Nowadays, the world is rapidly moving toward a digital paradigm. Big companies have transposed such change and are promptly applying a Digital Transformation process that represents, anyway, a very difficult goal for small and medium-sized enterprises. In this paper a cloud based and collaborative platform for a wide and rapid development and deploy of artificial intelligence applications is proposed. The platform enables SMEs to embrace AI capabilities in a fast and affordable way making them enough competitive in the current business landscape.

The modern age of Big Data, mostly leveraged by the consolidation of the IoT paradigm, leads to the need of giving meaning to the great amount of data, especially within the smart city. It is fundamental to extract value from the information we all are submerged in, thus motivating and supporting the decisions within our cities, which nowadays need transparency and practical evidence. Data visualization tools provide multiple perspectives and are meant to support decision makers, mining available data, with the help of graphical representations in order to ease the emersion of added value, as an initial point from which making inference, reasoning and simulation within our urban environments. And nonetheless, good data visualization provide intuitive evidence. In this paper we introduce a novel 3D urban data analysis framework for the smart city, which exploits the city itself and its buildings to convey data visualization. The novelty is realized thanks to a dynamic geographic tiling which binds the real city structure and the environmental data "on the fly", giving the opportunity to see the city changing as the data change. A prototype is proposed, which is based on a micro service architecture, open standards, and an immersive 3D map, aiming to support public decision makers in the process of environmental data analysis. To this extent, the current solution is built on the idea of replicability, accessibility and adaptation: it is location agnostic and does not depend on the particular position where the analysis takes place, it does not need human intervention or adjustments, once the services are instanced, and it is easily accessible, for the interface it is built on a web application.

Distributed measurement systems are widely employed in many domains, particularly in the smart city domain. Anyway, because of reasons like expensiveness of devices and installation issues, the sensor coverage is often inadequate to the accomplish the goals of a modern smart city. To surpass such issues, a novel paradigm becomes attractive that, once a specific domain is given, allows the creation of a system capable to virtually augment the sensor network, i.e. providing measurement estimation where sensors are unavailable. This kind of approach s particularly focused on training a target Neural Network model, which outlines environmental issues, on urban areas provided with large sensor network, and then to make other areas, equipped with poor sensor networks, take advantage of the same model. The present work has been specialized on the domain of air pollution that, because of the complex urban environment and the huge costs of measurements devices, represents a case study extremely fitting the problem.

Sharing personal data with service providers is a fundamental resource for the times we live in. But data sharing represents an unavoidable issue, due to improper data treatment, lack of users' awareness to whom they are sharing with, wrong or excessive data sharing from end users who ignore they are exposing personal information. The problem becomes even more complicate if we try to consider the devices around us: how to share devices we own, so that we can receive pervasive services, based on our contexts and device functionalities. The European Authority has provided the General Data Protection Regulation (GDPR), in order to implement protection of sensitive data in each EU member, throughout certification mechanisms (according to Art. 42 GDPR). The certification assures compliance to the regulation, which represent a mandatory requirement for any service which may come in contact with sensitive data. Still the certification is an open process and not constrained by strict rule. In this paper we describe our decentralized approach in sharing personal data in the era of smart devices, being those considered sensitive data as well. Having in mind the centrality of users in the ownership of the data, we have proposed a decentralized Personal Data Store prototype, which stands as a unique data sharing endpoint for third party services. Even if blockchain technologies may seem fit to solve the issue of data protection, because of the absence of a central authority, they lay to additional concerns especially relating such technologies with specifications described in the regulation. The current work offers a contribution in the advancements of personal data sharing management systems in a distributed environment by presenting a real prototype and an architectural blueprint, which advances the state of the art in order to meet the GDPR regulation. Address those arisen issues, from a technological perspective, stands as an important challenge, in order to empower end users in owning their personal data for real.

