Industrial Internet

Cybersecurity and traditional operational IT security matters are of extreme importance in the development towards Industrie 4.0 / Industry 4.0, Industrial Internet, Industrial IoT and Smart Manufacturing alltogether. This paper studies the development of the major frameworks in relation to their interest and actions on ICT security manners and provides a perspective view to which ICT Security researchers and professionals should work towards.

Industry 4.0 integrates a series of emerging technologies, such as the Internet of Things (IoT), cyber-physical systems (CPS), cloud computing, and big data, and aims to improve operational efficiency and accelerate productivity inside the industrial environment. This article provides a series of information about the required structure to adopt Industry 4.0 approaches and a brief review of related concepts to finally identify challenges and research opportunities to envision the adoption of so-called digital twins. We want to pay attention to upgrading older systems aiming to provide the well-known advantages of Industry 4.0 to such legacy systems as reducing production costs, increasing efficiency, acquiring better robustness of equipment, and reaching advanced process connectivity.

Impact of Industrie 4.0, Internet of Things IoT and Internet of Services IoS on the AEC/EPC ecosystem. Construction Lifecycle Management promotes new ways of thinking and doing business, aiming to achieve Lean by delivering innovative Construction Process Integration framework to manage holistically all the phases of the Lifecycle of a Capital Asset: design, build, operate and retirement. Lean Construction extends from the objectives of a lean production system - maximize value and minimize waste - to specific techniques, and applies them in a new project delivery process.

Ethernet based VPLS (Virtual Private LAN Service) is a transparent, protocol independent,
multipoint L2VPN (Layer 2 Virtual Private Network) mechanism to interconnect remote customer
sites over IP (Internet Protocol) or MPLS (Multiprotocol Label Switching) based provider
networks. VPLS networks are now becoming attractive in many Enterprise applications, such as
DCI (data center interconnect), voice over IP (VoIP) and videoconferencing services due to their
simple, protocol-independent and cost efficient operation. However, these new VPLS applications
demand additional requirements, such as elevated security, enhanced scalability, optimum
utilization of network resources and further reduction in operational costs. Hence, the motivation
of this thesis is to develop secure and scalable VPLS architectures for future communication
networks.

First, a scalable secure flat-VPLS architecture is proposed based on a Host Identity Protocol
(HIP). It contains a session key-based security mechanism and an efficient broadcast mechanism
that increase the forwarding and security plane scalability of VPLS networks. Second, a secure
hierarchical-VPLS architecture is proposed to achieve control plane scalability. A novel encrypted
label-based secure frame forwarding mechanism is designed to transport L2 frames over a
hierarchical VPLS network. Third, a novel Distributed Spanning Tree Protocol (DSTP) is
designed to maintain a loop free Ethernet network over a VPLS network. With DSTP it is
proposed to run a modified STP (Spanning Tree Protocol) instance in each remote segment of the
VPLS network. In addition, two Redundancy Identification Mechanisms (RIMs) termed Customer
Associated RIMs (CARIM) and Provider Associated RIMs (PARIM) are used to mitigate the
impact of invisible loops in the provider network.

Lastly, a novel SDN (Software Defined Networking) based VPLS (Soft-VPLS) architecture is
designed to overcome tunnel management limitations in legacy secure VPLS architectures.
Moreover, three new mechanisms are proposed to improve the performance of legacy tunnel
management functions: 1) A dynamic tunnel establishment mechanism, 2) a tunnel resumption
mechanism and 3) a fast transmission mechanism. The proposed architecture utilizes a centralized
controller to command VPLS tunnel establishment based on real-time network behavior.

Hence, the results of the thesis will help for more secure, scalable and efficient system design
and development of VPLS networks. It will also help to optimize the utilization of network
resources and further reduction in operational costs of future VPLS networks.

The Internet of Things (IoT) has heralded a never-before-seen quantity of high-quality data. This includes both personal and non-personal data. Factual and legal control over IoT data gives companies unparalleled power to influence consumers, policy makers, and the other stake-holders of the IoT’s supply chain. The combination of analytics algorithms, the data goldmine structure and the output of data processes are regularly kept secret by businesses. Leveraging this portfolio of big data and trade secrets, IoT companies put in place practices that can negatively affect consumers, who are often unaware of them due to technical and legal secrecy. ‘Technical’ secrecy results from the opacity of the algorithms that underpin the IoT, especially when AI-en-abled. ‘Legal’ secrecy, in turn, come from a combination of trade secrets and strategic contract management that keep IoT data practices secret. This begs the central research question of this article: how can consumers be empowered to...

