Contribution of New Digital Technologies to the Digital Building Logbook

According to the European Commission, the Digital Building Logbook (DBL) is a repository of all of the relevant data of a building. It was first introduced at the European scale in the Renovation Wave strategy and was first defined in the proposal for the recast of the energy performance of buildings Directive in December 2021. The European DBL has not been implemented yet, since a common model does not yet exist. Even though great efforts are being made to establish it, some relevant issues need to be addressed first. One of them is the identification of data sources that will feed the DBL. Existing digital data sources have already been explored in some countries and they have been found to be insufficient. In this paper, new digital data sources suitable for the logbook are identified, and their contribution in terms of indicators and interoperability is analysed. The analysis shows that these sources have great potential to contribute to the DBL, because they bring the possibility to collect a great amount of real data on buildings. However, the main barrier for these tools to be incorporated into the DBL is that their linkage still requires further research

Building Blocks for IoT Analytics Internet-of-Things Analytics

Internet-of-Things (IoT) Analytics are an integral element of most IoT applications, as it provides the means to extract knowledge, drive actuation services and optimize decision making. IoT analytics will be a major contributor to IoT business value in the coming years, as it will enable organizations to process and fully leverage large amounts of IoT data, which are nowadays largely underutilized. The Building Blocks of IoT Analytics is devoted to the presentation the main technology building blocks that comprise advanced IoT analytics systems. It introduces IoT analytics as a special case of BigData analytics and accordingly presents leading edge technologies that can be deployed in order to successfully confront the main challenges of IoT analytics applications. Special emphasis is paid in the presentation of technologies for IoT streaming and semantic interoperability across diverse IoT streams. Furthermore, the role of cloud computing and BigData technologies in IoT analytics are presented, along with practical tools for implementing, deploying and operating non-trivial IoT applications. Along with the main building blocks of IoT analytics systems and applications, the book presents a series of practical applications, which illustrate the use of these technologies in the scope of pragmatic applications. Technical topics discussed in the book include: Cloud Computing and BigData for IoT analyticsSearching the Internet of ThingsDevelopment Tools for IoT Analytics ApplicationsIoT Analytics-as-a-ServiceSemantic Modelling and Reasoning for IoT AnalyticsIoT analytics for Smart BuildingsIoT analytics for Smart CitiesOperationalization of IoT analyticsEthical aspects of IoT analyticsThis book contains both research oriented and applied articles on IoT analytics, including several articles reflecting work undertaken in the scope of recent European Commission funded projects in the scope of the FP7 and H2020 programmes. These articles present results of these projects on IoT analytics platforms and applications. Even though several articles have been contributed by different authors, they are structured in a well thought order that facilitates the reader either to follow the evolution of the book or to focus on specific topics depending on his/her background and interest in IoT and IoT analytics technologies. The compilation of these articles in this edited volume has been largely motivated by the close collaboration of the co-authors in the scope of working groups and IoT events organized by the Internet-of-Things Research Cluster (IERC), which is currently a part of EU's Alliance for Internet of Things Innovation (AIOTI)

mF2C: Towards a coordinated management of the IoT-fof-cloud continuum

Fog computing enables location dependent resource allocation and low latency services, while fostering novel market and business opportunities in the cloud sector. Aligned to this trend, we refer to Fog-tocloud (F2C) computing system as a new pool of resources, set into a layered and hierarchical model, intended to ease the entire fog and cloud resources management and coordination. The H2020 project mF2C aims at designing, developing and testing a first attempt for a real F2C architecture. This document outlines the architecture and main functionalities of the management framework designed in the mF2C project to coordinate the execution of services in the envisioned set of heterogeneous anddistributed resources.Postprint (author's final draft

