No / Abstract: Internet of Things (IoT) aims to enable the interconnection of a large number of smart devices (things) using a combination of networks and computing technologies. But an influx of interconnected things makes a greater demand on the underlying communication networks and affects the quality of service (QoS). This paper investigates into the QoS of delay sensitive things and the corresponding traffic they generate over the network. Things such as security alarms, cameras, etc, generate delay sensitive information that must be communicated in a real time. Such things have heterogeneous features with limited buffer capacity, storage and processing power. Thus the most commonly used Best Effort service model cannot be an attractive mechanism to treat delay sensitive traffic. This paper proposes a cost-effective analytical model for a finite capacity queueing system with pre-emptive resume service priority and push-out buffer management scheme. Based on the analytical model various simulation results are generated in order to analyse the mean queue length and the blocking probability of high and low priority traffic for system with various capacities.

Yes / Web of Things (WoT) can be considered as a merger of newly emerging paradigms of Internet of Things (IoT) and cloud computing. Rapidly varying, highly volatile and heterogeneous data traffic is a characteristic of the WoT. Hence, the capture, processing, storage and exchange of huge volumes of data is a key requirement in this environment. The crucial resources in the WoT are the sensing devices and the sensing data. Consequently, access control mechanisms employed in this highly dynamic and demanding environment need to be enhanced so as to reduce the end-to-end latency for capturing and exchanging data pertaining to these underlying resources. While there are many previous studies comparing the advantages and disadvantages of access control mechanisms at the algorithm level, vary few of these provide any detailed comparison the performance of these access control mechanisms when used for different data handling procedures in the context of data capture, processing and storage. This study builds on previous work on token-based access control mechanisms and presents a comparison of two different approaches used for handling sensing devices and data in the WoT. It is shown that the aggregated data submission approach is around 700% more efficient than the serial payload submission procedure in reducing the round-trip response time.

Yes / Welcome to this special issue of the Future Generation Computer Systems (FGCS) journal. The special issue compiles seven technical contributions that significantly advance the state-of-the-art in exploration of Internet of Things (IoT) generated big data using semantic web techniques and technologies.

Yes / With the advancement of disruptive new technologies, there has been a considerable focus on personalisation as an important component in nurturing users' engagement. In the context of smart cities, Internet of Things (IoT) offer a unique opportunity to help empower citizens and improve societies' engagement with their governments at both micro and macro levels. This study aims to examine the role of perceived value of IoT in improving citizens' engagement with public services. A survey of 313 citizens in the UK, engaging in various public services, enabled through IoT, found that the perceived value of IoT is strongly influenced by empowerment, perceived usefulness and privacy related issues resulting in significantly affecting their continuous use intentions. The study offers valuable insights into the importance of perceived value of IoT-enabled services, while at the same time, providing an intersectional perspective of UK citizens towards the use of disruptive new technologies in the public sector.

Yes / Technological advancements have been evolving for so long, particularly Internet of Things (IoT) technology that has seen an increase in the number of connected devices surpass non IoT connections. It has unlocked a lot of potential across different organisational settings from healthcare, transportation, smart cities etc. Unfortunately, these advancements also mean that cybercriminals are constantly seeking new ways of exploiting vulnerabilities for malicious and illegal activities. IoT is a technology that presents a golden opportunity for botnet attacks that take advantage of a large number of IoT devices and use them to launch more powerful and sophisticated attacks such as Distributed Denial of Service (DDoS) attacks. This calls for more research geared towards the detection and mitigation of botnet attacks in IoT systems. This paper proposes a feature selection approach that identifies and removes less influential features as part of botnet attack detection method. The feature selection is based on the frequency of occurrence of the value counts in each of the features with respect to total instances. The effectiveness of the proposed approach is tested and evaluated on a standard IoT dataset. The results reveal that the proposed feature selection approach has improved the performance of the botnet attack detection method, in terms of True Positive Rate (TPR) and False Positive Rate (FPR). The proposed methodology provides 100% TPR, 0% FPR and 99.9976% F-score.

