobility and environment, and specifically on traffic, environmental data and parking. The mobility reduction has been assessed to be quite coherent with respect to what has been described by Google Global mobility report. On the other hand, in this paper a number of additional aspects have been put in evidence providing detailed aspects on mobility and parking that allowed us to better analyse the impact of the reopening on an eventual revamping of the infection, also taking into account of the Rt index. To this end, the collected data from the field have been compared from those of Google and some considerations with respect to the Imperial college Report 20 have been derived. For the pollutant aspects, a relevant reduction on most of them has been measured and rationales are reported. The solution has exploited the Snap4City IOT smart city infrastructure and data collector and Dashboard in place in Tuscany.

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.

In recent years, there is an increasing attention on air quality derived services for the final users. A dense grid of measures is needed to implement services such as conditional routing, alerting on data values for personal usage, data heatmaps for Dashboards in control room for the operators, and for web and mobile applications for the city users. Therefore, the challenge consists of providing high density data and services starting from scattered data and regardless of the number of sensors and their position to a large number of users. To this aim, this paper is focused on providing an integrated solution addressing at the same time multiple aspects: To create and optimize algorithms for data interpolation (creating regular data from scattered), making it possible to cope with the scalability and providing support for on demand services to provide air quality data in any point of the city with dense data. To this end, the accuracy of different interpolation algorithms has been evaluated comparing the results with respect to real values. In addition, the trends of heatmaps interpolation errors have been exploited to detected devices&rsquo, dysfunctions. Such anomalies may often be useful to request a maintenance action. The solution proposed has been integrated as a Micro Services providing data analytics in a data flow real time process based on Node.JS Node-RED, called in the paper IoT Applications. The specific case presented in this paper refers to the data and the solution of Snap4City for Helsinki. Snap4City, which has been developed as a part of Select4Cities PCP of the European Commission, and it is presently used in a number of cities and areas in Europe.

In recent years, there is an increasing attention on Air Quality and derived services. In most cases, the main objective consists in providing services independently on the number of sensors, and on any position of the users. On the other hand, sensors are collected in limited positions, then a dense grid is computed to satisfy the needs of services such as: conditional routing, alerting on data values for personal usage, general heatmap production for Dashboards in control room of the operators, and for web and mobile applications for the city users. The paper formalizes the development process and describes how it is possible to automatically integrate Data Analytics in data flow real time processes, called in the paper IoT Applications. Two interpolation methods have been compared and validated in order to assess the accuracy. Interpolation errors trends have been used to detected devices' dysfunctions on sensors. The specific case presented in this paper refers to the data and the solution of Snap4City for Helsinki. Snap4City (https://www.snap4city.org) has been developed as a part Select4Cities PCP of the European Commission, and it is presently used in a number of cities and areas in Europe.

The main technical issues regarding smart city solutions are related to data gathering, aggregation, reasoning, data analytics, access, and service delivering via Smart City APIs (Application Program Interfaces). Different kinds of Smart City APIs enable smart city services and applications, while their effectiveness depends on the architectural solutions to pass from data to services for city users and operators, exploiting data analytics, and presenting services via APIs. Therefore, there is a strong activity on defining smart city architectures to cope with this complexity, putting in place a significant range of different kinds of services and processes. In this paper, the work performed in the context of Sii-Mobility smart city project on defining a smart city architecture addressing a wide range of processes and data is presented. To this end, comparisons of the state of the art solutions of smart city architectures for data aggregation and for Smart City API are presented by putting in evidence the usage semantic ontologies and knowledge base in the data aggregation in the production of smart services. The solution proposed aggregate and re-conciliate data (open and private, static and real time) by using reasoning/smart algorithms for enabling sophisticated service delivering via Smart City API. The work presented has been developed in the context of the Sii-Mobility national smart city project on mobility and transport integrated with smart city services with the aim of reaching a more sustainable mobility and transport systems. Sii-Mobility is grounded on Km4City ontology and tools for smart city data aggregation, analytics support and service production exploiting smart city API. To this end, Sii-Mobility/Km4City APIs have been compared to the state of the art solutions. Moreover, the proposed architecture has been assessed in terms of performance, computational and network costs in terms of measures that can be easily performed on private cloud on premise. The computational costs and workloads of the data ingestion and data analytics processes have been assessed to identify suitable measures to estimate needed resources. Finally, the API consumption related data in the recent period are presented.

Internet of Things paradigm enables computation and communication in tools that every day everyone uses. The vastness and heterogeneity of devices and the ways they are composed to offer innovative services and scenarios require a challenging vison in interoperability, security and in managing huge quantity of data. Many IoT frameworks and platforms propose to solve these issues, aggregating different sources of information and combine their flow of data in innovative services. Due to the potentially very sensible nature of some of this data, privacy and security aspects have to be taken into account by design and by default. An end-to-end secure solution has to permit the final users to have full control on their personal data and, on the other side, the framework has to support developers in writing applications offering the highest level of security/protection on their data flow. European Commission GDPR also added complexity to this context. In this paper, Snap4City solution to support such level of privacy and security in an IoT scenarios is presented. Snap4City has been developed in the context of Select4Cities PCP project of the European Commission.