Building Blocks for IoT Analytics Internet-of-Things Analytics

Internet-of-Things (IoT) Analytics are an integral element of most IoT applications, as it provides the means to extract knowledge, drive actuation services and optimize decision making. IoT analytics will be a major contributor to IoT business value in the coming years, as it will enable organizations to process and fully leverage large amounts of IoT data, which are nowadays largely underutilized. The Building Blocks of IoT Analytics is devoted to the presentation the main technology building blocks that comprise advanced IoT analytics systems. It introduces IoT analytics as a special case of BigData analytics and accordingly presents leading edge technologies that can be deployed in order to successfully confront the main challenges of IoT analytics applications. Special emphasis is paid in the presentation of technologies for IoT streaming and semantic interoperability across diverse IoT streams. Furthermore, the role of cloud computing and BigData technologies in IoT analytics are presented, along with practical tools for implementing, deploying and operating non-trivial IoT applications. Along with the main building blocks of IoT analytics systems and applications, the book presents a series of practical applications, which illustrate the use of these technologies in the scope of pragmatic applications. Technical topics discussed in the book include: Cloud Computing and BigData for IoT analyticsSearching the Internet of ThingsDevelopment Tools for IoT Analytics ApplicationsIoT Analytics-as-a-ServiceSemantic Modelling and Reasoning for IoT AnalyticsIoT analytics for Smart BuildingsIoT analytics for Smart CitiesOperationalization of IoT analyticsEthical aspects of IoT analyticsThis book contains both research oriented and applied articles on IoT analytics, including several articles reflecting work undertaken in the scope of recent European Commission funded projects in the scope of the FP7 and H2020 programmes. These articles present results of these projects on IoT analytics platforms and applications. Even though several articles have been contributed by different authors, they are structured in a well thought order that facilitates the reader either to follow the evolution of the book or to focus on specific topics depending on his/her background and interest in IoT and IoT analytics technologies. The compilation of these articles in this edited volume has been largely motivated by the close collaboration of the co-authors in the scope of working groups and IoT events organized by the Internet-of-Things Research Cluster (IERC), which is currently a part of EU's Alliance for Internet of Things Innovation (AIOTI)

