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Generating SPARQL-Constraints for Consistency Checking in Industry 4.0 Scenarios
Full text linkA smart manufacturing line consists of multiple connected machines. These machines communicate with each other over a network, to solve a common task. Such a scenario can be located in the Internet of Things (IoT) area. An individual machine can be perceived as an IoT device. Due to machine to machine communication, a huge amount of data is generated during manufacturing. This emerging data flow is an essential part of today's industry, as analyzing data helps improving processes and thus, product quality. To adequately make use of the collected data, we require a high level of data quality. In our work, we address the issue of inconsistent data in smart manufacturing and present an approach to automatically generate SPARQL queries for validation
IoT-PMA: Patient Health Monitoring in Medical IoT Ecosystems
Full text linkThe emergence of the Internet of Things (IoT) and the increasing number of cheap medical devices enable geographically distributed healthcare ecosystems of various stakeholders. Such ecosystems contain different application scenarios, e.g., (mobile) patient monitoring using various vital parameters such as heart rate signals. The increasing number of data producers and the transfer of data between medical stakeholders introduce several challenges to the data processing environment, e.g., heterogeneity and distribution of computing and data, lowlatency processing, as well as data security and privacy. Current approaches propose cloud-based solutions introducing latency bottlenecks and high risks for companies dealing with sensitive patient data. In this paper, we address the challenges of medical IoT applications by proposing an end-to-end patient monitoring application that includes NebulaStream as the data processing system, an easy-to-use UI that provides ad-hoc views on the available vital parameters, and the integration of ML models to enable predictions on the patients' health state. Using our end-to-end solution, we implement a real-world patient monitoring scenario for hemodynamic and pulmonary decompensations, which are dynamic and life-threatening deteriorations of lung and cardiovascular functions. Our application provides ad-hoc views of the vital parameters and derived decompensation severity scores with continuous updates on the latest data readings to support timely decision-making by physicians. Furthermore, we envision the infrastructure of an IoT ecosystem for a multi-hospital scenario that enables geo-distributed medical participants to contribute data to the application in a secure, private, and timely manner
IoT Hub as a Service (HaaS): Data-Oriented Environment for Interactive Smart Spaces
Full text linkSmart devices around us produce a considerable volume of data and interact in a wide range of scenarios that guide the evolution of the Internet of Things (IoT). IoT adds informative and interactive aspects to our living spaces, converting them into smart spaces. However, the development of applications is challenged by the fragmented nature due to the vast number of different IoT things, the format of reported information, communication standards, and the techniques used to design applications. This paper introduces IoT Hub as a Service (HaaS), a data-oriented framework to enable communication interoperability between the ecosystem's entities. The framework abstracts things' information, reported data items, and developers' applications into programmable objects referred to as Cards. Cards represent specific entities and interactions of focus with meta-data. The framework then indexes cards' meta-data to enable interoperability, data management, and application development. The framework allows users to create virtual smart spaces (VSS) to define cards' accessibility and visibility. Within VSS, users can identify accessible data items, things to communicate, and authorized applications. The framework, in this paper, defines four types of Cards to represent: participating IoT things, data items, VSS, and applications. The proposed framework enables the development of synchronous and asynchronous applications. The framework dynamically creates, updates, and links the cards throughout the life-cycle of the different entities. We present the details of the proposed framework and show how our framework is advantageous and applicable
Building Next Generation IoT Infrastructure for Enabling M2M Crypto Economy
Full text linkAs Bitcoin and other cryptocurrencies are becoming part of our lives, there is a growing interest to enable using them in our daily lives even for micropayments. This interest stems from many factors including privacy, convenience and overhead/fraud that comes with credit cards. In this regard, Internet of Things (IoT) devices can also benefit from this feature for enabling touchless payments for users. However, there is even a bigger opportunity there considering the nature and diversity of very large-scale unattended IoT devices. The integration of any IoT device with blockchain including cryptocurrencies and smart contracts can trigger a machine-to-machine (M2M) economy revolution by streamlining business among IoT devices. Under such a future business model, IoT devices can autonomously request a service and make a payment in return. Such a large-scale ecosystem should rely on various components thus requiring a paradigm shift on the current design and understanding of the IoT systems. In particular, decentralized architecture of blockchain with cryptocurrency and smart contract capability can be a key enabler. In this vision paper, we advocate the need and necessary elements of a M2M crypto economy infrastructure and investigate the role of blockchain in realizing this vision. We specifically focus on the advantages and challenges of blockchain-based systems along with the existing proposed solutions. We then offer several future directions in creating such a M2M economy
Network Metrics Detection to Support Internet of Things Application Orchestration
