Ionizing Radiation Monitoring Technology at the Verge of Internet of Things

As nuclear technology evolves, and continues to be used in various fields since its discovery less than a century ago, radiation safety has become a major concern to humans and the environment. Radiation monitoring plays a significant role in preventive radiological nuclear detection in nuclear facilities, hospitals, or in any activities associated with radioactive materials by acting as a tool to measure the risk of being exposed to radiation while reaping its benefit. Apart from in occupational settings, radiation monitoring is required in emergency responses to radiation incidents as well as outdoor radiation zones. Several radiation sensors have been developed, ranging from as simple as a Geiger-Muller counter to bulkier radiation systems such as the High Purity Germanium detector, with different functionality for use in different settings, but the inability to provide real-time data makes radiation monitoring activities less effective. The deployment of manned vehicles equipped with these radiation sensors reduces the scope of radiation monitoring operations significantly, but the safety of radiation monitoring operators is still compromised. Recently, the Internet of Things (IoT) technology has been introduced to the world and offered solutions to these limitations. This review elucidates a systematic understanding of the fundamental usage of the Internet of Drones for radiation monitoring purposes. The extension of essential functional blocks in IoT can be expanded across radiation monitoring industries, presenting several emerging research opportunities and challenges. This article offers a comprehensive review of the evolutionary application of IoT technology in nuclear and radiation monitoring. Finally, the security of the nuclear industry is discussed.

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The Internet of Things: Making Cities — AndThe Way They Use Technology — Smarter

Cross Americas: Probing Disglobal Networks- Papers ◽

10.35483/acsa.intl.2016.49 ◽

2016 ◽

Author(s):

Wendy W. Fok ◽

Keyword(s):

New York ◽

Internet Of Things ◽

Energy Use ◽

Smart Cities ◽

Traffic Monitoring ◽

Urban Life ◽

The Internet ◽

Time Data ◽

Heating And Cooling ◽

The Internet Of Things

Minerva Tantoco was named New York City’s first chief technology officer last year, charged with developing a coordinated citywide strategy on technology and innovation. We’re likely to see more of that as cities around the country, and around the world, consider how best to use innovation and technology to operate as “smart cities.”The work has major implications for energy use and sustainability, as cities take advantage of available, real-time data – from ‘smart’ phones, computers, traffic monitoring, and even weather patterns — to shift the way in which heating and cooling systems, landscaping, flow of people through cities, and other pieces of urban life are controlled. But harnessing Open Innovation and the Internet of Things can promote sustainability on a much broader and deeper scale. The question is, how do you use all the available data to create a more environmentally sound future? The term “Internet of Things” was coined in 1999 by Kevin Ashton, who at the time was a brand manager trying to find a better way to track inventory. His idea? Put a microchip on the packaging to let stores know what was on the shelves.

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How Industry 4.0 Can Benefit From Semantic Web Technologies and Artefacts

International Journal of Software Science and Computational Intelligence ◽

10.4018/ijssci.2021100105 ◽

2021 ◽

Vol 13 (4) ◽

pp. 64-74

Author(s):

Leila Zemmouchi-Ghomari

Keyword(s):

Cloud Computing ◽

Internet Of Things ◽

Semantic Web ◽

Industry 4.0 ◽

The Internet ◽

Time Data ◽

Semantic Web Technologies ◽

Web Technologies ◽

Real Time Data ◽

The Internet Of Things

Industry 4.0 is a technology-driven manufacturing process that heavily relies on technologies, such as the internet of things (IoT), cloud computing, web services, and big real-time data. Industry 4.0 has significant potential if the challenges currently being faced by introducing these technologies are effectively addressed. Some of these challenges consist of deficiencies in terms of interoperability and standardization. Semantic Web technologies can provide useful solutions for several problems in this new industrial era, such as systems integration and consistency checks of data processing and equipment assemblies and connections. This paper discusses what contribution the Semantic Web can make to Industry 4.0.

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Application of IoT in the COVID-19 Pandemic

European Journal of Electrical Engineering and Computer Science ◽

10.24018/ejece.2021.5.5.354 ◽

2021 ◽

Vol 5 (5) ◽

pp. 1-3

Author(s):

B. Shoban Babu ◽

Prince Patel

Keyword(s):

Internet Of Things ◽

The Internet ◽

Time Data ◽

Smart Systems ◽

Risk Patients ◽

Review Study ◽

Smart Hospitals ◽

High Level ◽

The Internet Of Things ◽

Level Of Agreement

As we all know, the Internet has altered everything, and the Internet of Things has given us hope for a bright future of the Internet with Machine-to-Machine (M2M) connectivity. This review study demonstrated that smart systems based on the Internet of Things are feasible and economical to build (IoT). In the field of healthcare, the Internet of Things has made significant progress. This article examines how the Internet of Things (IoT) is revolutionising the healthcare industry by giving huge healthcare advantages to humanity through accessible and practical healthcare solutions specially during the hard coronavirus situation around the world. The purpose of this study is to address the function of IoT in smart hospitals, as well as its importance in dealing with pandemics. Various smart gadgets that can provide a variety of features, such as adequate monitoring of high-risk patients, tracking their bio-metric measurements, and gathering real-time data, can be used to serve community-specific demands during pandemic spread. We've also looked into other plans that can detect unforeseen events utilising a variety of sensors and display the information gathered on an LED display. The results of observational studies have indicated a high level of agreement with the hypothetical claims.

