| 1. |
- Javed, Salman, 1982-, et al.
(författare)
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An approach towards demand response optimization at the edge in smart energy systems using local clouds
- 2023
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Ingår i: Smart Energy. - : Elsevier. - 2666-9552. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- The fourth and fifth industrial revolutions (Industry 4.0 and Industry 5.0) have driven significant advances in digitalization and integration of advanced technologies, emphasizing the need for sustainable solutions. Smart Energy Systems (SESs) have emerged as crucial tools for addressing climate change, integrating smart grids and smart homes/buildings to improve energy infrastructure. To achieve a robust and sustainable SES, stakeholders must collaborate efficiently through an energy management framework based on the Internet of Things (IoT). Demand Response (DR) is key to balancing energy demands and costs. This research proposes an edge-based automation cloud solution, utilizing Eclipse Arrowhead local clouds, which are based on Service-Oriented Architecture that promotes the integration of stakeholders. This novel solution guarantees secure, low-latency communication among various smart home and industrial IoT technologies. The study also introduces a theoretical framework that employs AI at the edge to create environment profiles for smart buildings, optimizing DR and ensuring human comfort. By focusing on room-level optimization, the research aims to improve the overall efficiency of SESs and foster sustainable energy practices.
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| 2. |
- Javed, Salman, 1982-
(författare)
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Approach Towards Engineering Microservice-Oriented Composable Ecosystems for Smart Industries
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The emergence of smart and integrated industrial ecosystems is replacing traditional manufacturing, where operations are more digitalized and automated. For communication and cooperation, these operations require seamless integration of the devices to ensure interoperability in a secure, reliable, and adaptable environment. Designing a solution with these capabilities raises concerns about automation and engineering optimization. More recently, the rapid progression toward Industry 5.0 (I5.0) is further reshaping the landscape of smart industry ecosystems, necessitating innovative engineering and management solutions based on its core values of resilience, sustainability, and human-centricity.This thesis investigates these challenges and requirements by emphasizing adaptable, secure, reliable, composable, and scalable communication in complex industrial ecosystems. Central to this work is a local cloud-based collaboration approach to the design and development of composable ecosystems using microservices, which facilitate the integration of various information technology and operational technology (IT/OT) systems prevalent in smart industries. These encompass industrial and smart home Internet of Things (IoT)-based smart industry ecosystems and smart energy systems. Using the microservice-oriented Eclipse Arrowhead framework, this research provides scalable and adaptable solutions that adhere to the core values of I5.0. This research also bridges the integration gap between smart manufacturing ecosystems and smart home IoT technologies, laying the foundation for interconnected smart factories and improved energy management systems.Collaboration between IT/OT components and stakeholders in smart industry and smart energy ecosystems improves competitiveness, productivity, and informed decision making, thereby filling a critical research gap. The thesis presents a cloud-based collaborative learning (CCL) approach for automated condition monitoring in smart industry ecosystems. The thesis exemplifies the use cases of wind farms and smart manufacturing ecosystems that use CCL to address the issues of dynamic learning and real-time data sharing between various IoT-based IT/OT systems. Unlike traditional smart manufacturing models that focus primarily on automation and cost efficiency, CCL-based and I5.0 core value-driven ecosystems support human-centricity, sustainability, and resilience. Lastly, the thesis investigates the optimization of demand response based on collaboration among stakeholders in smart energy systems using edge-based automation clouds. The proposed approach promotes resilient and sustainable smart city demand response strategies by ensuring human comfort, security, data privacy, and all stakeholder integration in smart energy systems.
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| 3. |
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| 4. |
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| 5. |
- Javed, Salman, et al.
(författare)
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Smart Adapter System Architecture for Seamless and Scalable Integration of Industry and Smart Home IoT
- 2022
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Ingår i: IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society. - : IEEE. - 9781665480253
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Konferensbidrag (refereegranskat)abstract
- Integrating smart manufacturing ecosystems with industrial-grade smart energy and building automation systems enables real-time adaptation to changes in demands and factory conditions, the supply chain, and the needs of customers and society. However, integrating, managing, and controlling data exchange usually incurs high overheads in such a collaborative industrial environment. Smart home IoT technologies are a cost-effective solution for smart energy and building automation systems; they are not fully interoperable with industrial IoT technologies. This paper presents a mechanism to solve this interoperability problem using the Eclipse Arrowhead framework. The proposed solution provides a microservice-oriented architecture to develop protocol-specific smart adapter systems for the Arrowhead framework. These smart adapter systems provide seamless and highly scalable integrations between smart home and industrial IoT technologies. Our solution enables smart manufacturing ecosystems to meet Industry 5.0’s core values and reduce their carbon footprint to save the planet. We present the performance of our solution using an example from a real-world use case of a smart heating system scenario in a smart factory.
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| 6. |
- Kolluru, Katyayani Kiranmayee, et al.
(författare)
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An AAA Solution for Securing Industrial IoT Devices using Next Generation Access Control
- 2018
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Konferensbidrag (refereegranskat)abstract
- Industry 4.0 is advancing the use of Internet of Things (IoT) devices in industrial applications, which enablesefficient device-to-device (D2D) communication. However, these devices are often heterogeneous in nature, i.e. from different manufacturers, use different protocols, etc. and adds requirements such as security, interoperability, etc.To address these requirements, the Service-Oriented Architecture-Based (SOA) Arrowhead Framework was previously proposed using the concept of local clouds. These local clouds provide a set of mandatory and support core systems to enable industrial automation applications. One of these mandatory core systems is an Authentication, Authorisationand Accounting (AAA) system, which is used to authenticate and provide access control to the devices in a local cloud. In an industrial context, with multiple stakeholders, the AAA mustsupport fine-grain access control. For example, in a distributed control loop, a controller should only have read access to its sensor such as a flow meter and write access to its actuator, such as a valve. The controller should not have access to anyother information besides what is needed to implement the desired functionality. In this work, an NGAC-based AAA solution to achieve fine-grain service level access control between IoT devices has been proposed and implemented. The solution is presented using a district heating use case.