The manufacturing domain has been experiencing several revolutions over the years that have been shaping not only the design and management of processes but also their core drivers and value propositions. Industry 4.0 unleashes many enabling technologies such as the Internet of Things sensors and machine learning algorithms to boost industries’ productivity through data-driven process monitoring, rather than relying on operation manager experience. However, this fourth revolution does not set as strategic goals sustainability drivers (e.g., social and environmental) triggered by external forces that undermine modern societies. European policymakers address this structural limitation by defining the Industry 5.0 paradigm focused on human-centric and sustainable value creations. In this fast-paced landscape, this doctoral thesis targets the limitations of Industry 4.0 related contributions and defines three research questions to demonstrate the competitive advantages in designing cyber-physical systems to monitor the efficiency and sustainability of human-centric manufacturing environments. The human-centricity is an important feature of this work because, despite the rise of automation, workers represent a strategic and fragile resource in industrial plants. Therefore, Internet of Things technologies are leveraged to achieve a digital representation of workers. The acquired measurements are fed into computational algorithms to appreciate data-driven managerial insights based on the returned Key Performance and Risk indicators. The contributions of this thesis can be conceptually divided into two separate streams. The first demonstrates the relevance of enhancing the operational visibility of in-plant operations by exploiting Real Time Locating Systems acquisition layers. Although this technology indoor locates whichever (manufacturing) entity and asset in a defined coverage area, the returned workers’ positions fail to evaluate systems’ performances and sustainability. For this purpose, density-based machine learning algorithms and neural networks are introduced and validated to embed operational metrics into Decision Support Systems. Multidimensional managerial insights prove the consistency of this methodology in three different manufacturing environments. Considering production settings, managers appreciate the uptimes of workers and resource utilizations while evaluating the layout configurations and the related efficiency in manual material handling activities. This twofold level of analysis enables to eventually increase in-plant productivity while optimizing workers’ efforts in replenishment routes. The logistic investigation offers similar takes by monitoring the Overall Equipment Effectivness of manual forklifts and the distribution of picking/depositing activities in storage areas. Potential inefficiencies provide valid input to optimize the performances while reducing the energy consumption of logistics vehicles. The second stream focuses on workers’ physical resilience during task executions. To achieve this purpose, ergonomic indices are largely adopted to mitigate work-related musculoskeletal disorders in the workforce. The European Assembly Worksheet screening tool is the most complete one focusing on several parameters ranging from working postures to exterted forces. The developed cyber-physical system mirrors in digital spaces workers’ operations through a multi-device acquisition layer. While a four-channel surface ElectroMyoGraphy and a network of markerless cameras acquire muscular contractions in upper limbs and body joints, a radio-frequency-based smart glove detects process interactions such as tool usages and component pickings and thus segments production activities. These digital measurements are fed into computational algorithms to automate the mentioned ergonomic assessment. The experimental campaign validates the proposed cyber-physical systems and draws several managerial insights. For instance, strong bending postures may highlight a poor workplace design suggesting the need of self-adjustable workstations to accommodate a diverse workforce. At the same time, worrisome exerted forces could require line rebalancing to fairly redistribute muscular activity rates among operators. In summary, this thesis represents a significant advancement in digital manufacturing, offering ready-to-deploy systems while outlining future research opportunities and applications.

I extended and adapted the current technology acceptance models and privacy research to the peculiar context of the COVID-19 pandemic to ascertain the effective "power" of IT in fighting such a pandemic. The research models developed for the purpose of this study contain peculiar modifications to the technological-personal-environmental (TPE) framework and privacy calculus model because of the unique technologies implemented and the peculiar pandemic scenario. I developed three studies that investigate the interaction between social, legal, and technical factors that affect the adoption of IoT devices and blockchain systems implemented to fight the spread of COVID-19. Essay 1 systematically reviews existing literature on the analysis of the social, legal, and technical components in addressing phenomena related to IoT architecture and blockchain technology. The employment of a comparable coding method allows finding which of the above components is prominent in relation to the study of IoT and blockchain. Essay 2 develops a technological acceptance model by integrating the TPE framework with new constructs, i.e., regulatory environment, epidemic ecosystem, pre-epidemic ecosystem, perceived social usefulness, and technical characteristics. Essay 3 further explores the interplay between social, legal, and technical factors toward the adoption of smart contracts in the context of the COVID-19 pandemic. Essay 3 integrates the privacy calculus model by introducing new constructs, i.e., technical characteristics, regulatory environment, and perceived social benefits. For both Essays 2 and 3, research surveys were developed and distributed to undergraduate and graduate students in a major university located in the US. The research hypotheses were tested using partial least square modeling.

Today the digital evolution is progressing rapidly. This entails both pros and cons concerning the security of devices. Despite the evolution, security has been left in the dark. This results in threats and vulnerabilities in devices, which could potentially be used by a hacker with the purpose of exploiting information. Security has not been a priority in industrial enterprises, even though industrial devices and other networked devices reside on the same network. The evolution of the infrastructure of the Internet has resulted in an increase of cyberattacks. These attacks used to target random individuals. The attacks of today are more intelligent, and hackers have changed their targets to specific enterprises to further exploit sensitive information, damage devices or for financial benefits. Safety in today’s industrial workplaces, such as firewalls, encryption and intrusion detection systems are not specifically designed to work in this type of environment. This leads to new threats and vulnerabilities which further leads to more exploited vulnerabilities. This formulate the following questions: Which are the most occurring threats and vulnerabilities today? What current methods and tools are suited for controlling security in IIoT-networks and its internal industrial devices? The purpose of this thesis was to examine the most occurring threats and vulnerabilities in IIoT-networks and its internal devices and reason among the methods to evaluate security in industrial enterprises. Lastly, an experiment in a real industrial workplace was conducted to attain a nuanced picture of the implementation of finding threats and vulnerabilities in industrial systems. In summary, there are a lot of different threats and vulnerabilities divided into categories and many tools are available to ensure the vulnerability. To conduct a test to find threats and vulnerabilities in an industrial enterprise, it needs to be ethically correct and the consequences carefully considered. The result of this thesis is a mapping and a demonstration of how threats and vulnerabilities are detected in an industrial workplace.

