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On blockchain and its integration with IoT. Challenges and opportunities

Secure integration of IoT and Cloud Computing

Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.

Digital Twin: Enabling Technologies, Challenges and Open Research

Digital twin can be defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision making. Recent advances in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, data processing and management tools bring the promise of digital twins and their impact on society closer to reality. Digital twinning is now an important and emerging trend in many applications. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, there can be no doubt that a digital twin plays a transformative role not only in how we design and operate cyber-physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. In this work, we review the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective. Our aim is to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.

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Digital Twin: Values, Challenges and Enablers From a Modeling Perspective

State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing

Machine Learning (ML) and Artificial Intelligence (AI) have a dependency on data sources to train, improve and make predictions through their algorithms. With the digital revolution and current paradigms like the Internet of Things, this information is turning from static data into continuous data streams. However, most of the ML/AI frameworks used nowadays are not fully prepared for this revolution. In this paper, we proposed Kafka-ML, an open-source framework that enables the management of TensorFlow ML/AI pipelines through data streams (Apache Kafka). Kafka-ML provides an accessible and user-friendly Web User Interface where users can easily define ML models, to then train, evaluate and deploy them for inference. Kafka-ML itself and its deployed components are fully managed through containerization technologies, which ensure its portability and easy distribution and other features such as fault-tolerance and high availability. Finally, a novel approach has been introduced to manage and reuse data streams, which may lead to the (no) utilization of data storage and file systems.

Kafka-ML: connecting the data stream with ML/AI frameworks

The Internet of Things (IoT) is an emerging technology that is growing continuously thanks to the number of devices deployed and data generated. Nevertheless, an upper layer to abstract the limitations of storing, processing, battery and networking is becoming a mandatory need in this field. Cloud Computing is an especially suitable technology that can supplement this field in the limitations mentioned. However, the current platforms are not prepared for querying large amounts of data with arbitrary functions in real-time, which are necessary requirements for real-time systems. This paper presents $\lambda $-CoAP architecture, a novel paradigm not introduced yet to the best of our knowledge, which proposes an integration of Cloud Computing and Internet of Things through the Lambda Architecture (LA) and a Constrained Application Protocol (CoAP) middleware. The $\lambda $-CoAP architecture has the purpose to query, process and analyze large amounts of IoT data with arbitrary functions in real-time. On the other hand, the CoAP middleware is a lightweight middleware that can be deployed in resource constrained devices and allows the way of the IoT towards the Web of Things. Moreover, the $\lambda $-CoAP also contains a set of components with well defined interfaces for querying, managing, and actuating over the system.

/pdf/lambda-coap-an-internet-of-things-and-cloud-computing-2gql6sidav.pdf

$$\lambda $$-CoAP: An Internet of Things and Cloud Computing Integration Based on the Lambda Architecture and CoAP

The rapid development in low-cost sensor and wireless communication technology has made it possible for a large number of devices to coexist and exchange information autonomously. It has been predicted that a substantial number of devices will be able to exchange and provide information about an environment with the goal of improving our lives, under the well-known paradigm of the Internet of Things (IoT). One of the main applications of these kinds of devices is the monitoring of scenarios. In order to improve the current wine elaboration process, this paper presents a real-time monitoring system to supervise the status of wine casks. We have focused on a special kind of white wine, called Fino, principally produced in Andalusia (Southern Spain). The process by which this kind of wind is monitored is completely different from that of red wine, as the casks are not completely full and, due to the fact that they are not renewed very often, are more prone to breakage. A smart cork prototype monitors the structural health, the ullage, and the level of light inside the cask and the room temperature. The advantage of this smart cork is that it allows winemakers to monitor, in real time, the status of each wine cask so that, if an issue is detected (e.g., a crack appears in the cask), they can act immediately to resolve it. Moreover, abnormal parameters or incorrect environmental conditions can be detected in time before the wine loses its desired qualities. The system has been tested in “Bodegas San Acacio,” a winery based in Montemayor, a town in the north of Andalusia. Results show that the use of such a system can provide a solution that tracks the evolution and assesses the suitability of the delicate wine elaboration process in real time, which is especially important for the kind of wine considered in this paper.

Cristian Martín

Papers

On blockchain and its integration with IoT. Challenges and opportunities

State-of-the-art, challenges, and open issues in the integration of Internet of things and cloud computing

Kafka-ML: connecting the data stream with ML/AI frameworks

$$\lambda $$-CoAP: An Internet of Things and Cloud Computing Integration Based on the Lambda Architecture and CoAP

Smart Winery: A Real-Time Monitoring System for Structural Health and Ullage in Fino Style Wine Casks.