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| 7. |
- Labra Caso, Fernando, et al.
(författare)
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Towards Interoperability Mismatch Identification. An Expert System Approach
- 2022
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Ingår i: IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society. - : IEEE. - 9781665480253
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Konferensbidrag (refereegranskat)abstract
- Lack of interoperability is a growing problem for the industry and the adoption of new technologies. Despite the current efforts in digitization and automatization, challenges regarding the integration and compatibility between heterogeneous devices and systems remain open. In the literature, new solutions can be found. To adopt them, the identification of the differences between service interfaces that hamper communication is critical. Automating the analysis and identification, which is currently based on manual operations, would significantly reduce the engineering effort and associated costs.This paper proposes a novelty approach to autonomously select the most suitable solution to address interoperability problems in the communication between heterogeneous systems. This work introduces the mismatch analysis system, designed as an expert system through the use of production rules, frames and fuzzy logic. The mismatch analysis system calculates the degree of compatibility and uncertainty between service interfaces and decides the best course of action to assist the communication between systems. The system has been successfully designed, implemented, integrated, and tested in the Arrowhead framework, demonstrating high potential.
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| 8. |
- Nilsson, Mattias, et al.
(författare)
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Integration of Neuromorphic AI in Event-Driven Distributed Digitized Systems: Concepts and Research Directions
- 2023
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Ingår i: Frontiers in Neuroscience. - : Frontiers Media S.A.. - 1662-4548 .- 1662-453X. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Increasing complexity and data-generation rates in cyber-physical systems and the industrial Internet of things are calling for a corresponding increase in AI capabilities at the resource-constrained edges of the Internet. Meanwhile, the resource requirements of digital computing and deep learning are growing exponentially, in an unsustainable manner. One possible way to bridge this gap is the adoption of resource-efficient brain-inspired “neuromorphic” processing and sensing devices, which use event-driven, asynchronous, dynamic neurosynaptic elements with colocated memory for distributed processing and machine learning. However, since neuromorphic systems are fundamentally different from conventional von Neumann computers and clock-driven sensor systems, several challenges are posed to large-scale adoption and integration of neuromorphic devices into the existing distributed digital–computational infrastructure. Here, we describe the current landscape of neuromorphic computing, focusing on characteristics that pose integration challenges. Based on this analysis, we propose a microservice-based conceptual framework for neuromorphic systems integration, consisting of a neuromorphic-system proxy, which would provide virtualization and communication capabilities required in distributed systems of systems, in combination with a declarative programming approach offering engineering-process abstraction. We also present concepts that could serve as a basis for the realization of this framework, and identify directions for further research required to enable large-scale system integration of neuromorphic devices.
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| 9. |
- Palm, Emanuel, 1987-, et al.
(författare)
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Syntactic Translation of Message Payloads Between At Least Partially Equivalent Encodings
- 2019
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Ingår i: Proceedings. - : IEEE. ; , s. 812-817
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Konferensbidrag (refereegranskat)abstract
- Recent years have seen a surge of interest in using IoT systems for an increasingly diverse set of applications, with use cases ranging from medicine to mining. Due to the disparate needs of these applications, vendors are adopting a growing number of messaging protocols, encodings and semantics, which result in poor interoperability unless systems are explicitly designed to work together. Key efforts, such as Industry 4.0, put heavy emphasis on being able to compose arbitrary IoT systems to create emergent applications, which makes mitigating this barrier to interoperability a significant objective. In this paper, we present a theoretical method for translating message payloads in transit between endpoints, complementing previous work on protocol translation. The method involves representing and analyzing encoding syntaxes with the aim of identifying the concrete translations that can be performed without risk of syntactic data loss. While the method does not facilitate translation between all possible encodings or semantics, we believe that it could be extended to enable such translation.
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| 10. |
- Paniagua, Cristina
(författare)
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Architectural approach for Autonomous System of Systems Interoperability
- 2019
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The current technological environment is evolving increasingly fast, and the development of new devices, technologies, and architectures has opened an emergent era where the digital and physical world work together. The implementation and use of systems based on a service-oriented architecture (SOA) in conjunction with the Internet of Things (IoT) and cyberphysical systems (CPS) have been extended during the last decades in numerous scenarios in industry and other domains. However, some of the major barriers to this approach are the lack of interoperability and the amount of engineering effort required for their integration. The research presented in this thesis targets issues related to digitalization and automation. It is framed by the Industry 4.0 paradigm, which promotes the rise of efficiency and sustainability on industrial production. The interoperability between heterogeneous systems and different domains is one of the main challenges of Industry 4.0. The quest for solutions that help to increase interoperability is an important part of this research. This thesis proposes a set of architectural design principles and tools in order to reduce engineering effort by means of finding solutions that enable autonomous integration and increase interoperability without human intervention. The research is focused on the IoT field, taking into account resource-constrained devices, system of systems integration, and data models. A detailed investigation of various interoperability mismatch problems is presented in this thesis. The proposed solution is an adapter system that can aid in the generation of new service consumer interfaces at both compile-time and run-time. The proposed approach requires a new point of view in the service description field that can provide a holistic description of the information required for the generation of consumer interfaces.In addition, aspects related to interoperability, such as the multiple IoT frameworks in the current market, naming conventions, syntactic modeling and translation, and security, are also partially analyzed. On a separate track, service composition in resource-constrained devices is analyzed in terms of latency, using the orchestration provided by the Arrowhead Framework.
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