This article is a useful tool for both Asian and European readers as regards some of the state-of-the-art technologies revolving around the Internet of Things (‘IoT’) and their intersection with cloud computing (the Clouds of Things, ‘CoT’) in both the continents. The main legal issues will be presented, with a focus on intellectual property, consumer protection, and privacy. India and the United Kingdom are selected because they are at the forefront of the IoT innovation in their respective countries. The IoT is an expanding and heterogeneous universe encompassing all Things which are capable of connectivity and are equipped with sensing and actuating capabilities. One can find Things in very diverse sectors, from agriculture to manufacturing, retail, healthcare, leisure, domotics, urban development, etc. Therefore, not only is providing an exhaustive and static definition of the IoT nearly impossible (or at least pointless), but also the endeavour of providing a complete picture of the phenomenon would be a cumbersome path towards failure. Consequently, I will give account only of the highlights of the IoT in India and the United Kingdom. In India, the IoT will be analysed through the prism of net neutrality, smart cities, manufacturing, computer-related inventions, and a recent bill on the surveillance aspects of the world’s largest biometric database (Aadhaar). In turn, I will look at the British context by analysing some (quasi) regulatory acts with a focus on privacy and consumer protection. One last caveat. When it comes to new technologies, one tends to be either ‘apocalyptic’ or ‘integrated’. Either the technology will save us all by leveraging a revolution leading to a disruptive innovation, or it will destroy our lives and the world will go to the dogs. I take a middle position and believe that through education, collective awareness, and soft law, one will be able to keep the human being at the centre of innovation, to unite people rather than divide them, to empower them and alleviate discrimination and poverty. What is important is neither should one delegate to technology nor to rely entirely on government: if the IoT is to actually become a revolution, it will do so due to the commitment of each and every one of us who will contribute to create the Internet of Citizens.

PLEASE CITE AS: Guido NOTO LA DIEGA, The Internet of Citizens. A lawyer’s view on some technological developments in the United Kingdom and India, in Indian Journal of Law & Technology, 2017, 12(1), 53-104.

The Internet of Things (IoT) has heralded a never-before-seen quantity of high-quality data. This includes both personal and non-personal data. Factual and legal control over IoT data gives companies unparalleled power to influence consumers, policy makers, and the other stake-holders of the IoT’s supply chain. The combination of analytics algorithms, the data goldmine structure and the output of data processes are regularly kept secret by businesses. Leveraging this portfolio of big data and trade secrets, IoT companies put in place practices that can negatively affect consumers, who are often unaware of them due to technical and legal secrecy. ‘Technical’ secrecy results from the opacity of the algorithms that underpin the IoT, especially when AI-en-abled. ‘Legal’ secrecy, in turn, come from a combination of trade secrets and strategic contract management that keep IoT data practices secret. This begs the central research question of this article: how can consumers be empowered to counter IoT data appropriation?

Traditional consumer protection approaches, epitomised by the Consumer Rights Directive, are focused on pre-contractual duties to inform consumers. Their benefit to IoT consumers is limited by their reflecting a text-based paradigm, whereby information must be legible. This is not fit for the IoT, where displays tend to disappear and information is provided in audio or video formats. Consumer laws are drafted on the assumption of information asymmetries in business-to-consumer contracts, but they fail to account for the power imbalances that permeate IoT transactions. These power imbalances are exacerbated by control over a wealth of user data and corresponding granular knowledge of consumers’ vulnerabilities, behaviors, and biases. This knowledge can be used to impose opaque practices on consumers; among these, IoT data appropriation by means of trade secrets plays a key role.
Therefore, an emergent concern is whether the law provides tools that effectively safeguard consumers’ interests, in particular by ensuring substantial transparency as to the actual use of their personal data. How can this can be guaranteed, and the consumer empowered in a post-interface world of profoundly imbalanced relationships? The answer cannot be found solely within the trade secrets’ regime: data protection needs to be considered.

This article focuses on the trade secrets exceptions of legitimate interest and freedom of information, and on the General Data Protection Regulation (GDPR)’s rights to access, data portability, information, and not to be subject to solely automated decisions. We put forward that trade secrets’ exceptions and GDPR rights re-balance the interests of consumers vis-à-vis big IoT players such as Amazon. Specifically, they can positively contribute to transparency, consumers autonomy, information symmetry, data portability, and freedom of choice. We propose a holistic approach that empowers consumers by countering data appropriation, thus redistributing data control.

