Conclusion

2019 ◽  
pp. 215-222
Author(s):  
Rowan Wilken
Keyword(s):  
Machine Learning ◽  
Autonomous Vehicle ◽  
Data Capture ◽  
The Internet ◽  
Depth Sensing ◽  
Locative Media ◽  
Location Data ◽  
Recent Developments ◽  
Technological Developments ◽  
The Internet Of Things

The Conclusion revisits the terrain the book has covered, providing recapitulations of the arguments of each of the three parts of the book and the chapters contained within them. The argument of this Conclusion is that, while locative media having shifted significantly over the course of the past decade or so, location, locative media, and location data capture remain central concerns, both in the present and within and for new technological developments. It is, for instance, central to visions of “smart” or “networked” cities, and of depth-sensing vision capture technologies. Location is also crucial to recent developments in mapping and indoor mapping, autonomous vehicle development, environmental sensing, the internet of things, machine learning, and distributed ledger technologies.

scholarly journals SUITCEYES Scoping Report on Law and Policy on Deafblindness, Disability and New Technologies: United Kingdom

2021 ◽  
Author(s):  
Sarah Lesley Woodin
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
New Technologies ◽  
The Internet ◽  
Disabled People ◽  
Law And Policy ◽  
Technological Developments ◽  
The Uk ◽  
The Internet Of Things ◽  
Broad Overview

This report discusses law and policy on new technologies: artificial intelligence (AI), machine learning and the Internet of Things (IoT) in relation to disabled people and people with deafblindness in the UK. Written as part of the SUITCEYES project, it provides a broad overview of formal rights and the extent to which disabled people can access new technologies in practice. The field is fast moving and volatile, with judgements regularly made and overturned in the courts and frequent new initiatives. The UK government emphasises the importance of investing in new technologies as a means of strengthening the economy. The opportunities represented by technological developments have been largely welcomed by disabled people but questions remain about how the technology might be used and developed by disabled people and people with deafblindness themselves and the need for safeguards against exploitation.

Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model

Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Mobile Networks ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Traffic Model ◽  
The Internet ◽  
Wide Spread ◽  
The Internet Of Things

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.

scholarly journals IMPROVING INTERNET OF THINGS PARKING SYSTEMS

2021 ◽  
Vol 19 (3) ◽  
pp. 163
Author(s):  
Dušan Bogićević
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Information Needs ◽  
Vehicle Classification ◽  
The Internet ◽  
Parking Space ◽  
Automated Systems ◽  
The Internet Of Things

Edge data processing represents the new evolution of the Internet and Cloud computing. Its application to the Internet of Things (IoT) is a step towards faster processing of information from sensors for better performance. In automated systems, we have a large number of sensors, whose information needs to be processed in the shortest possible time and acted upon. The paper describes the possibility of applying Artificial Intelligence on Edge devices using the example of finding a parking space for a vehicle, and directing it based on the segment the vehicle belongs to. Algorithm of Machine Learning is used for vehicle classification, which is based on vehicle dimensions.

A Comprehensive Survey on Interoperability for IIoT: Taxonomy, Standards, and Future Directions

2023 ◽  
Vol 55 (1) ◽  
pp. 1-35
Author(s):  
Abhishek Hazra ◽  
Mainak Adhikari ◽  
Tarachand Amgoth ◽  
Satish Narayana Srirama
Keyword(s):  
Industrial Revolution ◽  
Industrial Applications ◽  
Future Research ◽  
The Internet ◽  
Large Numbers ◽  
Industrial Iot ◽  
Recent Developments ◽  
Comprehensive Survey ◽  
Real Time Information ◽  
The Internet Of Things

In the era of Industry 4.0, the Internet-of-Things (IoT) performs the driving position analogous to the initial industrial metamorphosis. IoT affords the potential to couple machine-to-machine intercommunication and real-time information-gathering within the industry domain. Hence, the enactment of IoT in the industry magnifies effective optimization, authority, and data-driven judgment. However, this field undergoes several interoperable issues, including large numbers of heterogeneous IoT gadgets, tools, software, sensing, and processing components, joining through the Internet, despite the deficiency of communication protocols and standards. Recently, various interoperable protocols, platforms, standards, and technologies are enhanced and altered according to the specifications of the applicability in industrial applications. However, there are no recent survey papers that primarily examine various interoperability issues that Industrial IoT (IIoT) faces. In this review, we investigate the conventional and recent developments of relevant state-of-the-art IIoT technologies, frameworks, and solutions for facilitating interoperability between different IIoT components. We also discuss several interoperable IIoT standards, protocols, and models for digitizing the industrial revolution. Finally, we conclude this survey with an inherent discussion of open challenges and directions for future research.

Industry 4.0 and the Internet of Things (IoT)

2020 ◽  
pp. 1-24
Author(s):  
Zelal Gültekin Kutlu
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Information Technologies ◽  
Industrial Revolution ◽  
The Internet ◽  
Automation Systems ◽  
Technological Developments ◽  
Use Of The Internet ◽  
Internet Networks ◽  
The Internet Of Things

In this study, the periodical differences of industrial revolutions, which is one of the effects of technological developments in the industrial field, and the last stage of it are mentioned. With the latest industrial revolution called Industry 4.0, machines work in harmony with technology at every stage of industrial areas. This period, known as Industry 4.0 or the fourth industrial revolution, refers to the system in which the latest production technologies, automation systems, and the technologies that make up this system exchange data with each other. In addition to the information technologies and automation systems used in Industry 3.0, industrial production has gained a whole new dimension with the use of the internet. With internet networks, machines, operators, and robots now work in harmony. At this point, the concept of internet of objects becomes important. Therefore, another focus of the study is the concept of internet of objects. There are some assumptions about the uses, benefits, and future status of the internet of things.

Current Trends in Integrating the Internet of Things Into Software Engineering Practices

2021 ◽  
pp. 413-428
Author(s):  
S. Kavitha ◽  
J. V. Anchitaalagammai ◽  
S. Nirmala ◽  
S. Murali
Keyword(s):  
Machine Learning ◽  
Software Engineering ◽  
Internet Of Things ◽  
The Internet ◽  
Infrastructure Management ◽  
Integration Testing ◽  
Current Trends ◽  
Software Construction ◽  
Engineering Practices ◽  
The Internet Of Things

The chapter summarizes the concepts and challenges of DevOps in IoT, DevSecOps in IoT, integrating security into IoT, machine learning and AI in IoT of software engineering practices. DevOps is a software engineering culture and practice that aims at unifying software development (Dev) and software operation (Ops). The main characteristic of DevOps is the automation and monitoring at all steps of software construction, from integration, testing, releasing to deployment and infrastructure management. DevSecOps is a practice of integrating security into every aspect of an application lifecycle from design to development.

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