Smart Cities are approaching the Internet of Things (IoT) World. Most of the first-generation Smart City solutions are based on Extract Transform Load (ETL), processes and languages that mainly support pull protocols for data gathering. IoT solutions are moving forward to event-driven processes using push protocols. Thus, the concept of IoT applications has turned out to be widespread, but it was initially &ldquo, implemented&rdquo, with ETL, rule-based solutions, and finally, with true data flows. In this paper, these aspects are reviewed, highlighting the requirements for smart city IoT applications and in particular, the ones that implement a set of specific MicroServices for IoT Applications in Smart City contexts. Moreover, our experience has allowed us to implement a suite of MicroServices for Node-RED, which has allowed for the creation of a wide range of new IoT applications for smart cities that includes dashboards, IoT Devices, data analytics, discovery, etc., as well as a corresponding Life Cycle. The proposed solution has been validated against a large number of IoT applications, as it can be verified by accessing the https://www.Snap4City.org portal, while only three of them have been described in the paper. In addition, the reported solution assessment has been carried out by a number of smart city experts. The work has been developed in the framework of the Select4Cities PCP (PreCommercial Procurement), funded by the European Commission as Snap4City platform.

The new IoT/IoE (internet of things/everythings) paradigm and architecture permits to rethink about the way the Smart City infrastructures are designed and managed, on the other hand a number of problems have to be solved. In terms of mobility the cities that embrace the sensoring era can take advantage of this disruptive technology to improve the quality of life of their citizen, also thanks the rationalization in the use of their resources. In Sii-Mobility, a national smart city project on mobility and transportation, a flexible platform has been designed and here, in this paper, is presented. It permits to setup heterogeneous and complex scenarios that integrate sensors/actuators as IoT/IoE in an overall scenario of Big Data, Machine Learning and Data Analytics. A detailed and complex case-study has been presented to validate the solution in the context of a system that dynamically reverse the traveling direction of a road segment, with all the safety conditions in place. This case study composes several building blocks of the IoT platform, which demonstrate that a flexible and dynamic set-up is possible, supporting off-grid, security, safety, cloud and mixed solutions.

The new challenges in the smart city context are mainly related to the stimulation of the city users towards taking more sustainable behaviors, in mobility and energy. The state of the art in this case is mainly focused on classical smart city solution for informing the city users and or for engaging them with specific wired rules toward virtuous models. And not using flexible languages and predictive models, pushing them towards a larger range of virtuous habits. On this regards, the main problems are the computation of user behavior via data analytic (semantic computing, machine learning), as well as the formalization of strategies via simple and well formalized language for producing engagements to the city users, which can be understood by city operators. In this paper, a solution for city users engagement is studied and implemented for Sii-Mobility Smart city national project in Italy has been presented. The solution has been implemented thanks to the exploitation of Km4City model and semantic computing. The paper also presents the validation of results about the effective usage of the solution by providing some statistical evidence about the efficient assessment of user behavior and of engagement rules acceptance rate.

The Web is rapidly becoming the prime medium for human socialization. As it evolves towards an information-centric operation, it records everything and forgets nothing, assuming that every online resource disclosed by people (photos, posts, multimedia files, etc.) is permanently valid and is to be stored forever. However, throughout their lives, people tend to change, both in their habits as well as in their views and opinions. In many situations, as the years go by, information released loses relevance or people may decide they no longer want others to access information they have previously published. The work presented in this paper strives for a new information persistence paradigm, whereby the enforcement of "digital forgetting" is implemented over an information-centric model for the Internet. The defined solution enables the definitive elimination of digital objects, either on-demand or on a pre-scheduled basis, and, hence, their "forgetting." The solution, conceived within the framework of the European project CONVERGENCE, is based on the employment of metadata descriptions about resources, which unambiguously identify their rightful owners. This additional data is efficiently bound to the resource through the use of an extended version of the MPEG- 21 Digital Item specification, and its prescriptions are enforced by CONVERGENCE's distributed provisions.

The Web is rapidly becoming the prime medium for human socialization. The resources that enable that process (social web sites, blogs, media objects, etc.) present growing complexity and, collectively, weave an ever more intricate web of relationships. Current technology for declaring those relationships is predominantly implicit, ambiguous and semantically poor. As a consequence, their automatic assessment is complex and error prone, preventing the satisfaction of users' needs such as effective semantic searches. To address these limitations, whilst enabling the explicit declaration of semantically unambiguous relationships between digital resources, a solution employing structured semantic descriptors and ontologies was conceived, based on MPEG-21. This paper explains the functioning of the devised mechanism, and goes beyond that, into the definition of two novel employment venues for it, at the service of two real-world usage scenarios. These demonstrate the mechanism's added value as a powerful alternative for the semantically aware interconnection of web resources, and highlight the increased QoE that said mechanism enables.