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Value Enablement of Collaborative Supply Chain Environment Embedded With the Internet of Things

International Journal of Intelligent Information Technologies ◽

10.4018/ijiit.2020070102 ◽

2020 ◽

Vol 16 (3) ◽

pp. 19-51

Author(s):

Samir Yerpude ◽

Tarun Kumar Singhal

Keyword(s):

Supply Chain ◽

Internet Of Things ◽

Supply Chains ◽

Goodness Of Fit ◽

The Internet ◽

Chain Model ◽

Time Data ◽

Business Goals ◽

The Impact ◽

The Internet Of Things

Currently, industry is going through the fourth Industrial Revolution, also termed Industry 4.0. It is characterized mainly by the cyber-physical systems dominated by digital technologies such as the Internet of Things (IoT). Organizations are making significant effort to understand customer needs and subsequently align them to the business goals for achieving market leadership. It is imperative for the longevity of the organization that goods and services be made available to the customer at the most appropriate place, time, and price. Supply chains are contributing to achieving this organizational goal. A paradigm shift was observed in the past few decades when organizations competed as supply chains in the market more than an individual brand. This shift brought forward the importance of collaborative supply chains. Researchers in this study have presented the impact of IoT origins on real-time data on a collaborative supply chain model, including internally and externally aligned parameters. The study recommends the best model basis for the goodness of fit from the customer and vendor perspective for the automotive industry in India.

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Internet of Things (IoT) in Healthcare

Advances in Medical Technologies and Clinical Practice - Diagnostic Applications of Health Intelligence and Surveillance Systems ◽

10.4018/978-1-7998-6527-8.ch012 ◽

2021 ◽

pp. 237-258

Author(s):

Shashwat Pathak ◽

Shreyans Pathak

Keyword(s):

Internet Of Things ◽

Recent Decade ◽

Vital Role ◽

Healthcare Sector ◽

Smart Devices ◽

The Internet ◽

Time Data ◽

Iot Devices ◽

The Many ◽

Almost All

The recent decade has seen considerable changes in the way the technology interacts with human lives and almost all the aspects of life be it personal or professional has been touched by technology. Many smart devices have also started playing a vital role in many fields and domains and the internet of things (IoT) has been the harbinger of the advent of IoT devices. IoT devices have proven to be monumental in imparting ‘smartness' in the otherwise static machines. The ability of the devices to interact and transfer the data to the internet and ultimately to the end-user has revolutionized the technological world and has brought many seemingly disparate fields in the technological purview. Out of the many fields where IoT has started gaining momentum, one of the most important ones is the healthcare sector. Many wearable smart devices have been developed over time capable to transmit real-time data to hospitals and doctors. It is essential for tracking the progress of the critically ill patients and has opened the horizon for attending patients remotely using these smart devices.

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Information Security Transmission Technology in Internet of Things Control System

International Journal of Online Engineering (iJOE) ◽

10.3991/ijoe.v14i06.8707 ◽

2018 ◽

Vol 14 (06) ◽

pp. 177 ◽

Cited By ~ 1

Author(s):

Ying Zou ◽

Jiezhuo Lv

Keyword(s):

Control System ◽

Information Security ◽

Internet Of Things ◽

Basic Structure ◽

Information Storage ◽

Storage Device ◽

The Internet ◽

Time Data ◽

Control Equipment ◽

The Internet Of Things

<p class="0abstract"><span lang="EN-US">To solve the information security problem in Internet of things control system, the information security transmission technology was mainly discussed and studied, and the basic structure of networking control system was analyzed. From the main control equipment, communication equipment, control equipment, monitoring equipment, information storage device, connecting equipment and other aspects, the further research was carried out. Secondly, the structure of the Internet of things was studied, the security problems which may exist were discussed, and it was analyzed from the access security, transmission security and delays stability safety three aspects. Finally, the information security transmission technology based on the Internet of things control system was explored, and the encryption technology, authentication technology and isolation technology were analyzed in detail. The results showed that the networking control system not only had the advantages of transmission reliability, convenient interaction, and simple assembly, but also had the strengths of disperse structure, real-time data, remote monitoring and others. At last, it is summed up that the existing reliable communication resources are maximized in the transmission mechanism of the Internet of things. </span></p>

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Low-Cost Automatic Weather Stations in the Internet of Things