Hierarchical distributed fog-to-cloud data management in smart cities

There is a vast amount of data being generated every day in the world with different formats, quality levels, etc. This new data, together with the archived historical data, constitute the seed for future knowledge discovery and value generation in several fields of science and big data environments. Discovering value from data is a complex computing process where data is the key resource, not only during its processing, but also during its entire life cycle. However, there is still a huge concern about how to organize and manage this data in all fields for efficient usage and exploitation during all data life cycles. Although several specific Data LifeCycle (DLC) models have been recently defined for particular scenarios, we argue that there is no global and comprehensive DLC framework to be widely used in different fields. In particular scenario, smart cities are the current technological solutions to handle the challenges and complexity of the growing urban density. Traditionally, Smart City resources management rely on cloud based solutions where sensors data are collected to provide a centralized and rich set of open data. The advantages of cloud-based frameworks are their ubiquity, as well as an (almost) unlimited resources capacity. However, accessing data from the cloud implies large network traffic, high latencies usually not appropriate for real-time or critical solutions, as well as higher security risks. Alternatively, fog computing emerges as a promising technology to absorb these inconveniences. It proposes the use of devices at the edge to provide closer computing facilities and, therefore, reducing network traffic, reducing latencies drastically while improving security. We have defined a new framework for data management in the context of a Smart City through a global fog to cloud resources management architecture. This model has the advantages of both, fog and cloud technologies, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. In this thesis, we propose many novel ideas in the design of a novel F2C Data Management architecture for smart cities as following. First, we draw and describe a comprehensive scenario agnostic Data LifeCycle model successfully addressing all challenges included in the 6Vs not tailored to any specific environment, but easy to be adapted to fit the requirements of any particular field. Then, we introduce the Smart City Comprehensive Data LifeCycle model, a data management architecture generated from a comprehensive scenario agnostic model, tailored for the particular scenario of Smart Cities. We define the management of each data life phase, and explain its implementation on a Smart City with Fog-to-Cloud (F2C) resources management. And then, we illustrate a novel architecture for data management in the context of a Smart City through a global fog to cloud resources management architecture. We show this model has the advantages of both, fog and cloud, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. As a first experiment for the F2C data management architecture, a real Smart City is analyzed, corresponding to the city of Barcelona, with special emphasis on the layers responsible for collecting the data generated by the deployed sensors. The amount of daily sensors data transmitted through the network has been estimated and a rough projection has been made assuming an exhaustive deployment that fully covers all city. And, we provide some solutions to both reduce the data transmission and improve the data management. Then, we used some data filtering techniques (including data aggregation and data compression) to estimate the network traffic in this model during data collection and compare it with a traditional real system. Indeed, we estimate the total data storage sizes through F2C scenario for Barcelona smart citiesAl món es generen diàriament una gran quantitat de dades, amb diferents formats, nivells de qualitat, etc. Aquestes noves dades, juntament amb les dades històriques arxivades, constitueixen la llavor per al descobriment de coneixement i la generació de valor en diversos camps de la ciència i grans entorns de dades (big data). Descobrir el valor de les dades és un procés complex de càlcul on les dades són el recurs clau, no només durant el seu processament, sinó també durant tot el seu cicle de vida. Tanmateix, encara hi ha una gran preocupació per com organitzar i gestionar aquestes dades en tots els camps per a un ús i explotació eficients durant tots els cicles de vida de les dades. Encara que recentment s'han definit diversos models específics de Data LifeCycle (DLC) per a escenaris particulars, argumentem que no hi ha un marc global i complet de DLC que s'utilitzi àmpliament en diferents camps. En particular, les ciutats intel·ligents són les solucions tecnològiques actuals per fer front als reptes i la complexitat de la creixent densitat urbana. Tradicionalment, la gestió de recursos de Smart City es basa en solucions basades en núvol (cloud computing) on es recopilen dades de sensors per proporcionar un conjunt de dades obert i centralitzat. Les avantatges dels entorns basats en núvol són la seva ubiqüitat, així com una capacitat (gairebé) il·limitada de recursos. Tanmateix, l'accés a dades del núvol implica un gran trànsit de xarxa i, en general, les latències elevades no són apropiades per a solucions crítiques o en temps real, així com també per a riscos de seguretat més elevats. Alternativament, el processament de boira (fog computing) sorgeix com una tecnologia prometedora per absorbir aquests inconvenients. Proposa l'ús de dispositius a la vora per proporcionar recuirsos informàtics més propers i, per tant, reduir el trànsit de la xarxa, reduint les latències dràsticament mentre es millora la seguretat. Hem definit un nou marc per a la gestió de dades en el context d'una ciutat intel·ligent a través d'una arquitectura de gestió de recursos des de la boira fins al núvol (Fog-to-Cloud computing, o F2C). Aquest model té els avantatges combinats de les tecnologies de boira i de núvol, ja que permet reduir les latències per a aplicacions crítiques mentre es poden utilitzar les grans capacitats informàtiques de la tecnologia en núvol. En aquesta tesi, proposem algunes idees noves en el disseny d'una arquitectura F2C de gestió de dades per a ciutats intel·ligents. En primer lloc, dibuixem i descrivim un model de Data LifeCycle global agnòstic que aborda amb èxit tots els reptes inclosos en els 6V i no adaptats a un entorn específic, però fàcil d'adaptar-se als requisits de qualsevol camp en concret. A continuació, presentem el model de Data LifeCycle complet per a una ciutat intel·ligent, una arquitectura de gestió de dades generada a partir d'un model agnòstic d'escenari global, adaptat a l'escenari particular de ciutat intel·ligent. Definim la gestió de cada fase de la vida de les dades i expliquem la seva implementació en una ciutat intel·ligent amb gestió de recursos F2C. I, a continuació, il·lustrem la nova arquitectura per a la gestió de dades en el context d'una Smart City a través d'una arquitectura de gestió de recursos F2C. Mostrem que aquest model té els avantatges d'ambdues, la tecnologia de boira i de núvol, ja que permet reduir les latències per a aplicacions crítiques mentre es pot utilitzar la gran capacitat de processament de la tecnologia en núvol. Com a primer experiment per a l'arquitectura de gestió de dades F2C, s'analitza una ciutat intel·ligent real, corresponent a la ciutat de Barcelona, amb especial èmfasi en les capes responsables de recollir les dades generades pels sensors desplegats. S'ha estimat la quantitat de dades de sensors diàries que es transmet a través de la xarxa i s'ha realitzat una projecció aproximada assumint un desplegament exhaustiu que cobreix tota la ciutat

