Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Digital Twin Technology: A Review of Its Applications and Prominent Challenges

Digital twin is a virtual representation of physical product that is used as benchmark to evaluate, diagnose, optimize and supervise operational performance of products before venturing into mass full production in accordance with global standard. Digital twin merges virtual and physical objects together via sensors and IoT to transmit data and keep traces of objects interactivity within present environments. In virtual model environment, digital twin permits product troubleshooting and testing to minimize rate of failure and product defects during product manufacturing to enhance effectiveness and customers’ satisfaction. Digital twin is utilized throughout product life-cycle to simulate, optimize and predict product quality before final production is financed. Digital twin is beneficial to modern digital society because attitude of modern factory workers can be boosted to improve motivation to work. Digital twin has come to stay, future product suppliers may be required to put forward digital twin of their products beforehand for virtual lab testing before making order while suppliers that fail to comply may be left over. With emergence of digital twin, virtual testing can be conducted on proposed products before finding their ways into physical marketplaces. Business sector remains most beneficiaries of digital twin to predict present and future state of physical product via digital peer analysis. Today, digital twin application can support enterprises by improving product performances, decision making and customers’ satisfactions on logistic and operational workflow. However, in this survey of digital twin research, efforts have been made to review in detail about digital twin, its impact and benefits to modern society, its architecture; security challenges and how solutions are proffered. It is believed that ICT experts, manufacturers and industries will leverage on this research to improve QoS (Quality of Service) for new and future products to take full advantage of profits on investment returns via digital twin

6G White Paper on Machine Learning in Wireless Communication Networks

The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has led enable a wide range of novel technologies such as self-driving vehicles and voice assistants. Such innovation is possible as a result of the availability of advanced ML models, large datasets, and high computational power. On the other hand, the ever-increasing demand for connectivity will require a lot of innovation in 6G wireless networks, and ML tools will play a major role in solving problems in the wireless domain. In this paper, we provide an overview of the vision of how ML will impact the wireless communication systems. We first give an overview of the ML methods that have the highest potential to be used in wireless networks. Then, we discuss the problems that can be solved by using ML in various layers of the network such as the physical layer, medium access layer, and application layer. Zero-touch optimization of wireless networks using ML is another interesting aspect that is discussed in this paper. Finally, at the end of each section, important research questions that the section aims to answer are presented

The Future of the Internet III

Presents survey results on technology experts' predictions on the Internet's social, political, and economic impact as of 2020, including its effects on integrity and tolerance, intellectual property law, and the division between personal and work lives

Mapping Industry 4.0 Enabling Technologies into United Nations Sustainability Development Goals

The emerging of the fourth industrial revolution, also known as Industry 4.0 (I4.0), from the advancement in several technologies is viewed not only to promote economic growth, but also to enable a greener future. The 2030 Agenda of the United Nations for sustainable development sets out clear goals for the industry to foster the economy, while preserving social well-being and ecological validity. However, the influence of I4.0 technologies on the achievement of the Sustainable Development Goals (SDG) has not been conclusively or systematically investigated. By understanding the link between the I4.0 technologies and the SDGs, researchers can better support policymakers to consider the technological advancement in updating and harmonizing policies and strategies in different sectors (i.e., education, industry, and governmental) with the SDGs. To address this gap, academic experts in this paper have investigated the influence of I4.0 technologies on the sustainability targets identified by the UN. Key I4.0 element technologies have been classified to enable a quantitative mapping with the 17 SDGs. The results indicate that the majority of the I4.0 technologies can contribute positively to achieving the UN agenda. It was also found that the effects of the technologies on individual goals varies between direct and strong, and indirect and weak influences. The main insights and lessons learned from the mapping are provided to support future policy

10301 Executive Summary and Abstracts Collection -- Service Value Networks

From 25.07.2010 to 30.07.2010, the Perspectives Workshop 10301 ``Perspectives Workshop: Service Value Networks \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available