This chapter provides the definition of the Versatile Digital Item, the basic unit for data distribution used within the CONVERGENCE system. It explains how the VDI builds on, and extends the scope, of the MPEG-21 Digital Item to build a self-contained data package that can be used to encapsulate any kind of digital information in an information-centric, publish-subscribe framework. This chapter details some of the most relevant aspects pertaining to the structure of the VDI, its identification, its connection into sequences, and its logical interweaving into a fabric of inter-VDI relationships. It also explores some implications of the above aspects on the system’s operations.

This chapter describes CONVERGENCE’s licensing scheme and its governance, based on the MPEG-21 part 5 standard and on the specific content protection and rights management requirements, identified in the CONVERGENCE use scenarios. In the digital media value chain, Rights Expression Languages (RELs) are used to enable controlled access to digital resources, addressing several different issues from the description of licenses to access and usage control, payments, etc. A REL is an essential component of any security infrastructure supporting differentiated controlled access to digital resources, and providing adequate protection of intellectual property rights. Among these, the project has selected the MPEG-21 part 5 open standard, which can be implemented in XML, and is one of the main current contenders for a general-purpose REL. Our scheme is designed in the light of CONVERGENCE’s ability to distribute and manage any kind of digital resource in a large distributed environment, and this chapter explains how REL data is embedded into the CONVERGENCE data unit, the Versatile Digital Item (VDI) and introduces a basic set of security features, based on digital certificates, for the enforcement of the rights and conditions expressed in CONVERGENCE licenses.

This chapter provides the description of the overall architecture of the content level of convergence: the CONVERGENCE Middleware (CoMid). The chapter starts with the presentation of the MPEG-M standard, which provides the foundations for CoMid, then proceeding with a complete description of this architectural level. The key components of the Content level comprise a diversified set of middleware engines to manipulate Versatile Digital Items (VDIs), a Community Dictionary Service (CDS) and a Semantic Overlay. The set of middleware engines were partially borrowed and/or adapted from MPEG-M and partially designed and developed from scratch within CONVERGENCE, adopting the same design principles. The CDS and the Semantic Overlay, newly designed and developed by CONVERGENCE, when used together with the middleware engines, enable the semantic, content-based, publish-subscribe functionality of the platform.

This paper introduces a suitable way for indexing multimedia metadata on a structured peer-to-peer overlay network, with special care to the management of rights metadata expressed by MPEG-21. We have selected a suitable subset of MPEG-21 rights expression language elements to be indexed, in order to map governed contents into a flat space and allow insertion and retrieval of digital contents. Furthermore, we present a distributed application built on a structured overlay network enabling the search of multimedia items using rights related information. Our solution is completely decentralized and can be exploited in any MPEG-21 compliant metadata representation.

This chapter presents the recommendation techniques applied in Personal Program Guide (PPG). This is a system generating personalized Electronic Program Guides for Digital TV. The PPG manages a user model that stores the estimates of the individual user’s preferences for TV program categories. This model results from the integration of different preference acquisition modules that handle explicit user preferences, stereotypical information about TV viewers, and information about the user’s viewing behavior. The observation of the individual viewing behavior is particularly easy because the PPG runs on the set-top box and is deeply integrated with the TV playing and the video recording services offered by that type of device.

The modern mobile phones and the complete digitalization of the public and private transport networks have allowed to access useful information to understand the user’s mean of transportation. This enables a plethora of old and new applications in the fields of sustainable mobility, smart transportation, assistance, and e-health. The precise understanding of the travel means is at the basis of the development of a large range of applications. In this paper, a number of metrics has been identified to understand whether an individual on the move is stationary, walking, on a motorized private or public transport, with the aim of delivering to city users personalized assistance messages for: sustainable mobility, health, and/or for a better and enjoyable life, etc. Differently from the state-of-the-art solutions, the proposed approach has been designed to provide results, and thus collect metrics, in real operating conditions (imposed on the mobile phones as: a range of different mobile phone kinds, operating system constraints managing Applications, active battery consumption manager, etc.). The paper reports the whole experimentations and results. The solution has been developed in the context of Sii-Mobility Km4City Research Project infrastructure and tools, performed with the collaboration of public transport operators, and GDPR compliant. The same solution has been used in Snap4City mobile Apps with experiments performed in Antwerp and Helsinki.

This paper presents the recommendation techniques applied in Personal Program Guide (PPG), a system generating personalized Electronic Program Guides for digital TV. The PPG recommends TV programs by relying on the integration of heterogeneous user modeling techniques.