Hierarchical distributed fog-to-cloud data management in smart cities

There is a vast amount of data being generated every day in the world with different formats, quality levels, etc. This new data, together with the archived historical data, constitute the seed for future knowledge discovery and value generation in several fields of science and big data environments. Discovering value from data is a complex computing process where data is the key resource, not only during its processing, but also during its entire life cycle. However, there is still a huge concern about how to organize and manage this data in all fields for efficient usage and exploitation during all data life cycles. Although several specific Data LifeCycle (DLC) models have been recently defined for particular scenarios, we argue that there is no global and comprehensive DLC framework to be widely used in different fields. In particular scenario, smart cities are the current technological solutions to handle the challenges and complexity of the growing urban density. Traditionally, Smart City resources management rely on cloud based solutions where sensors data are collected to provide a centralized and rich set of open data. The advantages of cloud-based frameworks are their ubiquity, as well as an (almost) unlimited resources capacity. However, accessing data from the cloud implies large network traffic, high latencies usually not appropriate for real-time or critical solutions, as well as higher security risks. Alternatively, fog computing emerges as a promising technology to absorb these inconveniences. It proposes the use of devices at the edge to provide closer computing facilities and, therefore, reducing network traffic, reducing latencies drastically while improving security. We have defined a new framework for data management in the context of a Smart City through a global fog to cloud resources management architecture. This model has the advantages of both, fog and cloud technologies, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. In this thesis, we propose many novel ideas in the design of a novel F2C Data Management architecture for smart cities as following. First, we draw and describe a comprehensive scenario agnostic Data LifeCycle model successfully addressing all challenges included in the 6Vs not tailored to any specific environment, but easy to be adapted to fit the requirements of any particular field. Then, we introduce the Smart City Comprehensive Data LifeCycle model, a data management architecture generated from a comprehensive scenario agnostic model, tailored for the particular scenario of Smart Cities. We define the management of each data life phase, and explain its implementation on a Smart City with Fog-to-Cloud (F2C) resources management. And then, we illustrate a novel architecture for data management in the context of a Smart City through a global fog to cloud resources management architecture. We show this model has the advantages of both, fog and cloud, as it allows reduced latencies for critical applications while being able to use the high computing capabilities of cloud technology. As a first experiment for the F2C data management architecture, a real Smart City is analyzed, corresponding to the city of Barcelona, with special emphasis on the layers responsible for collecting the data generated by the deployed sensors. The amount of daily sensors data transmitted through the network has been estimated and a rough projection has been made assuming an exhaustive deployment that fully covers all city. And, we provide some solutions to both reduce the data transmission and improve the data management. Then, we used some data filtering techniques (including data aggregation and data compression) to estimate the network traffic in this model during data collection and compare it with a traditional real system. Indeed, we estimate the total data storage sizes through F2C scenario for Barcelona smart citiesAl món es generen diàriament una gran quantitat de dades, amb diferents formats, nivells de qualitat, etc. Aquestes noves dades, juntament amb les dades històriques arxivades, constitueixen la llavor per al descobriment de coneixement i la generació de valor en diversos camps de la ciència i grans entorns de dades (big data). Descobrir el valor de les dades és un procés complex de càlcul on les dades són el recurs clau, no només durant el seu processament, sinó també durant tot el seu cicle de vida. Tanmateix, encara hi ha una