In this paper a new optical, Fiber Bragg Grating (FBG) based, pressure sensor is presented. The sensor adopts a stainless steel membrane with a FBG sensor attached and is thought to be used in a multi parametric multi-sensor system aimed at the detection of water leakages in potable water networks. The sensor has been experimentally characterized on a reference plant in the range of pressure 0–6 bar. Main metrological characteristics of the lab-scale prototype developed are: a sensitivity of 0.314 nm/bar, an accuracy of about 39 mbar and a resolution of about 1.5 mbar.

The upcoming IoE paradigm is taking the IoT era to a new shift, and that because of the natural inter-connection of processes, people, devices and stakeholders. From the smart city perspective, the main goal is to make well-informed decisions, on the base of a variable number of sensors and sources, exposing different data with different protocols and structures. The urban contexts may change, and with them, the number of sensors deployed. The novel smart city service must go beyond an integration strategy, it needs an exploitation model to optimally retrieve useful and highly contextualized information. In this paper we focus on the development of a model which fuses together the IoE potential and machine learning techniques for the cognitive smart city: retrive useful intelligent information, optimally exploiting the infrastructure the specific physical context may offer. We propose an approach and related techniques for realizing context agnostic services, namely services that do not depend on the enabling infrastructure beneath. The purpose is to create an IoE-based self-contextualizing service, which potentially consider the entire range of data that is being collected in smart cities and use such data to provide highly-personalized information about each environment, i.e., information that best suits the context of each Smart City. To prove the proposed context agnostic service, we take into account the air quality observation issue: we provide two high-contextualized informative services to leverage data related to two different physical environments, thus building location awareness for different geographic areas and stakeholders. But still managed by the same application which can adapts itself. Finally we present the evaluation of this prototype to illustrate the benefits of our solution and the future work.

In the times we are living, data protection infringements, at local, national or international level, are a daily occurrence, highlighting how important is the problem of users' awareness and “consent” about what data should or not be shared. A vast number of service providers strives to have access to users' personal data. While users may be aware of sharing their data with services they receive, they may be still unaware if their data is passing in others' hands and unknown third parties. But the sharing of personal data remains unavoidable, in this always connected digital era, contextualized services are not only fancy desires, they could save money, time, and even lives. The problem becomes even more complicate if we try to consider the devices around us: how to share devices we own, so that we can receive pervasive services, based on our contexts and device functionalities. The European Authority has provided regulations about personal data protection, but there are still significant differences in the ways each EU member state would implement the protection of privacy and personal data in national laws, policies, and practices. The tool that should empower users with the personal data protection has to face two problems: data privacy and control. Due to the lack of central authorities, blockchain based technologies would seem fit for the challenge, but such solutions are not fully exploited. One possible reason could be that distributed architectures alone do not achieve privacy of data. In this paper we tackle the challenge of a novel Personal Data Store, by making use of a distributed architecture, based on the Ethereum framework, together with an ontology to model user profile and data/device sharing towards services. Such solution, The Decentralized Identity Manager, solves personal data protection by offering a unique endpoint, without any central authority, where users can manage their data/device access, their privacy levels, and grant or deny sharing consent, every time services ask for personal data.

Smart objects are around us, more than in the past, and their services are available for being used. Large scale consolidation and easy availability of the IoT paradigm, pervasive services, Cloud computing, lead us to face the challenge of effective interaction with emerging clusters of novel devices, capable of collaborating together in order to meet always changing users' needs. The problem that must be solved is how to meet the immense number of possible services offered by device collaboration, with the everyday users' needs, who could be untrained and lacking proper skills. Actual solutions are scattered, often solving vertical problems, and requiring some deal of training for properly usage. The absence of technical skill for end users is crucial, if we want to take advantage of their creativity and innate knowledge, so that new services may emerge, without any developers' limitation. It becomes fundamental to investigate how to communicate the new pervasive and powerful opportunities that those smart objects offer, and how to leverage fruition through device collaboration. In this paper we present our theoretical approach to empower common users with an interaction model for IoT services composition, capable to intuitively manage the complexity of smart devices deployed all around us. Then we propose a technological tool, based on the novel interaction paradigm, able to scale the fruition of self made solutions, so that the users can autonomously solve their special needs by simply adding functionalities to the services they receive. Following this evolutionary paradigm, self customization of IoT service composition, empowers users in creating always different services, fit for their unique contexts.

