IoT-liiketoiminnan mallintaminen

Our world is becoming increasingly digitized. Digitalization has changed and is changing business models at accelerating pace and creating new revenue and value-producing opportunities. We are now witnessing the age where the digital technologies are harnessed for our advantage - as the physical technologies were harnessed in the first industrial revolution. Still, the digital world and the physical world are separated from each other. This is the one significant issue, that the Internet of Things (IoT) is about to change. The vision of the IoT is to connect people and devices and produce a vast variety of new goods and services. As the IoT is a novel phenomenon, it can be a difficult concept to define. It can be difficult to create a comprehensive understanding on what the IoT is and what kind opportunities it has to offer. In addition, The IoT is a complex phenomenon in terms of monetization. It can be difficult to create a comprehensive understanding on where the real value of the IoT comes from. The goal of this study is to to create a framework of possible IoT business opportunities for the target company. This is done by creating a conceptualization that unfolds the different roles there are in IoT business for the target company to take or aim for. In addition to the conceptualization, there is also a need to create better understanding of the customership and value proposition related to the IoT business, and recognize the most important barriers of adoption and capabilities required for managing the barriers of adoption.Digitalisaatio on muuttanut ja muuttaa liiketoimintamalleja kiihtyvällä vauhdilla luoden uusia mahdollisuuksia arvontuotolle. Todistamme nyt aikakautta, jossa digitaaliset teknologiat valjastetaan käyttöön, kuten fyysiset teknologiat valjastettiin ensimmäisessä teollisessa vallankumouksessa. Siltikin digitaalinen ja fyysinen maailma ovat olleet tähän asti erossa toisistaan. Tämä on merkittävin asia, jonka esineiden internet tulee muuttamaan. Esineiden internetin visiona on yhdistää ihmiset ja laitteet ja luoda laaja valikoima uusia tavaroita ja palveluita. Koska esineiden internet on uusi ilmiö, sen määritteleminen voi olla vaikeaa. On haastavaa luoda kattavaa käsitystä siitä, mitä esineiden internet on ja millaisia mahdollisuuksia se tarjoaa. Lisäksi esineiden internet on minimutkainen ilmiö kaupallistamisen kannalta. On haastavaa luoda kattavaa käsitystä mistä esineiden internetin todellinen arvo tulee. Tämän opinnäytteen tavoitteena on luoda viitekehys, jonka avulla kohdeyritys voi paremmin hahmottaa esineiden internetin tarjoamia liiketoimintamahdollisuuksia. Tämä mahdollistetaan hahmottamalla erilaiset roolit, joihin kohdeyritys voi asettua. Viitekehyksen lisäksi opinnäytteen tavoitteena on luoda parempi ymmärrys IoT-liiketoimintaan liittyvistä asiakkuuksista ja arvolupauksista, sekä tunnistaa tärkeimmät käyttöönoton esteet sekä tarvittavat kyvykkyydet niiden hallitsemiseksi

Machine Learning and Integrative Analysis of Biomedical Big Data.

Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome) is analyzed in isolation using statistical and machine learning (ML) methods. Integrative analysis of multi-omics and clinical data is key to new biomedical discoveries and advancements in precision medicine. However, data integration poses new computational challenges as well as exacerbates the ones associated with single-omics studies. Specialized computational approaches are required to effectively and efficiently perform integrative analysis of biomedical data acquired from diverse modalities. In this review, we discuss state-of-the-art ML-based approaches for tackling five specific computational challenges associated with integrative analysis: curse of dimensionality, data heterogeneity, missing data, class imbalance and scalability issues

Underpinning Quality Assurance: Identifying Core Testing Strategies for Multiple Layers of Internet-of-Things-Based Applications

The Internet of Things (IoT) constitutes a digitally integrated network of intelligent devices equipped with sensors, software, and communication capabilities, facilitating data exchange among a multitude of digital systems via the Internet. Despite its pivotal role in the software development life-cycle (SDLC) for ensuring software quality in terms of both functional and non-functional aspects, testing within this intricate software–hardware ecosystem has been somewhat overlooked. To address this, various testing techniques are applied for real-time minimization of failure rates in IoT applications. However, the execution of a comprehensive test suite for specific IoT software remains a complex undertaking. This paper proposes a holistic framework aimed at aiding quality assurance engineers in delineating essential testing methods across different testing levels within the IoT. This delineation is crucial for effective quality assurance, ultimately reducing failure rates in real-time scenarios. Furthermore, the paper offers a mapping of these identified tests to each layer within the layered framework of the IoT. This comprehensive approach seeks to enhance the reliability and performance of IoT-based applications

A Reference Architecture for Provisioning of Tools as a Service: Meta-Model, Ontologies and Design Elements

Abstract not availableMuhammad Aufeef Chauhan, Muhammad Ali Babar, Quan Z. Shen

A Survey on Layer-Wise Security Attacks in IoT: Attacks, Countermeasures, and Open-Issues

