Performance analysis of SWOT suite toolkit on Inter-domain and Intra-domain Web of Things

The Web of Things (WoT) is a term used to describe approaches, software architectural styles and programming patterns that allow real-world objects to be part of the World Wide Web [1]. Similarly to what the Web (Application Layer) is to the Internet (Network Layer), the Web of Things provides an Application Layer that simplifies the creation of Internet of Things applications [2]

Understanding the Internet of Things: A Conceptualisation of Business-to-Thing (B2T) Interactions

The Internet of Things is widely regarded as one of the most disruptive technologies as it integrates Internet-enabled physical objects into the networked society and makes these objects increasingly autonomous partners in digitised value chains. After transforming internal processes and enhancing efficiency, the Internet of Things yields the potential to transform traditional business-to-customer interactions in a way previously not thought of. Remote patient monitoring, predictive maintenance, and automatic car repair are only some innovative examples. This paper contributes to the conceptualisation of the emerging business relationships based on such empowered smart things by proposing a series of core and advanced business-to-thing (B2T) interaction patterns. The core patterns named C2T-Only, B2T-Only, Customer-Centred, Business-Centred, Thing-Centred, and All-In B2T classify alternative interactions between businesses, customers, and smart things, using the connected car as an ongoing case and Uber as an example to demonstrate how patters can be composed. The proposed patterns demonstrate the affordances of integrating smart things into the networked society and sensitise for the emergence of B2T interactions

Did Class 1 and Class 2 Aminoacyl Trna Synthetases Descend from Genetically Complimentary, Catalytically Active ATP-Binding Motifs?

The Internet of Things is widely regarded as one of the most disruptive technologies as it inte-grates smart physical objects into the networked society and digital value networks. Today, the Internet of Things has the potential to transform business-to-customer interactions enabled by smart things. Remote patient monitoring, predictive maintenance, and automatic car repair are just a few examples of evolving business-to-thing (B2T) interactions. However, the Internet of Things remains a space low on theoretical investigations. Complementing the tech-nical/engineering focus on the Internet of Things, we developed and evaluated a taxonomy of B2T interaction patterns, building on sociomateriality as justificatory knowledge. We also demonstrated the taxonomy’s applicability and usefulness based on simple and complex real-life objects (e.g., Nest, RelayRides, Uber). Our taxonomy contributes to the descriptive knowledge related to the Internet of Things, as it enables the classification of B2T interactions, providing the basis for sense-making research and early theory-led design. When combining the weak and the strong form of sociomateriality as justificatory knowledge, we also found that the Internet of Things enables and requires a new perspective on material agency, treating smart things as independent actors

Path Recognition with DTW in a Distributed Environment

The Internet of Things is a concept, where various devices are connected in a network and data is exchanged between them. With the help of Internet of Things applications, it is possible to access sensors remotely to collect data from the physical world. The collected data contains potential knowledge, which could be revealed by applying machine learning techniques. Due to the rapid development of Internet of Things applications, the amount of collected data increases enormously. In order to perform computations on large datasets, distributed computing technologies are used. Recognizing people’s movements is a popular topic in the context of the Internet of Things. Movement patterns are usually sequential and continuous, and can therefore be encoded in the form of time series. Since the Dynamic-Time-Warping (DTW) is an established algorithm for processing time series data, it is chosen as a similarity measure for different movement patterns. Moreover, based on the DTW results, the movements are classified. In this thesis, we provide an implementation for the recognition of movement patterns. The prototype is built on Apache Spark and Apache Hadoop and uses their distributed computation possibilities. In an experiment, data from probands is collected and evaluated. Finally, the algorithm performance and accuracy is measured

Enabling IoT ecosystems through platform interoperability

Today, the Internet of Things (IoT) comprises vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and adapt to the platform-specific API and information models. Having to perform these actions for each platform often outweighs the possible gains from adapting applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and prevent the emergence of broadly accepted IoT ecosystems. The BIG IoT (Bridging the Interoperability Gap of the IoT) project aims to ignite an IoT ecosystem as part of the European Platforms Initiative. As part of the project, researchers have devised an IoT ecosystem architecture. It employs five interoperability patterns that enable cross-platform interoperability and can help establish successful IoT ecosystems.Peer ReviewedPostprint (author's final draft

thematic series on verification and composition for the internet of services and things

Abstract ■■■ The Internet of Services and Things is characterized as a distributed computing environment that will be populated by a large number of software services and things. Within this context, software systems will increasingly be built by reusing and composing together software services and things distributed over the Internet. This calls for new integration paradigms and patterns, formal composition theories, integration architectures, as well as flexible and dynamic composition and verification mechanisms. In particular, service- and thing-based systems pose new challenges for software composition and verification techniques, due to changing requirements, emerging behaviors, uncertainty, and dynamicity