Background: While smart objects are present in our cities everywhere, the real aim of the Internet of Things is not turned into reality yet. Each smart object is still designated to a specific task and requires proprietary procedures for interaction. Thus, it becomes more necessary to have a connection platform for abstracting the complexity of smart objects and to present their data to the end-users through a simpler interaction procedure. Keywords: Human Computer Interface, IoT, middleware, smart city, NVE, VEoT, virtual reality, WebGL.

Smart objects are present in our cities everywhere, thus it is becoming more and more necessary to have a connection platform, not only capable to make those objects talk with each other, but to present the results of their functions also to the citizens/users. Objective of this paper is the definition and development of a model that represents a connection and interaction layer between smart objects and people. In particular, we propose an immersive virtual platform, able to engage endusers and let people be aware of the where, what and how factors: where smart objects are deployed in the city, what functionalities/data they offer, and how those data represent context for the urban areas. To prove this particular model, we developed a prototypical Virtual Environment of Things (VEoT), within an immersive 3D environment in which the user can explore the virtualized urban area and interact with the available smart objects through gestures and affordable VR devices. The VEoT is fed by real-time data produced by a multi-protocol sensing middleware that simplifies the interaction with physical devices through high-level (RESTful) APIs. Paying attention to interconnection of people and things, this prototype will empower final users with engaging tools in order to enhance the fruition of the IoT paradigm.

Novel ideas are the key ingredients for innovation processes, and Idea Management System (IMS) plays a prominent role in managing captured ideas from external stakeholders and internal actors within an Open Innovation process. By considering a specific case study, Lecce-Italy, we have designed and implemented a collaborative environment, which provides an ideal platform for government, citizens, etc. to share ideas and co-create the value of innovative public services in Lecce. In this study the application of IMS with six main steps, including: idea generation, idea improvement, idea selection, refinement, idea implementation, and monitoring, shows that this, remarkably, helps service providers to exploit the intellectual capital and initiatives of the regional stakeholders and citizens and assist service providers to stay in line with the needs of society. Moreover, we have developed two support tools to foster collaboration and transparency: sentiment analysis tool and gamification application.

The need for urban regeneration does not come only by structural requirements, but also by socio-cultural needs. What we are going to propose is the urban regeneration as a way to perceive, in a different way, the surrounding spaces allowing users to receive and provide a wide range of information on the urban environment. Each space of a city has a variety of intrinsic meanings provided by human groups interacting with each other everyday. The purpose is collecting the hidden information thanks to citizens' contribution. The objective is the involvement of citizens as "builders of sense" through a playful attitude as "builders of virtual cities", and using game based on motivation as impetus for the regeneration. Urban regeneration is innovative thanks to a new participatory and cooperative methodology based on the perception of every citizen, and on the collection of players' experiences.

This paper describes a Sentiment Analysis (SA) method to analyze tweets polarity and to enable government to describe quantitatively the opinion of active users on social networks with respect to the topics of interest to the Public Administration. We propose an optimized approach employing a document-level and a dataset-level supervised machine learning classifier to provide accurate results in both individual and aggregated sentiment classification. The aim of this work is also to identify the types of features that allow to obtain the most accurate sentiment classification for a dataset of Italian tweets in the context of a Public Administration event, also taking into account the size of the training set. This work uses a dataset of 1,700 Italian tweets relating to the public event of "Lecce 2019 – European Capital of Culture".

The Object Management Group (OMG) is promoting the Model Driven Architecture (MDA) approach to support interaction among enterprises based on business process models. Based on this approach, we discuss in this paper how to specify performance indicators among the levels with different degree of abstraction suggested in MDA. These indicators will drive the monitoring activities to check the execution of business processes involving networked enterprises. Connecting the different levels we also decrease the cost of implementing metrics as the measurement of the entities at one level can be based on the lower level.

