Domain-specific diagrammatic modelling: a source of machine-readable semantics for the Internet of Things

2016 ◽  
Vol 20 (1) ◽  
pp. 895-908 ◽  
Author(s):  
Robert Andrei Buchmann ◽  
Dimitris Karagiannis
2018 ◽  
Vol 23 (5) ◽  
pp. 407-411 ◽  
Author(s):  
Alok Tayi

Over the past decade, cloud software has transformed numerous industries—from finance to logistics, marketing to manufacturing. The simplified aggregation of data, enabled by cloud computing, empowers individuals to glean insights and make data-driven decisions rapidly. In science, however, such a transformation has yet to emerge. The domain lacks centralized, machine-readable repositories of scientific data; this absence inhibits analytics and expedient decision-making. Recently, the Internet of Things (IoT) has served as a catalyst for digitizing and automating science. IoT enables the centralized collection and analysis of scientific data (e.g., instruments, sensors, and environments). Here, we discuss this new technology trend, its applications in laboratories and promise as a platform for improved efficiency, more innovative capabilities, and machine learning/artificial intelligence.


Author(s):  
Daniel Meana-Llorián ◽  
Cristian González García ◽  
Cristina Pelayo G-Bustelo ◽  
Juan Manuel Cueva-Lovelle

2021 ◽  
Vol 23 (09) ◽  
pp. 1216-1224
Author(s):  
Saniya Zahoor ◽  
◽  
Shabir A.Sofi ◽  

The Internet of Things (IoT) is an emerging paradigm that embodies the vision of merging smart objects while utilizing the internet as the backbone of the communication system to establish a smart interaction among physical entities in pervasive environments. In IoT, data is generated in realtime and stored in permanent repositories. Additional data in the form of meta-data that describes things adds to the data volume and to manage this data, architecture is required. IoT finds its applicability in a plethora of applications such as transportation, smart city, smart health, smart environment, home entertainment, sports, etc. but there is no universal architecture for all IoT implementations. We have layered architectures and domain-specific architectures for different IoT applications. Besides a large number of architectures for IoT, it faces several potential challenges such as scalability, reliability, heterogeneity, etc. This paper presents an understanding of the Internet of Things in terms of its functionality, layered and domain-specific architectures, and its potential challenges.


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