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

The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

The Internet of Things (IoT) is a dynamic global information network consisting of internet-connected objects, such as Radio-frequency identification (RFIDs), sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organisations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. More importantly, we identify the trends, opportunities and open challenges in the industry-based the IoT solutions. Based on the application domain, we classify and discuss these solutions under five different categories: smart wearable, smart home, smart, city, smart environment, and smart enterprise. This survey is intended to serve as a guideline and conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.Comment: IEEE Transactions on Emerging Topics in Computing 201

Mind My Value: a decentralized infrastructure for fair and trusted IoT data trading

Internet of Things (IoT) data are increasingly viewed as a new form of massively distributed and large scale digital assets, which are continuously generated by millions of connected devices. The real value of such assets can only be realized by allowing IoT data trading to occur on a marketplace that rewards every single producer and consumer, at a very granular level. Crucially, we believe that such a marketplace should not be owned by anybody, and should instead fairly and transparently self-enforce a well defined set of governance rules. In this paper we address some of the technical challenges involved in realizing such a marketplace. We leverage emerging blockchain technologies to build a decentralized, trusted, transparent and open architecture for IoT traffic metering and contract compliance, on top of the largely adopted IoT brokered data infrastructure. We discuss an Ethereum-based prototype implementation and experimentally evaluate the overhead cost associated with Smart Contract transactions, concluding that a viable business model can indeed be associated with our technical approach

Foggy clouds and cloudy fogs: a real need for coordinated management of fog-to-cloud computing systems

The recent advances in cloud services technology are fueling a plethora of information technology innovation, including networking, storage, and computing. Today, various flavors have evolved of IoT, cloud computing, and so-called fog computing, a concept referring to capabilities of edge devices and users' clients to compute, store, and exchange data among each other and with the cloud. Although the rapid pace of this evolution was not easily foreseeable, today each piece of it facilitates and enables the deployment of what we commonly refer to as a smart scenario, including smart cities, smart transportation, and smart homes. As most current cloud, fog, and network services run simultaneously in each scenario, we observe that we are at the dawn of what may be the next big step in the cloud computing and networking evolution, whereby services might be executed at the network edge, both in parallel and in a coordinated fashion, as well as supported by the unstoppable technology evolution. As edge devices become richer in functionality and smarter, embedding capacities such as storage or processing, as well as new functionalities, such as decision making, data collection, forwarding, and sharing, a real need is emerging for coordinated management of fog-to-cloud (F2C) computing systems. This article introduces a layered F2C architecture, its benefits and strengths, as well as the arising open and research challenges, making the case for the real need for their coordinated management. Our architecture, the illustrative use case presented, and a comparative performance analysis, albeit conceptual, all clearly show the way forward toward a new IoT scenario with a set of existing and unforeseen services provided on highly distributed and dynamic compute, storage, and networking resources, bringing together heterogeneous and commodity edge devices, emerging fogs, as well as conventional clouds.Peer ReviewedPostprint (author's final draft

User Participation in Value Creation

This article examines HM Treasury’s proposal to account for the active participation of users in value creation in certain digital platforms. The first key question is whether there is any reason to believe, as HM Treasury suggests, that users only meaningfully or actively contribute to value creation in the context of certain digital platforms. The article accordingly explores the factors HM Treasury sets out for the attribution of income to active user participation, including features such as network effects, multisided business models, and a lack of physical presence in the jurisdiction of the user. It concludes that if a user participation concept were adopted into international tax norms, it is unlikely to be limited to digital businesses or to the business models particularly highlighted in the proposal issued by HM Treasury. The analysis proceeds by considering the factors set out by HM Treasury for the attribution of income to active user participation in the context of pharmaceuticals and biologics, the financial sector, and the “internet of things”. For example, the article concludes that under HM Treasury’s user participation theory, returns from certain London-based financial intermediation businesses would need to be reallocated to other jurisdictions. Moreover, as the internet of things develops, one would expect the range of business affected by the active user participation concept to constantly expand

Trading of cloud of things resources

Cloud Computing and Internet of Things (IoT) continue to emerge as revolutionary paradigms to support wide range of real world scenarios. They promise benefits for increasing number of applications, including health, smart cities, smart homes, smart logistics, video surveillance, energy and environmental monitoring. Independent deployments of each technology have issues that can be resolved partially or fully by integrating Cloud and IoT. This integration forms a new paradigm that is called Cloud of Things (CoT)supporting Everything as a Service (XaaS) service model. Despite the issues integration resolves, the integrated services will suffer from issues that Cloud and IoT offerings previously encountered. This includes interoperability, ambiguous SLAs, QoS, elasticity and reliability concerns. This paper argues that commoditising CoT resources will help resolving these issues. This paper aims to; 1) review the state-of-the-art in CoT literature 2) propose a conceptual model for CoT marketplace and its basic trading processes

Business Models for Internet of Things Platforms: Empirical Development of a Taxonomy and Archetypes

A wide range of Internet of Things platform providers operate diverse business models to cater for the manifold requirements of the IoT. This paper contributes to a more precise understanding of IoT platforms as an essential building block of the IoT based on the characteristics of its business models. Even though research listing technological dimensions according to which IoT platforms differ, they have neither been systematically derived nor been linked to the business model concept. In turn, they lack descriptive power on the heterogeneous value creation mechanisms of the platform providers. Within our research, we first analyzed 195 IoT platforms and systemically developed a taxonomy allowing the characterization of IoT platform business models. Second, based on this taxonomy, we identified nine archetypes of IoT platform business models and illustrated typical combinations of business model characteristics. Equipped with such an understanding, practice and research can analyze existing IoT platforms more accurately

Discovering Business Models of Data Marketplaces

The modern economy relies heavily on data as a resource for advancement and growth. Data marketplaces have gained an increasing amount of attention since they provide possibilities to exchange, trade and access data across organizations. Due to the rapid development of the field, the research on business models of data marketplaces is fragmented. We aimed to address this issue in this article by identifying the dimensions and characteristics of data marketplaces from a business model perspective. Following a rigorous process for taxonomy building, we propose a business model taxonomy for data marketplaces. Using evidence collected from a final sample of twenty data marketplaces, we analyze the frequency of specific characteristics of data marketplaces. In addition, we identify four data marketplace business model archetypes. The findings reveal the impact of the structure of data marketplaces as well as the relevance of anonymity and encryption for identified data marketplace archetypes