In the Web 3.0 scenario, where information and services are connected by means of their semantics, organizations can improve their competitive advantage by publishing their business and service descriptions. In this scenario, Semantic Peer to Peer (P2P) can play a key role in defining dynamic and highly reconfigurable infrastructures. Organizations can share knowledge and services, using this infrastructure to move towards value networks, an emerging organizational model characterized by fluid boundaries and complex relationships. This chapter collects and defines the technological requirements and architecture of a modular and multi-Layer Peer to Peer infrastructure for SOA-based applications. This technological infrastructure, based on the combination of Semantic Web and P2P technologies, is intended to sustain Internetworked Enterprise configurations, defining a distributed registry and enabling more expressive queries and efficient routing mechanisms. The following sections focus on the overall architecture, while describing the layers that form it.

This chapter presents the SuperJet International case study, a start-up in the aeronautics industry characterized by a process-oriented approach and a complex and as yet evolving network of partnerships and collaborations. The chapter aims to describe the key points of the start-up process, highlighting common factors and differences compared to the TEKNE Methodology of Change, with particular reference to the second and third phase, namely, the design and deployment of new techno-organizational systems. The SuperJet International start-up is presented as a case study where strategic and organizational aspects have been jointly conceived from a network-driven perspective. The chapter compares some of the guidelines of the TEKNE Methodology of Change with experiences and actual practices deriving from interviews with key players in SJI's start-up process.

The development of formal models related to the organizational aspects of an enterprise is fundamental when these aspects must be re-engineered and digitalized, especially when the enterprise is involved in the dynamics and value flows of a business network. Business modeling provides an opportunity to synthesize and make business processes, business rules and the structural aspects of an organization explicit, allowing business managers to control their complexity and guide an enterprise through effective decisional and strategic activities. This chapter discusses the main results of the TEKNE project in terms of software components that enable enterprises to configure, store, search and share models of any aspects of their business while leveraging standard and business-oriented technologies and languages to bridge the gap between the world of business people and IT experts and to foster effective business-to-business collaborations.

The benefits of managing companies through a process-based approach are well recognized in the business literature and in many corporate contexts. However, there is a limited discussion on how to practically design and develop an organization based on processes. This paper aims to address this relative ‘gap’ in the literature by presenting the case of a recent international joint venture in the regional jet industry. In the following paper, we present a story of organization design based on the identification and description of the core process model of the company, with a specific focus on customer service activities. Based on interviews and direct observation at the field site, this paper shows the main steps undertaken to define the process taxonomy levels and to describe process elements, along with a discussion of the relationships with the business model components of the company. The paper provides practical value as it provides practical insights relating to the start-up of a new company driven by a process-based approach. Copyright © 2010 John Wiley & Sons, Ltd.

In the Web 3.0 scenario, where information and services are connected by means of their semantics, organizations can improve their competitive advan- tage by publishing their business and service descriptions. In this scenario, Seman- tic Peer to Peer (P2P) can play a key role in defining dynamic and highly reconfi- gurable infrastructures. Organizations can share knowledge and services, using this infrastructure to move towards value networks, an emerging organizational model characterized by fluid boundaries and complex relationships. This chapter collects and defines the technological requirements and architecture of a modular and multi-Layer Peer to Peer infrastructure for SOA-based applications. This technological infrastructure, based on the combination of Semantic Web and P2P technologies, is intended to sustain Internetworked Enterprise configurations, de- fining a distributed registry and enabling more expressive queries and efficient routing mechanisms. The following sections focus on the overall architecture, while describing the layers that form it.

This work contributes to the results of the TEKNE projec, a project aimed at developing a framework for Business Process Management (BPM), supporting the designer with a set of performance indicators. The indicators drive the designer in estimating if the process comply to the objectives and when necessary enable re-engineering of the process. In particular this paper discuses how to derive performance indicators directly from requirements expressed in a Business Rules (BR) format.