Aplikace na platformě Windows 10 IoT pro získávání dat ze sensorů

The paper describes the creation of Windows IoT applications in Windows 10, specifically on mobile device for collecting and displaying data obtained from sensors connected to the Arduino development board. This article describes all the steps necessary to create an application in C #, development tools, hardware devices, and libraries in a compact summary which forms the algorithm of the implementation of Windows Universal Application on so-called IoT devices from different manufacturers.Příspěvek popisuje tvorbu aplikace v prostředí Windows 10, konkrétně na mobilním zařízení pro sběr a zobrazení dat získaných ze sensorů připojených na vývojovou desku Arduino. Příspěvek popisuje všechny nezbytné kroky k vytvoření aplikace v jazyce C#, vývojové prostředky, hw zařízení a knihovny v uceleném souhrnu, který tvoří postup implementace Windows Universal Apps na tzv. IoT zařízení

How Hortilux Used Low-Code to Develop Its IoT Digital Services

By 2021, Hortilux, a Dutch horticultural grow light company, offered multiple digital services in its low-code-based HortiSense IoT platform. HortiSense was developed to fulfill the company’s mission of moving from a product-centric to a service-centric solution provider. Based on interviews with IT and non-IT employees, the case explores an example of a company using low-code development beyond simple task automation and illustrates the company’s journey in bringing its IoT platform to market quickly despite a technical talent deficit. The case introduces low-code development, its opportunities, and challenges, and guides the reader to analyze the potential of low-code innovation in an industry undergoing digital transformation

Engineering News, Fall 2019

https://scholarcommons.scu.edu/eng_news/1043/thumbnail.jp

Taming the interoperability challenges of complex IoT systems

of communication protocols and data formats; hence ensuring diverse devices can interoperate with one another remains a significant challenge. Model-driven development and testing solutions have been proposed as methods to aid software developers achieve interoperability compliance in the face of this increasing complexity. However, current approaches often involve complicated and domain specific models (e.g. web services described by WSDL). In this paper, we explore a lightweight, middleware independent, model-driven development framework to help developers tame the challenges of composing IoT services that interoperate with one another. The framework is based upon two key contributions: i) patterns of interoperability behaviour, and ii) a software framework to monitor and reason about interoperability success or failure. We show using a case-study from the FI-WARE Future Internet Service domain that this interoperability framework can support non-expert developers address interoperability challenges. We also deployed tools built atop the framework and made them available in the XIFI large-scale FI-PPP test environment

IoT on Shared Vehicles

Nowadays the need of people to have the power to control everything is increasing. Due to the technological evolution together with the Internet of things, this is already possible. In this context, the shared vehicles are a good example. With just one click people can use a vehicle from a vehicle sharing eet anywhere, anytime. During the realization of this project the uMDC was developed. It is a small device capable of managing and controlling di erent types of vehicles, with the main focus being the electric bicycles. As a nal conclusion of the project, the results obtained with the uMDC have proved very attractive. During its integration in the electric bicycles, the system was capable of controlling the bicycle's di erent components, as required for the rst prototype.Hoje em dia, a necessidade das pessoas terem controlo sobre tudo está a aumentar. Devido á evolução tecnológica juntamente com a Internet das coisas, isso já é possível. Neste contexto, os veículos partilhados são um bom exemplo disso. Com um simples clique, as pessoas podem usufruir e uma viatura de uma frota de veículos partilhados em qualquer lugar, a qualquer hora. Durante a realização deste projeto, foi desenvolvido o uMDC. Um pequeno ispositivo capaz de gerir e controlar diferentes tipos de veículos, sendo o foco principal as bicicletas elétricas. No nal deste projeto, os resultados obtidos com o uMDC foram bastante satisfatórios. Durante a sua integração nas bicicletas elétricas, o sistema foi capaz de controlar diferentes componentes das mesmas, como requerido para primeiro protótipo

Ten Quick Tips for Using a Raspberry Pi

Much of biology (and, indeed, all of science) is becoming increasingly computational. We tend to think of this in regards to algorithmic approaches and software tools, as well as increased computing power. There has also been a shift towards slicker, packaged solutions--which mirrors everyday life, from smart phones to smart homes. As a result, it's all too easy to be detached from the fundamental elements that power these changes, and to see solutions as "black boxes". The major goal of this piece is to use the example of the Raspberry Pi--a small, general-purpose computer--as the central component in a highly developed ecosystem that brings together elements like external hardware, sensors and controllers, state-of-the-art programming practices, and basic electronics and physics, all in an approachable and useful way. External devices and inputs are easily connected to the Pi, and it can, in turn, control attached devices very simply. So whether you want to use it to manage laboratory equipment, sample the environment, teach bioinformatics, control your home security or make a model lunar lander, it's all built from the same basic principles. To quote Richard Feynman, "What I cannot create, I do not understand".Comment: 12 pages, 2 figure

A Roadmap for successful IoT implementation : empirical evidence from the energy industry

The Internet of Things has become a spotlight in contemporary literature in the domain of industry 4.0 and emerging technologies. Majority of research studies focuses on technicalities and theoretical implications of implementing IoT in the energy sector. However, in practice, organisations face a combination of technical and non-technical challenges. There is a clear need for the studies to empirically evaluate IoT use cases, challenges, and a roadmap for successfully implementing emerging technologies. To fulfil the research gap and provide insights for practitioners, we conducted seven semi-structured interviews with professionals working in Finland’s energy sector. Based on results retrieved through content analysis of transcribed interviews, we developed a roadmap with managerial implications for successfully implementing IoT and other emerging technologies. Furthermore, study results present practical insights on IoT applications, benefits, and major IoT utilisation challenges in the Finnish energy sector industrial ecosystem. In the end, conclusion and future research directions are discussed.©2021 the Authors. Articles published in Issues in Information Systems are licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.fi=vertaisarvioitu|en=peerReviewed

IoT Based Image Processing Filters

Internet of things (IoT) becomes the backbone of the advanced countries and it has a real contribute to exchange the traditional style or way of practical life, even personal life into smart style, with (IoT) technology the life become more and more easy and professional. internet of things achieves various applications coordinate with sensors and standard protocols to apply what is called machine -to- machine connection (M2M), in this paper we will talk more about the concept of (M2M), the main component of internet of things and finally the common protocols that is used in network, in addition to that this work present an IOT operation with processing system using camera for capturing image and Xilinx system generator(XSG)models for designing  image processing algorithms and the result of  the processing is an image with black and white for edge detection and Thresholding models  and gray color image for gray enhancement model