Please cite as Guido Noto La Diega and Cristiana Sappa, ‘The Internet of Things at the intersection of data protection and trade secrets. Non-conventional paths to counter data appropriation and empower consumers’ (2020) 3 Revue européenne de droit de la consommation / European Journal of Consumer Law 419-458

Industrie 4.0 is originally a future vision described in the high-tech strategy of the German government that is conceived upon the information and communication technologies like Cyber-Physical Systems, Internet of Things, Physical Internet and Internet of Services to achieve a high degree of flexibility in production, higher productivity rates through real-time monitoring and diagnosis, and a lower wastage rate of material in production. An important part of the tasks in the preparation for Industrie 4.0 is the adaptation of the higher education to the requirements of this vision, in particular the engineering education. In this work, we introduce a road map consisting of three pillars describing the changes/enhancements to be conducted in the areas of curriculum development, lab concept, and student club activities. We also report our current application of this road map at the Turkish-German University, Istanbul.

Industrie 4.0 is originally a future vision described in the high-tech strategy of the German government that is conceived upon the information and communication technologies like Cyber-Physical Systems, Internet of Things, Physical Internet and Internet of Services to achieve a high degree of flexibility in production, higher productivity rates through real-time monitoring and diagnosis, and a lower wastage rate of material in production. An important part of the tasks in the preparation for Industrie 4.0 is the adaptation of the higher education to the requirements of this vision, in particular the engineering education. In this work, we introduce a road map consisting of three pillars describing the changes/enhancements to be conducted in the areas of curriculum development, lab concept, and student club activities. We also report our current application of this road map at the Turkish-German University, Istanbul.

Information and communication technology (ICT) is getting smaller and faster at a dashing pace and is increasingly pervading production technology. This penetration of ICT within and across production technology enables companies to aggregate and utilize massive amounts of data of production processes, both horizontally (across different products) and vertically (from machine level, over the shop floor, to the supply chain level). Presumably, this yields in Smart Factories with adaptable manufacturing processes that adjust to different goals, such as performance, product quality, or resource efficiency.
But the increasing amount of available data also raises considerable challenges: Strategic decisions still depend on humans in the loop who have to perceive and process increasingly complex multi dimensional data sets and to make decisions whose effects are increasingly difficult to forecast. This paper is concerned with the potential of the human factor. Along with three case studies, we demonstrate the potential of human factors in the development of applications for Smart Factories and enterprises in the era of Industry 4.0.
The paper concludes with a set of guidelines and methods for the user centered development of applications for Industry 4.0.

Industry 4.0 is originally a future vision described in the high-tech strategy of the German government that is conceived upon information and communication technologies like Cyber-Physical Systems, Internet of Things, Physical Internet, and Internet of Services to achieve a high degree of flexibility in production (individualized mass production), higher productivity rates through real-time monitoring and diagnosis, and a lower wastage rate of material in production. An important part of the tasks in the preparation for Industry 4.0 is the adaption of the higher education to the requirements of this vision, in particular the engineering education. In this work, we introduce a road map consisting of three pillars describing the changes/enhancements to be conducted in the areas of curriculum development, lab concept, and student club activities. We also report our current application of this road map at the Turkish German University, Istanbul.

The Internet of Things will influence how production systems of the future will work. An expected change is the increase in complexity when production system will start communicating with each other. This complexity can be managed by applying socio-technical approaches. This includes analyzing a production system regarding the domains: tasks, actors, technology, and structure. We identified three topics per domain that we think need further investigation, as they may influence complexity to a strong degree. For tasks we suggest looking into urgency, habituation, and strategies; for actors we suggest looking into skills, human factors, and user diversity. In the field of technology we find visualization, decision support, and interactions to be most pressing, while in the field of structure we see responsibility, delegation, and communication.

Die Digitalisierung biete Chancen und Risiken, gerade in der Autoindustrie stärke sie die Wettbewerbsfähigkeit - in Reaktion auf die Sachzwänge des Weltmarkts. In dieser Sichtweise erscheint die neue Technologie als Subjekt, angetreten zur Innovation ganzer Branchen. Dagegen fragt Peter Schadt, wer sie zu welchem Zweck ins Werk setzt. Indem er handelnde Akteure benennt, lässt sich die Digitalisierung als Mittel zur Durchsetzung von Interessen begreifen. Und das mit weitreichenden Folgen für die Arbeitsbedingungen bei VW, BMW und Co. Zugleich geht er gewerkschaftlichen Handlungsspielräumen im Rahmen der Industrie 4.0 nach. So lassen sich auf mehreren Ebenen Veränderungen von >Kooperation und Konkurrenz< in den Blick nehmen: Zwischen Kapitaleignern und Beschäftigten, zwischen verschiedenen Unternehmen sowie zwischen Lohnabhängigen. Der Band schließt mit einem Ausblick auf die Konkurrenz nach außen: die Rivalität der deutschen Autoindustrie mit dem US-amerikanischen Pendant zur Industrie 4.0, dem »Industrial Internet«, und dem Programm »China 2025«.