This thesis details the design of a protocol translator between the industrial-automation protocol OPC UA, and HTTP. The design is based on the architecture of the protocol translator of the Arrowhead framework, and is interoperable with all of its associated protocols. The design requirements are defined to comply with a service-oriented architecture (SOA) and RESTful interaction through HTTP, with minimal requirement of the consuming client to be familiar with OPC UA semantics. Effort is put into making translation as transparent as possible, but limits the scope of this work to exclude a complete semantic translation. The solution presented in this thesis satisfies structural- and foundational interoperability, and bridges interaction to be independent of OPC UA services. The resulting translator is capable of accessing the content of any OPC UA server with simple HTTP-requests, where addressing is oriented around OPC UA nodes.

Med begreppet "Internet of Things" menas att ett objekt ur den riktiga världen blir en del av internet. Tunabyggen i Borlänge planerar att implementera ett sådant informationssystem som med hjälp av sensorer och en ständig internetuppkoppling håller uppsikt över temperatur och luftfuktighet i utvalda lokaler. Det är ett enkelt system som till synes inte har så stora effekter på den nuvarande verksamheten. De ekonomiska effekterna går ofta att räkna på i förhand men effekterna på personal, miljö och rutiner kan glömmas bort. Vi har därför med detta examensarbete undersökt vilka inledande effekter som kan tänkas uppkomma efter implementering av ett nytt informationssystem med "Internet of Things" funktionalitet i en verksamhet. Detta sker inom kategorierna ekonomi, arbetsmiljö, miljöpåverkan och systemförvaltning. För att kunna besvara detta har vi gjort en fallstudie baserad på en scenariometodik som består av fyra faser. Fas 1, där vi fick vårt Case och skapade en förståelse för scenariofältet. Fas 2, där vi identifierade nyckelfaktorer. Detta har gjorts genom en litteraturstudie samt intervju med berörd personal på Tunabyggen. Fas 3, där analysen av dessa nyckelfaktorer skedde genom nulägesanalys och framtidsanalys av nyckelfaktorer. Fas 4, där vi genererade scenarier av de analyserade nyckelfaktorerna. Det har sedan gjorts en SWOT-analys för att belysa styrkor, svagheter, möjligheter och hot. Resultatet visar tydliga tecken på att det kommer att bli många effekter för Tunabyggen efter implementering av det nya informationssystemet som yttrar sig i alla kategorier. Slutsatsen är att vid implementation av ett informationssystem som detta är effekterna många. Detta är något som vi anser bör beaktas av alla verksamheter som har tankar på att införskaffa ett nytt informationssystem. De bör inte bara utvärdera informationssystem rent ekonomiskt utan borde ta i beaktning att det finns ett antal andra faktorer som har en avgörande roll om implementation av informationssystem ska bli lyckad. / The term "Internet of Things" refers to when an object from the real world becomes a part of the internet. Tunabyggen in Borlänge plans to implement an information system that will monitor temperature and humidity in selected facilities using a constant internet connection and different sensors. It is a simple system that doesn't seem to have a major impact on the current operations. The economic effects is often possible to calculate in advance, but the impact on staff, environment and routines may be forgotten. We have with this thesis examined the initial effects that may occur after the implementation of a new information system with Internet of Things functionality in a business, within the categories of economy, working environment, environmental impact and system management. To answer this we made a case study which is based on a scenario methodology that consists of four phases. Phase 1, where we got our case and created an understanding of the scenario field. Phase 2, identifying the key factors. It has been done through a literature study and interviews with relevant staff on Tunabyggen. Phase 3, where the analysis of these key factors were made through the situation and future analysis. Phase 4, where we generate scenarios of the analyzed key factors. Finally we have done a SWOT analysis to highlight the strengths, weaknesses, opportunities and threats. The results clearly show signs that there will be many effects for Tunabyggen after the implementation of the new information system, which manifests itself in all categories. The conclusion is that even the implementation of a menial information system like this one, the impacts are many. This is something that we believe should be considered by all companies that are thinking of acquiring a new system so they do not only evaluate IT-systems in economic terms, but also other factors that play a crucial role for the implementation of an information system to be successful.