Full text linkSoftware DefinedWireless Sensor Networks (SDWSN) play an important role to serve as an infrastructure to Internet of Things (IoT) applications. In order to improve coverage, reduce costs, and make better use of the available resources, sharing the infrastructure among multiple applications is necessary. Works in the literature aim to enable resource sharing by allocating applications dynamically according to the resources available on the node. However, these works do not monitor if a node stops complying with application requirements once the application is allocated. Thus, network metrics detection is essential to identify nodes that are not able to comply with the application requirements. In this paper, we present the IT-SDN Manager architecture which is composed of a monitoring module and a resource orchestrator. The monitoring module monitors the network metrics, enabling the orchestrator to identify nodes that reach a certain threshold for energy available and packet loss. This threshold configuration depends on the metric characteristics. For packet loss, we present a study showing how it should be defined according to the network size and applications executed in the network. In order to evaluate the orchestrator detection rate, we set two application requirements to identify nodes that reach 90% of available energy and packet loss greater than the obtained threshold for each scenario studied. Results from the simulations executed show that the resource orchestrator detects all the nodes that reach the available energy threshold, and at least 85%, with an average of 97%, of the nodes that reach the packet loss threshold
Monitoring of Stream Processing Engines Beyond the Cloud: An Overview
Full text linkThe Internet of Things (IoT) is rapidly growing into a network of billions of interconnected physical devices that constantly stream data. To enable data-driven IoT applications, data management systems like NebulaStream have emerged that manage and process data streams, potentially in combination with data at rest, in a heterogeneous distributed environment of cloud and edge devices. To perform internal optimizations, an IoT data management system requires a monitoring component that collects system metrics of the underlying infrastructure and application metrics of the running processing tasks. In this paper, we explore the applicability of existing cloud-based monitoring solutions for stream processing engines in an IoT environment. To this end, we provide an overview of commonly used approaches, discuss their design, and outline their suitability for the IoT. Furthermore, we experimentally evaluate different monitoring scenarios in an IoT environment and highlight bottlenecks and inefficiencies of existing approaches. Based on our study, we show the need for novel monitoring solutions for the IoT and define a set of requirements
Streaming Data through the IoT via Actor-Based Semantic Routing Trees
Full text linkThe Internet of Things (IoT) enables the usage of resources at the edge of the network for various data management tasks that are traditionally executed in the cloud. However, the heterogeneity of devices and communication methods in a multi-tiered IoT environment (cloud/fog/edge) exacerbates the problem of deciding which nodes to use for processing and how to route data. In addition, both decisions cannot be made only statically for the entire lifetime of an application, as an IoT environment is highly dynamic and nodes in the same topology can be both stationary and mobile as well as reliable and volatile. As a result of these different characteristics, an IoT data management system that spans across all tiers of an IoT network cannot meet the same availability assumptions for all its nodes. To address the problem of choosing ad-hoc which nodes to use and include in a processing workload, we propose a networking component that uses a-priori as well as ad-hoc routing information from the network. Our approach, called Rime, relies on keeping track of nodes at the gateway level and exchanging routing information with other nodes in the network. By tracking nodes while the topology evolves in a geo-distributed manner, we enable efficient communication even in the case of frequent node failures. Our evaluation shows that Rime keeps in check communication costs and message transmissions by reducing unnecessary message exchange by up to 82:65%
Realizing the Digital Twin Transition for Smart Cities
Full text linkThe digital twin transition for cities is expected to improve, among others, living quality, carbon footprint and generate new business opportunities across different organizations. However, as cities consist of many separate entities that are in close and frequent interaction with each other, it is not possible to simply apply digital twin concepts from the engineering and manufacturing domains in a silo-ed fashion for each entity. In this paper, we distill the requirements and challenges to develop digital twins for smart cities based on a typical smart city use case. We follow with a first systematic approach to address them in a data-driven fashion to realize the digital twin transition for cities
Generating Sound from the Processing in Semantic Web Databases
Full text linkDatabases process a lot of intermediate steps generating many intermediate results during data processing for answering queries. It is not easy to understand these complex tasks and algorithms for students, developers and all those interested in databases. For this purpose, an additional medium is sonification, which maps data to auditory dimensions and offers a new audible experience to their listeners. Hence, we propose a sonification of query processing paired with a corresponding visualization both integrated in a web application. In a demonstration of our approach and in an extensive user evaluation we show that listeners increase their understanding of the operators' functionality and sonification supports easy remembering of requirements like merge joins work on sorted input. Furthermore, new ways of analyzing query processing are possible with our proposed sonification approach
Massive Wireless Energy Transfer with Multiple Power Beacons for Very Large Internet of Things
Full text linkThe Internet of Things (IoT) comprises an increasing number of low-power and low-cost devices that autonomously interact with the surrounding environment. As a consequence of their popularity, future IoT deployments will be massive, which demands energy-efficient systems to extend their lifetime and improve the user experience. Radio frequency wireless energy transfer has the potential of powering massive IoT networks, thus eliminating the need for frequent battery replacement by using the so-called power beacons (PBs). In this paper, we provide a framework for minimizing the sum transmit power of the PBs using devices' positions information and their current battery state. Our strategy aims to reduce the PBs' power consumption and to mitigate the possible impact of the electromagnetic radiation on human health. We also present analytical insights for the case of very distant clusters and evaluate their applicability. Numerical results show that our proposed framework reduces the outage probability as the number of PBs and/or the energy demands increase