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Security is a mandatory issue in any network, where sensitive data are transferred safely in the required direction. Wireless sensor networks (WSNs) are the networks formed in hostile areas for different applications. Whatever the application, the WSNs must gather a large amount of sensitive data and send them to an authorized body, generally a sink. WSN has integrated with Internet-of-Things (IoT) via internet access in sensor nodes along with internet-connected devices. The data gathered with IoT are enormous, which are eventually collected by WSN over the Internet. Due to several resource constraints, it is challenging to design a secure sensor network, and for a secure IoT it is essential to have a secure WSN. Most of the traditional security techniques do not work well for WSN. The merger of IoT and WSN has opened new challenges in designing a secure network. In this paper, we have discussed the challenges of creating a secure WSN. This research reviews the layer-wise security protocols for WSN and IoT in the literature. There are several issues and challenges for a secure WSN and IoT, which we have addressed in this research. This research pinpoints the new research opportunities in the security issues of both WSN and IoT. This survey climaxes in abstruse psychoanalysis of the network layer attacks. Finally, various attacks on the network using Cooja, a simulator of ContikiOS, are simulated.Peer reviewe

Context Aware Middleware Architectures: Survey and Challenges

Abstract: Context aware applications, which can adapt their behaviors to changing environments, are attracting more and more attention. To simplify the complexity of developing applications, context aware middleware, which introduces context awareness into the traditional middleware, is highlighted to provide a homogeneous interface involving generic context management solutions. This paper provides a survey of state-of-the-art context aware middleware architectures proposed during the period from 2009 through 2015. First, a preliminary background, such as the principles of context, context awareness, context modelling, and context reasoning, is provided for a comprehensive understanding of context aware middleware. On this basis, an overview of eleven carefully selected middleware architectures is presented and their main features explained. Then, thorough comparisons and analysis of the presented middleware architectures are performed based on technical parameters including architectural style, context abstraction, context reasoning, scalability, fault tolerance, interoperability, service discovery, storage, security & privacy, context awareness level, and cloud-based big data analytics. The analysis shows that there is actually no context aware middleware architecture that complies with all requirements. Finally, challenges are pointed out as open issues for future work

Advancing IoT Platforms Interoperability

The IoT European Platforms Initiative (IoT-EPI) projects are addressing the topic of Internet of Things and Platforms for Connected Smart Objects and aim to deliver an IoT extended into a web of platforms for connected devices and objects that supports smart environments, businesses, services and persons with dynamic and adaptive configuration capabilities. The specific areas of focus of the research activities are architectures and semantic interoperability, which reliably cover multiple use cases. The goal is to deliver dynamically-configured infrastructure and integration platforms for connected smart objects covering multiple technologies and multiple intelligent artefacts. The IoT-EPI ecosystem has been created with the objective of increasing the impact of the IoT-related European research and innovation, including seven European promising projects on IoT platforms: AGILE, BIG IoT, INTER-IoT, VICINITY, SymbIoTe, bIoTope, and TagItSmart.This white paper provides an insight regarding interoperability in the IoT platforms and ecosystems created and used by IoT-EPI. The scope of this document covers the interoperability aspects, challenges and approaches that cope with interoperability in the current existing IoT platforms and presents some insights regarding the future of interoperability in this context. It presents possible solutions, and a possible IoT interoperability platform architecture

Digital Twins: A Meta-Review on Their Conceptualization, Application, and Reference Architecture

The concept of digital twins (DTs) is receiving increasing attention in research and management practice. However, various facets around the concept are blurry, including conceptualization, application areas, and reference architectures for DTs. A review of preliminary results regarding the emerging research output on DTs is required to promote further research and implementation in organizations. To do so, this paper asks four research questions: (1) How is the concept of DTs defined? (2) Which application areas are relevant for the implementation of DTs? (3) How is a reference architecture for DTs conceptualized? and (4) Which directions are relevant for further research on DTs? With regard to research methods, we conduct a meta-review of 14 systematic literature reviews on DTs. The results yield important insights for the current state of conceptualization, application areas, reference architecture, and future research directions on DTs

A caching mechanism to exploit object store speed in High Energy Physics analysis

[EN] Data analysis workflows in High Energy Physics (HEP) read data written in the ROOT columnar format. Such data has traditionally been stored in files that are often read via the network from remote storage facilities, which represents a performance penalty especially for data processing workflows that are I/O bound. To address that issue, this paper presents a new caching mechanism, implemented in the I/O subsystem of ROOT, which is independent of the storage backend used to write the dataset. Notably, it can be used to leverage the speed of high-bandwidth, low-latency object stores. The performance of this caching approach is evaluated by running a real physics analysis on an Intel DAOS cluster, both on a single node and distributed on multiple nodes.This work benefited from the support of the CERN Strategic R&D Programme on Technologies for Future Experiments [1] and from grant PID2020-113656RB-C22 funded by Ministerio de Ciencia e Innovacion MCIN/AEI/10.13039/501100011033. The hardware used to perform the experimental evaluation involving DAOS (HPE Delphi cluster described in Sect. 5.2) was made available thanks to a collaboration agreement with Hewlett-Packard Enterprise (HPE) and Intel. User access to the Virgo cluster at the GSI institute was given for the purpose of running the benchmarks using the Lustre filesystem.Padulano, VE.; Tejedor Saavedra, E.; Alonso-Jordá, P.; López Gómez, J.; Blomer, J. (2022). A caching mechanism to exploit object store speed in High Energy Physics analysis. Cluster Computing. 1-16. https://doi.org/10.1007/s10586-022-03757-211