gran preocupació per com organitzar i gestionar aquestes dades en tots els camps per a un ús i explotació eficients durant tots els cicles de vida de les dades. Encara que recentment s'han definit diversos models específics de Data LifeCycle (DLC) per a escenaris particulars, argumentem que no hi ha un marc global i complet de DLC que s'utilitzi àmpliament en diferents camps. En particular, les ciutats intel·ligents són les solucions tecnològiques actuals per fer front als reptes i la complexitat de la creixent densitat urbana. Tradicionalment, la gestió de recursos de Smart City es basa en solucions basades en núvol (cloud computing) on es recopilen dades de sensors per proporcionar un conjunt de dades obert i centralitzat. Les avantatges dels entorns basats en núvol són la seva ubiqüitat, així com una capacitat (gairebé) il·limitada de recursos. Tanmateix, l'accés a dades del núvol implica un gran trànsit de xarxa i, en general, les latències elevades no són apropiades per a solucions crítiques o en temps real, així com també per a riscos de seguretat més elevats. Alternativament, el processament de boira (fog computing) sorgeix com una tecnologia prometedora per absorbir aquests inconvenients. Proposa l'ús de dispositius a la vora per proporcionar recuirsos informàtics més propers i, per tant, reduir el trànsit de la xarxa, reduint les latències dràsticament mentre es millora la seguretat. Hem definit un nou marc per a la gestió de dades en el context d'una ciutat intel·ligent a través d'una arquitectura de gestió de recursos des de la boira fins al núvol (Fog-to-Cloud computing, o F2C). Aquest model té els avantatges combinats de les tecnologies de boira i de núvol, ja que permet reduir les latències per a aplicacions crítiques mentre es poden utilitzar les grans capacitats informàtiques de la tecnologia en núvol. En aquesta tesi, proposem algunes idees noves en el disseny d'una arquitectura F2C de gestió de dades per a ciutats intel·ligents. En primer lloc, dibuixem i descrivim un model de Data LifeCycle global agnòstic que aborda amb èxit tots els reptes inclosos en els 6V i no adaptats a un entorn específic, però fàcil d'adaptar-se als requisits de qualsevol camp en concret. A continuació, presentem el model de Data LifeCycle complet per a una ciutat intel·ligent, una arquitectura de gestió de dades generada a partir d'un model agnòstic d'escenari global, adaptat a l'escenari particular de ciutat intel·ligent. Definim la gestió de cada fase de la vida de les dades i expliquem la seva implementació en una ciutat intel·ligent amb gestió de recursos F2C. I, a continuació, il·lustrem la nova arquitectura per a la gestió de dades en el context d'una Smart City a través d'una arquitectura de gestió de recursos F2C. Mostrem que aquest model té els avantatges d'ambdues, la tecnologia de boira i de núvol, ja que permet reduir les latències per a aplicacions crítiques mentre es pot utilitzar la gran capacitat de processament de la tecnologia en núvol. Com a primer experiment per a l'arquitectura de gestió de dades F2C, s'analitza una ciutat intel·ligent real, corresponent a la ciutat de Barcelona, amb especial èmfasi en les capes responsables de recollir les dades generades pels sensors desplegats. S'ha estimat la quantitat de dades de sensors diàries que es transmet a través de la xarxa i s'ha realitzat una projecció aproximada assumint un desplegament exhaustiu que cobreix tota la ciutat.Postprint (published version

Assessment of industrial pre-determinants of territories with active product-service innovation ecosystems

There has been growing interest in service-augmented products and the subsequent formation of product-service innovation (PSI) ecosystems. Hence, the objective of this paper is to empirically address an unexplored aspect of PSI ecosystems research by offering answers as to whether territories develop more performant PSI ecosystems in terms of manufacturing employment growth when they arise from an existing industrial base. Running a fixed-effects model on a sample of all 17 Spanish autonomous communities in the period from 2006 to 2012, the importance of territories having a strong incumbent manufacturing sector before developing PSI ecosystems is revealed. Specifically, it is found that PSI ecosystems will generate greater industrial employment growth in manufacturing-led territories. Our model and findings suggest various implications for scholars, managers, and policymakers alike.Peer ReviewedPostprint (published version

