Title Participants Abstract "IoF2020 - the Internet Of Meat: towards applications of Internet of Things in the meat supply chain" "Jarissa Maselyne, Kristof Mertens, Annelies Van Nuffel, Huub Scholten, Ioannis Athanasiadis, Mikel Larrañaga, Izaskun Fernández" "To enable all actors in the meat supply chain to monitor, manage and optimise their production process, Internet of Things applications create multiple opportunities. In the IoF2020 project (Internet of Food and Farm 2020), starting early 2017, 11 partners from five countries focus on large-scale implementations of IoT via three use cases in the meat supply chain: pig farm management, poultry chain monitoring and meat transparency and traceability. Farmer’s lack of accessibility to information to monitor their production on a continuous basis will be addressed by installing and integrating IoT sensors for environmental and animal monitoring. In addition, early warning systems will be developed, linking different data-streams to provide valuable feedback to the farmer, as well as information transfer to other stakeholders. Doing so, preventive or corrective actions for diseases, boar taint, bird mortality, feed waste, environment, etc. can be taken. Further, also EPCIS-based tracebility from farm to fork will be enabled, so that consumers receive reliable information on meat origin and quality. The current progress of these three use cases, as well as the planned developments will be presented. By addressing several technological and business challenges, as well as EU-wide dissemination, IoF2020 aims to contribute to the digital revolution in Smart Farming." "Out-of-Things Debugging: A Live Debugging Approach for Internet of Things" "Carlos Rojas Castillo, Matteo Marra, Jim Bauwens, Elisa Gonzalez Boix" "Internet of Things (IoT) has become an important kind of distributed systems thanks to the wide-spread of cheap embedded devices equipped with different networking technologies. Although ubiquitous, developing IoT systems remains challenging. A recent field study with 194 IoT developers identifies debugging as one of the main challenges faced when developing IoT systems. This comes from the lack of debugging tools taking into account the unique properties of IoT systems such as non-deterministic data, and hardware restricted devices. On the one hand, offline debuggers allow developers to analyse post-failure recorded program information, but impose too much overhead on the devices while generating such information. Furthermore, the analysis process is also time-consuming and might miss contextual information relevant to find the root cause of bugs. On the other hand, online debuggers do allow debugging a program upon a failure while providing contextual information (e.g., stack trace). In particular, remote online debuggers enable debugging of devices without physical access to them. However, they experience debugging interference due to network delays which complicates bug reproducibility, and have limited support for dynamic software updates on remote devices. This paper proposes out-of-things debugging, an online debugging approach especially designed for IoT systems. The debugger is always-on as it ensures constant availability to for instance debug post-deployment situations. Upon a failure or breakpoint, out-of-things debugging moves the state of a deployed application to the developer’s machine. Developers can then debug the application locally by applying operations (e.g., step commands) to the retrieved state. Once debugging is finished, developers can commit bug fixes to the device through live update capabilities. Finally, by means of a fine-grained flexible interface for accessing remote resources, developers have full control over the debugging overhead imposed on the device, and the access to device hardware resources (e.g., sensors) needed during local debugging. Out-of-things debugging maintains good properties of remote debugging as it does not require physical access to the device to debug it, while reducing debugging interference since there are no network delays on operations (e.g., stepping) issued on the debugger since those happen locally. Furthermore, device resources are only accessed when requested by the user which further mitigates overhead and opens avenues for mocking or simulation of non-accessed resources. We implemented an out-of-things debugger as an extension to a WebAssembly Virtual Machine and benchmarked its suitability for IoT. In particular, we compared our solution to remote debugging alternatives based on metrics such as network overhead, memory usage, scalability, and usability in production settings. From the benchmarks, we conclude that our debugger exhibits competitive performance in addition to confining overhead without sacrificing debugging convenience and flexibility. Out-of-things debugging enables debugging of IoT systems by means of classical online operations (e.g., stepwise execution) while addressing IoT specific concerns (e.g., hardware limitations). We show that having the debugger always-on does not have to come at cost of performance loss or increased overhead but