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This article sheds light on the pressing issue of software patents by giving an account of the approaches followed in Europe, the US and India. The occasion of this study is the adoption in 2016 of the final version of the Indian guidelines on the examination of computer-related inventions, which have been surprisingly overlooked in the legal literature. The main idea is that the Internet of Things will lead to a dramatic increase of applications for software patents and if examiners, courts, and legislators are not careful, there is a concrete risk of a surreptitious generalised grant of patents for computer programs as such (in Europe) and for abstract ideas without inventive concept (in the US). The clarity provided by the Indian guidelines, following a lively public debate, can constitute good practice that Europe and the US should take into account. Conversely, the sea of patent software looks very stormy in the US, where, after some reversals of the leading case Alice Corp v CLS Bank International, there seems to be the risk of swelling the ranks of speculative schemers who make it their business to watch the advancing wave of improvement, and gather its foam in the form of patented monopolies. Some good news, however, comes from a dissenting opinion that innovatively suggests bringing free speech into the reasoning on patents.

PLEASE CITE AS: Guido NOTO LA DIEGA, Software patents and the Internet of Things in Europe, the United States, and India, in European Intellectual Property Review, 2017, 39(3), 173-184.

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In the second half of the 2010s, AI has become a major hype across Chinese tech industries, venture capital investment, and government policy. The BAT national champions (Baidu, Alibaba and Tencent) have heavily invested in AI research and development, opening research centers in China and abroad to attract global talent, while thousands of startups have jumped on the AI hype to attract investment and reap the benefits of generous government funding. In a wave of innovation rhetoric closely resembling the previous hypes around Web 2.0 and Big Data, AI has become the most recurring buzzword in Chinese tech: besides its more predictable applications (industrial automation, self-driving cars, natural language processing and computer vision), almost everything in China – from e-commerce platforms to public utilities – is revamped as an ostensibly ‘AI-powered’ service. Drawing on research into the development of artificial intelligence technologies and products, this chapter charts China’s AI hype via its representation across government policy documents, industry advertisement, commercial products and popular culture. As trends and catchphrases travel between corporate boardrooms and policy think tanks to propaganda materials and music videos, the interplay between technical innovation and planned development reveals how AI is constructed, in real time, at the intersection of sociotechnical constraints and national imaginations.

Industry 4.0, or the fourth industrial revolution, that blurs the boundaries between the physical and the digital, is underpinned by vast amounts of data collected by sensors that monitor processes and components of smart factories that continuously communicate amongst one another and with the network hubs via the internet of things. Yet, collection of those vast amounts of data, which are inherently imperfect and burdened with uncertainties and noise, entails costs including hardware and software, data storage, processing, interpretation and integration into the decision-making process to name just the few main expenditures. This paper discusses a framework for rationalizing the adoption of (big) data collection for Industry 4.0. The pre-posterior Bayesian decision analysis is used to that end and industrial process evolution with time is conceptualized as a stochastic observable and controllable dynamical system. The chief underlying motivation is to be able to use the collected data in such a way as to derive the most benefit from them by trading off successfully the management of risks pertinent to failure of the monitored processes and/or its components against the cost of data collection, processing and interpretation. This enables formulation of optimization problems for data collection, e.g. for selecting the monitoring system type, topology and/or time of deployment. An illustrative example utilizing monitoring of the operation of an assembly line and optimizing the topology of a monitoring system is provided to illustrate the theoretical concepts.

Abstract In the Internet of Things (IoT), it should be possible to create ad hoc and loosely coupled information flows between any kinds of products, devices, computers, users and information systems in general when and as needed. However, this is still challenging to achieve in practice due to the lack of sufficiently generic and standardized interfaces for creating the needed information flows between all of the devices and systems that form the IoT. In the LinkedDesign project, such interoperability is also needed between the different software components that are used for building the Linked Engineering and mAnufacturing Platform (LEAP). This chapter presents the two interoperability standards developed for this purpose, which are published by The Open Group: Open Messaging Interface (O-MI) and Open Data Format (O-DF). This chapter describes the design principles and provides a description of the standards, including implementation principles and examples of real-life implementations.