Design of local energy communities according to typologies. Example application of the metropolitan region of Barcelona

El desenvolupament de comunitats energètiques locals establertes dins de la legislació de la UE promou la participació ciutadana i la propietat col·lectiva de les energies renovables, contribuint a una transició energètica més justa i inclusiva. No obstant això, encara hi ha una deficiència d'informació a causa de factors com ara un marc legal imprecís o la manca d'exemples de referència. L'objectiu del treball és analitzar les condicions contextuals i donar recomanacions tècniques i organitzatives sobre el disseny de comunitats energètiques locals a l'Àrea Metropolitana de Barcelona, incloent la consideració de dos casos d'estudi. A partir d'una revisió bibliogràfica, s'estableix un marc de factors de context importants que cal considerar en el disseny, així com de possibles configuracions segons les característiques tècniques i organitzatives rellevants. Aquesta informació es complementa amb una enquesta a diferents comunitats energètiques existents a Espanya i amb entrevistes a experts. L'aplicació d'aquest marc a l'Àrea Metropolitana de Barcelona mostra que, encara que encara hi ha certes barreres, en general existeix un gran potencial per al desenvolupament de comunitats energètiques locals a causa d'aspectes com les condicions favorables per a l'energia solar o la presència d'associacions de veïns i altres estructures comunitàries. A partir de l'anàlisi del context, es fan diferents recomanacions. El disseny d'una instal·lació fotovoltaica en una coberta d'exemple també pot il·lustrar que es poden crear sinèrgies en incloure diferents perfils de consumidors en una comunitat energètica, tals com edificis oficines, instituts i llars. El treball pot contribuir a una major investigació sobre els factors contextuals, així com sobre les tipologies de les comunitats energètiques locals. A més, la manca d'anàlisi de casos locals a l'entorn urbà s'aborda aplicant el marc elaborat al cas de Barcelona.El desarrollo de comunidades energéticas locales establecidas en la legislación de la UE promueve la participación ciudadana y la propiedad colectiva de las energías renovables, contribuyendo a una transición energética más justa e inclusiva. Sin embargo, todavía existen algunas brechas de información debido a factores como un marco legal impreciso o la falta de ejemplos de referencia. El objetivo del trabajo es analizar las condiciones contextuales y dar recomendaciones tanto técnicas como organizativas sobre el diseño de comunidades energéticas locales en el Área Metropolitana de Barcelona, incluyendo la consideración de dos casos de estudio. A partir de una revisión bibliográfica, se establece un marco de factores de contexto importantes a considerar en el diseño, así como de posibles configuraciones según características técnicas y organizativas relevantes. Esta información se complementa con una encuesta a diferentes comunidades energéticas existentes en España y con entrevistas a expertos. La aplicación de este marco en el Área Metropolitana de Barcelona muestra que, aunque todavía existen ciertas barreras, en general existe un gran potencial para el desarrollo de comunidades energéticas locales debido a aspectos como las condiciones favorables para la energía solar o la presencia de asociaciones de vecinos y otras estructuras comunitarias. A partir del análisis del contexto, se hacen diferentes recomendaciones. El diseño de una instalación fotovoltaica en una cubierta de ejemplo también puede ilustrar que se pueden crear sinergias al incluir diferentes perfiles de consumidores en una comunidad energética, tales como edificios de oficinas, institutos y hogares. El trabajo puede contribuir a una mayor investigación sobre los factores contextuales, así como sobre las tipologías de las comunidades energéticas locales. Además, la falta de análisis de casos locales en el entorno urbano se aborda aplicando el marco elaborado al caso de Barcelona.The development of local energy communities established in the EU legislation promotes citizen participation and the collective ownership of renewable energies, contributing to a more just and inclusive energy transition. However, there are still some information gaps due to factors such as an imprecise legal framework or a lack of reference examples. The objective of the thesis is to analyse the current framework conditions and give technical as well as organizational recommendations on the design of local energy communities in the Metropolitan Area of Barcelona, with consideration of two case studies. Based on a literature review, a framework of important context factors to be considered in the design as well as of possible configurations according to relevant technical and organizational characteristics is established. This information is complemented by a survey among existing energy communities in Spain and interviews with experts. The application of this framework to the Metropolitan Area of Barcelona shows that although certain barriers still exist, there is generally a great potential for the development of local energy communities due to aspects such as favourable conditions for solar energy or the presence of neighbourhood associations and other community structures. Based on the analysis of the context, different recommendations are made. The design of a PV installation on an example roof also illustrates that synergies can be created by including different consumer profiles in an energy community, such as office buildings, schools and households. The thesis at hand is able to contribute to further research on contextual factors as well as on typologies of local energy communities. Moreover, the lack of case study analysis in the urban setting is addressed by applying the elaborated framework on the case of Barcelona

Block-Based Development of Mobile Learning Experiences for the Internet of Things

The Internet of Things enables experts of given domains to create smart user experiences for interacting with the environment. However, development of such experiences requires strong programming skills, which are challenging to develop for non-technical users. This paper presents several extensions to the block-based programming language used in App Inventor to make the creation of mobile apps for smart learning experiences less challenging. Such apps are used to process and graphically represent data streams from sensors by applying map-reduce operations. A workshop with students without previous experience with Internet of Things (IoT) and mobile app programming was conducted to evaluate the propositions. As a result, students were able to create small IoT apps that ingest, process and visually represent data in a simpler form as using App Inventor's standard features. Besides, an experimental study was carried out in a mobile app development course with academics of diverse disciplines. Results showed it was faster and easier for novice programmers to develop the proposed app using new stream processing blocks.Spanish National Research Agency (AEI) - ERDF fund

How to Survive Identity Management in the Industry 4.0 Era

Industry 4.0 heavily builds on massive deployment of Industrial Internet of Things (IIoT) devices to monitor every aspect of the manufacturing processes. Since the data gathered by these devices impact the output of critical processes, identity management and communications security are critical aspects, which commonly rely on the deployment of X.509 certificates. Nevertheless, the provisioning and management of individual certificates for a high number of IIoT devices involves important challenges. In this paper, we present a solution to improve the management of digital certificates in IIoT environments, which relies on partially delegating the certificate enrolment process to an edge server. However, in order to preserve end-to-end security, private keys are never delegated. Additionally, for the protection of the communications between the edge server and the IIoT devices, an approach based on Identity Based Cryptography is deployed. The proposed solution considers also the issuance of very short-lived certificates, which reduces the risk of using expired or compromised certificates, and avoids the necessity of implementing performance expensive protocols such as Online Certificate Status Protocol (OCSP). The proposed solution has been successfully tested as an efficient identity management solution for IIoT environments in a real industrial environment.This work was supported in part by the Spanish Ministry of Science and Innovation through the National Towards zeRo toUch nEtwork and services for beyond 5G (TRUE-5G) Project under Grant PID2019-108713RB-C53, in part by the European Commission through the Electronic Components and Systems for European Leadership-Joint Undertaking (ECSEL-JU) 2018 Program under the framework of key enabling technologies for safe and autonomous drones' applications (COMP4DRONES) Project under Grant 826610, with the national financing from France, Spain, Italy, The Netherlands, Austria, Czech, Belgium, and Latvia, in part by the Ayudas Cervera para Centros Tecnologicos Grant of the Spanish Centre for the Development of Industrial Technology (CDTI) through the Project EGIDA under Grant CER-20191012, and in part by the Basque Country Government through the Creating Trust in the Industrial Digital Transformation (TRUSTIND) ELKARTEK Program Project under Grant KK-2020/00054