Information ◽

10.3390/info12040146 ◽

2021 ◽

Vol 12 (4) ◽

pp. 146

Author(s):

Konstantinos Ioannou ◽

Dimitris Karampatzakis ◽

Petros Amanatidis ◽

Vasileios Aggelopoulos ◽

Ilias Karmiris

Keyword(s):

Deep Learning ◽

Internet Of Things ◽

Low Cost ◽

The Internet ◽

Climatic Data ◽

Time Data ◽

New Era ◽

Observation Systems ◽

Weather Stations ◽

The Internet Of Things

Automatic Weather Stations (AWS) are extensively used for gathering meteorological and climatic data. The World Meteorological Organization (WMO) provides publications with guidelines for the implementation, installation, and usages of these stations. Nowadays, in the new era of the Internet of Things, there is an ever-increasing necessity for the implementation of automatic observing systems that will provide scientists with the real-time data needed to design and apply proper environmental policy. In this paper, an extended review is performed regarding the technologies currently used for the implementation of Automatic Weather Stations. Furthermore, we also present the usage of new emerging technologies such as the Internet of Things, Edge Computing, Deep Learning, LPWAN, etc. in the implementation of future AWS-based observation systems. Finally, we present a case study and results from a testbed AWS (project AgroComp) developed by our research team. The results include test measurements from low-cost sensors installed on the unit and predictions provided by Deep Learning algorithms running locally.

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IoT4Emergency

ACM SIGSOFT Software Engineering Notes ◽

10.1145/3437479.3437489 ◽

2021 ◽

Vol 46 (1) ◽

pp. 33-36

Author(s):

Julie Dugdale ◽

Mahyar T. Moghaddam ◽

Henry Muccini

Keyword(s):

Internet Of Things ◽

Emergency Management ◽

Real Time ◽

International Workshop ◽

The Internet ◽

Time Data ◽

Time Requirements ◽

Safety Systems ◽

Crises Management ◽

The Internet Of Things

The increasing natural and man-induced disasters such as res, earthquakes, oods, hurricanes, overcrowding, or pandemic viruses endanger human lives. Hence, designing infrastructures to handle those possible crises has become an ever-increasing need. The Internet of Things (IoT) has changed our approach to safety systems by connecting sensors and providing real-time data to managers, rescuers, and endangered people. IoT systems can monitor and react to progressive disasters, people's movements and their behavioral patterns. The community faces challenges in using IoT for crises management: i) how to take advantage of technological advancements and deal with IoT resources installation issues? ii) what environmental contexts should be considered while designing IoT-based emergency handling systems? iii) how should system design comply with various levels of real-time requirements? This paper reports on the results of the First International Workshop on Internet of Things for Emergency Management (IoT4Emergency 2020), which speci cally focuses on challenges and envisioned solutions in using smart connected systems to handle disasters.

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Performance analysis for similarity data fusion model for enabling time series indexing in internet of things applications

PeerJ Computer Science ◽

10.7717/peerj-cs.500 ◽

2021 ◽

Vol 7 ◽

pp. e500

Author(s):

Mina Younan ◽

Essam H. Houssein ◽

Mohamed Elhoseny ◽

Abd El-mageid Ali

Keyword(s):

Time Series ◽

Performance Analysis ◽

Internet Of Things ◽

Real Time ◽

The Internet ◽

Fusion Model ◽

Time Data ◽

Iot Applications ◽

Real Time Data ◽

Smart Things

The Internet of Things (IoT) has penetrating all things and objects around us giving them the ability to interact with the Internet, i.e., things become Smart Things (SThs). As a result, SThs produce massive real-time data (i.e., big IoT data). Smartness of IoT applications bases mainly on services such as automatic control, events handling, and decision making. Consumers of the IoT services are not only human users, but also SThs. Consequently, the potential of IoT applications relies on supporting services such as searching, retrieving, mining, analyzing, and sharing real-time data. For enhancing search service in the IoT, our previous work presents a promising solution, called Cluster Representative (ClRe), for indexing similar SThs in IoT applications. ClRe algorithms could reduce similar indexing by O(K − 1), where K is number of Time Series (TS) in a cluster. Multiple extensions for ClRe algorithms were presented in another work for enhancing accuracy of indexed data. In this theme, this paper studies performance analysis of ClRe algorithms, proposes two novel execution methods: (a) Linear execution (LE) and (b) Pair-merge execution (PME), and studies sorting impact on TS execution for enhancing similarity rate for some ClRe extensions. The proposed execution methods are evaluated with real examples and proved using Szeged-weather dataset on ClRe 3.0 and its extensions; where they produce representatives with higher similarities compared to the other extensions. Evaluation results indicate that PME could improve performance of ClRe 3.0 by = 20.5%, ClRe 3.1 by = 17.7%, and ClRe 3.2 by = 6.4% in average.

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