instead can enforce a smooth-going and flexible debugging experience of IoT systems." "The internet of robotic things : a review of concept, added value and applications" "Pieter Simoens, Mauro Dragone, Alessandro Saffiotti" "Semantics-based platform for context-aware and personalized robot interaction in the internet of robotic things" "Christof Mahieu, Femke Ongenae, Pieter Bonte, Filip De Turck, Pieter Simoens" "End-to-End QoS “Smart Queue” Management Algorithms and Traffic Prioritization Mechanisms for Narrow-Band Internet of Things Services in 4G/5G Networks" "Mykola Beshley, Natalia Kryvinska, Marian Seliuchenko, Halyna Beshley, Elhadi M. Shakshuki, Ansar YASAR" "This paper proposes a modified architecture of the Long-Term Evolution (LTE) mobile network to provide services for the Internet of Things (IoT). This is achieved by allocating a narrow bandwidth and transferring the scheduling functions from the eNodeB base station to an NB-IoT controller. A method for allocating uplink and downlink resources of the LTE/NB-IoT hybrid technology is applied to ensure the Quality of Service (QoS) from end-to-end. This method considers scheduling traffic/resources on the NB-IoT controller, which allows eNodeB planning to remain unchanged. This paper also proposes a prioritization approach within the IoT traffic to provide End-to-End (E2E) QoS in the integrated LTE/NB-IoT network. Further, we develop ""smart queue"" management algorithms for the IoT traffic prioritization. To demonstrate the feasibility of our approach, we performed a number of experiments using simulations. We concluded that our proposed approach ensures high end-to-end QoS of the real-time traffic by reducing the average end-to-end transmission delay." "Enabling direct connectivity between heterogeneous objects in the internet of things through a network-service-oriented architecture" "Eli De Poorter, Ingrid Moerman, Piet Demeester" "Internet of things virtual networks: bringing network virtualization to resource-constrained devices" "Isam Ishaq, Jeroen Hoebeke, Ingrid Moerman, Piet Demeester" "Networks of smart resource-constrained objects, such as sensors and actuators, can support a wide range of application domains. In most cases these networks were proprietary and stand-alone. More recently, many efforts have been undertaken to connect these networks to the Internet using standard protocols. Current solutions that integrate smart resource-constrained objects into the Internet are mostly gateway-based. In these solutions, security, firewalling, protocol translations and intelligence are implemented by gateways at the border of the Internet and the resource-constrained networks. In this paper, we introduce a complementary approach to facilitate the realization of what is called the Internet of Things. Our approach focuses on the objects, both resource-constrained and non-constrained, that need to cooperate by integrating them into a secured virtual network, named an Internet of Things Virtual Network or IoT-VN. Inside this IoT-VN full end-to-end communication can take place through the use of protocols that take the limitations of the most resource-constrained devices into account. We describe how this concept maps to several generic use cases and, as such, can constitute a valid alternative approach for supporting selected applications. A first implementation demonstrating the key concepts of this approach is described. It illustrates the feasibility of integrating resource-constrained devices into virtual networks, but also reveals open challenges." "Internet of Things and Blockchain Technology in Apparel Manufacturing Supply Chain Data Management" "Kamalendu Pal, Ansar YASAR" "The rapid changes in textile and clothing industry's operational environment in which apparel businesses are collaborating with their suppliers and customers have recognized interoperability of information systems as an important factor. The need to address this challenge becomes vital in the context of new paradigms such as the Internet of Things (IoT), and its ability to capture real-time information from different parts of textile and cloth manufacturing value chain by using Radio Frequency Identification (RFID) tags and sensors-based data communication networks. In this process, enterprise information system architecture plays an important role in storing, processing, and distributing data. Despite contributing to the rapid development of IoT applications, the current IoT-centric architecture has led to a myriad of isolated data silos. This paper presents a blockchain-based architecture for the IoT applications, which brings distributed data management to support transactions services within a multi-party apparel business supply chain network. (C) 2020 The Authors. Published by Elsevier B.V." "Light-weight streaming protocol for the internet of multimedia things : voice streaming over NB-IoT" "Abdulkadir Karaağaç, Enri Dalipi, Pieter Crombez, Eli De Poorter, Jeroen Hoebeke" "The cascading neural network : building the Internet of Smart Things" "Sam Leroux, Steven Bohez, Elias De Coninck, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt"