scholarly journals How to Put Predictive Maintenance to use on the Internet of Things

2021 ◽  
Author(s):  
Aymeric Goldsteinas
Keyword(s):  
Internet Of Things ◽  
Real Life ◽  
Heat Treating ◽  
Predictive Maintenance ◽  
The Internet ◽  
Part Quality ◽  
Business Cases ◽  
Potential Part ◽  
The Internet Of Things ◽  
Hot Zone

Abstract In an ever-changing world of increased automation and process efficiencies, and with Industry 4.0 and the Internet of Things at the forefront of these efforts, the most successful heat treaters globally employ a predictive maintenance platform that allows them to anticipate disruption before it occurs. In this presentation, you will:• Understand how costs associated with furnace downtime compare with and without predictive maintenance.• Learn the fundamentals of predictive maintenance and how it’s changing the heat treating industry.• Hear a series of practical, data-driven examples in which the software anticipated hazards—like a broken (open) heating element or diffusion pump heater failure—avoiding potential part quality issues and hot zone damage.• See real-life business cases on aged furnaces, where the risk and frequency of unplanned downtime is significantly higher. We will show all the benefits of monitoring furnace health with real-time diagnoses.

scholarly journals Concept, Possibilities and Pilot-Testing of a New Smartphone Application for the Social and Life Sciences to Study Human Behavior Including Validation Data from Personality Psychology

J ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 102-115 ◽  
Author(s):  
Christian Montag ◽  
Harald Baumeister ◽  
Christopher Kannen ◽  
Rayna Sariyska ◽  
Eva-Maria Meßner ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Human Behavior ◽  
Real Life ◽  
Smartphone Application ◽  
Self Report ◽  
The Internet ◽  
Validation Data ◽  
Personality Psychology ◽  
The Social ◽  
The Internet Of Things

With the advent of the World Wide Web, the smartphone and the Internet of Things, not only society but also the sciences are rapidly changing. In particular, the social sciences can profit from these digital developments, because now scientists have the power to study real-life human behavior via smartphones and other devices connected to the Internet of Things on a large-scale level. Although this sounds easy, scientists often face the problem that no practicable solution exists to participate in such a new scientific movement, due to a lack of an interdisciplinary network. If so, the development time of a new product, such as a smartphone application to get insights into human behavior takes an enormous amount of time and resources. Given this problem, the present work presents an easy way to use a smartphone application, which can be applied by social scientists to study a large range of scientific questions. The application provides measurements of variables via tracking smartphone–use patterns, such as call behavior, application use (e.g., social media), GPS and many others. In addition, the presented Android-based smartphone application, called Insights, can also be used to administer self-report questionnaires for conducting experience sampling and to search for co-variations between smartphone usage/smartphone data and self-report data. Of importance, the present work gives a detailed overview on how to conduct a study using an application such as Insights, starting from designing the study, installing the application to analyzing the data. In the present work, server requirements and privacy issues are also discussed. Furthermore, first validation data from personality psychology are presented. Such validation data are important in establishing trust in the applied technology to track behavior. In sum, the aim of the present work is (i) to provide interested scientists a short overview on how to conduct a study with smartphone app tracking technology, (ii) to present the features of the designed smartphone application and (iii) to demonstrate its validity with a proof of concept study, hence correlating smartphone usage with personality measures.

The Key Technology and Application of the Internet of Things

2014 ◽  
Vol 644-650 ◽  
pp. 2812-2815 ◽  
Author(s):  
Cui Mei Li ◽  
Rou Wang ◽  
Le Huang
Keyword(s):  
Internet Of Things ◽  
Real Life ◽  
The Internet ◽  
Third Wave ◽  
Information Industry ◽  
Key Technology ◽  
The Third ◽  
World Information ◽  
Strategic Advice ◽  
The Internet Of Things

The Internet of Things, which is another revolution in the information industry following the computer and the Internet, is referred to as the third wave of the world information industry. In this paper, the concepts, the architecture system and the principle, and the key technology in the Internet of Things and its application in real life are presented. Finally, a strategic advice on the development of the Internet of Things in China is put forward.

Leveraging the Internet of Things (IoT) Paradigm Towards Smarter Applications

2019 ◽  
pp. 306-324
Author(s):  
E. A. Neeba ◽  
J. Aswini ◽  
R. Priyadarshini
Keyword(s):  
Internet Of Things ◽  
Real Life ◽  
Smart Devices ◽  
The Internet ◽  
Evidence Based ◽  
Theoretical Studies ◽  
Basic Requirement ◽  
Research Focus ◽  
Intelligent Processing ◽  
The Internet Of Things

Intelligent processing with smart devices and informative communications in everyday tasks brings an effective platform for the internet of things (IOT). Internet of things is seeking its own way to be the universal solution for all the real-life scenarios. Even though many theoretical studies pave the basic requirement for the internet of things, still the evidence-based learning (EBL) is lacking to deal with the application of the internet of things. As a contribution of this chapter, the basic requirements to study about internet of things with its deployment architecture for mostly enhanced applications are analyzed. This shows researchers how to initiate their research focus with the utilization of internet of things.

scholarly journals Analysis of an Intelligent Graphical Tutoring System using the Internet of Things (IoT) to Develop the Competency of Embedded Systems

2019 ◽  
Vol 15 (04) ◽  
pp. 98
Author(s):  
Jiragorn Chalermdit ◽  
Prachyanun Nilsook ◽  
Panita Wannapiroon
Keyword(s):  
Internet Of Things ◽  
Embedded Systems ◽  
Intelligent System ◽  
Real Life ◽  
The Internet ◽  
Tutoring System ◽  
System Suitability ◽  
Research Findings ◽  
High Level ◽  
The Internet Of Things

<p class="0abstract">The objectives of this research are to analyse and assess an intelligent graphical tutoring system using the internet of things (IoT) to develop the efficiency of embedded systems. The research findings suggest that an intelligent system is composed of six modules: 1) student, 2) graphical tutoring, 3) expert, 4) knowledge, 5) evaluation and 6) user interface. The result of a composition assessment performed by experts indicates that the overall results are at a high level. The system suitability scored the highest level which can be applied to real life situations.</p>

scholarly journals Designing Smart Home (IOT) Using Cisco Packet Tracer 7.2 Simulator

2020 ◽  
Vol 6 (12) ◽  
pp. 208-216
Author(s):  
Tanishka and Prof. Shikha Gupta
Keyword(s):  
Internet Of Things ◽  
Smart Home ◽  
Data Exchange ◽  
Real Life ◽  
The Internet ◽  
Different Types ◽  
Life Issues ◽  
Packet Tracer ◽  
Iot Devices ◽  
The Internet Of Things

The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Internet of Things (IoT) is rapidly gaining momentum in the scenario of telecommunications. Conventional networks allow for interactivity and data exchange, but these networks have not been designed for the new features and functions of IoT devices. In this paper, an algorithm is proposed to share common recourse among Things, that is, between different types of smart appliances. . Purpose is to analyze deeper the cases separating the network and IoT layout, giving a deeper explanation of the purpose of the simulations, presenting all the information needed to utilize the exercises but also giving suggestion how to expand the exercises further. This implementation can be implemented effectively using package tracking software that includes IoT functions to control and simulate a smart home. IoT technology can be applied to many real life issues, such as: homework, treatment, campus, office, etc.

scholarly journals Research on the Construction of Intelligent Fire Protection Virtual Simulation Teaching Platform Based on Internet of Things

2021 ◽  
Vol 11 (10) ◽  
pp. 450-455
Author(s):  
Guiling Sun ◽  
◽  
Sirui Wang ◽  
Hai Wang ◽  
Yi Gao
Keyword(s):  
Internet Of Things ◽  
Data Storage ◽  
Fire Protection ◽  
Real Life ◽  
Social Background ◽  
Virtual Simulation ◽  
The Internet ◽  
Wireless Sensor Node ◽  
Teaching Platform ◽  
The Internet Of Things

Aiming at the teaching challenge of cultivating integrated talents of Internet of things worldwide, and combining with the social background of fire rescue and management problems, We propose a virtual simulation teaching platform for the Internet of Things under the background of intelligent fire protection application. Based on the overall structure of the Internet of Things, different fire scenarios that cannot be simulated in real life are constructed through virtual simulation technology. OMNet++ technology is adopted to carry out virtual deployment of fire nodes for the overall structure of the building, and experiments such as cluster routing simulation, communication transmission simulation and wireless sensor node data acquisition simulation are designed. Meanwhile, a 3D fire data model is established using big data to simulate the best fire extinguishing scheme and the best escape strategy. From aspects of the Internet of Things system design and development, sensor principle and application, Internet of Things communication technology and Internet of Things data storage and application, we have realized the efficiency, innovation and challenge of the Internet of Things teaching.The virtual simulation teaching platform we built has been deployed and put into practical teaching, which has received positive response from students and achieved excellent teaching effect.

scholarly journals Applications of 3D Image Using Internet of Things in the Exhibition of Classical Architecture Art Style

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Xusheng Xie ◽  
Xin Wen ◽  
Fengfeng Deng
Keyword(s):  
Internet Of Things ◽  
Cultural Heritage ◽  
Real World ◽  
Real Life ◽  
Policy Formulation ◽  
The Internet ◽  
3D Image ◽  
Architectural Heritage ◽  
Classical Architecture ◽  
The Internet Of Things

Classical architecture is an architectural, cultural heritage with specific historical value. It is also a city with historical and cultural heritage and even a testimony of the profound historical culture of a country. Therefore, urbanization is unavoidable, and it directly influences historical buildings. This study aims to combine the three-dimensional image techniques and the Internet of Things (IoT) technology to research the development of classical architectural artistic style. This article presents the acquisition equipment, methods, precautions, and data processing of real-life 3D image data of the classical architectural heritage. We realized the online publishing of real-world 3D services of classical architectural heritage through the real-world 3D display system developed through the Internet of Things and mobile terminals. The model was verified through simulation tests. The combination of image processing techniques and analysis methods such as simulated annealing improved the accuracy of the prediction model. The proposed model can provide data support for policy formulation, technical intervention, and targeted field investigation on architectural heritage by screening research objects.

scholarly journals Detection and Mitigation of RPL Rank and Version Number Attacks in the Internet of Things: SRPL-RP

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 5997
Author(s):  
Zahrah A. Almusaylim ◽  
NZ Jhanjhi ◽  
Abdulaziz Alhumam
Keyword(s):  
Internet Of Things ◽  
Routing Protocol ◽  
Smart Cities ◽  
Real Life ◽  
Average Energy ◽  
The Internet ◽  
Delivery Ratio ◽  
Lossy Networks ◽  
Average Energy Consumption ◽  
The Internet Of Things

The rapid growth of the Internet of Things (IoT) and the massive propagation of wireless technologies has revealed recent opportunities for development in various domains of real life, such as smart cities and E-Health applications. A slight defense against different forms of attack is offered for the current secure and lightweight Routing Protocol for Low Power and Lossy Networks (RPL) of IoT resource-constrained devices. Data packets are highly likely to be exposed in transmission during data packet routing. The RPL rank and version number attacks, which are two forms of RPL attacks, can have critical consequences for RPL networks. The studies conducted on these attacks have several security defects and performance shortcomings. In this research, we propose a Secure RPL Routing Protocol (SRPL-RP) for rank and version number attacks. This mainly detects, mitigates, and isolates attacks in RPL networks. The detection is based on a comparison of the rank strategy. The mitigation uses threshold and attack status tables, and the isolation adds them to a blacklist table and alerts nodes to skip them. SRPL-RP supports diverse types of network topologies and is comprehensively analyzed with multiple studies, such as Standard RPL with Attacks, Sink-Based Intrusion Detection Systems (SBIDS), and RPL+Shield. The analysis results showed that the SRPL-RP achieved significant improvements with a Packet Delivery Ratio (PDR) of 98.48%, a control message value of 991 packets/s, and an average energy consumption of 1231.75 joules. SRPL-RP provided a better accuracy rate of 98.30% under the attacks.

Advanced Enterprise Asset Management Systems: Improve Predictive Maintenance and Asset Performance by Leveraging Industry 4.0 and the Internet of Things (IoT)

2021 ◽  
Author(s):  
Sandeep Bhanji ◽  
Howard Shotz ◽  
Sravani Tadanki ◽  
Youssef Miloudi ◽  
Patrick Warren
Keyword(s):  
Internet Of Things ◽  
Asset Management ◽  
Leading Edge ◽  
Predictive Maintenance ◽  
The Internet ◽  
Time Data ◽  
Management Scenarios ◽  
Intelligent Sensors ◽  
Reliability Centered Maintenance ◽  
The Internet Of Things

Abstract Advanced Enterprise Asset Management (EAM) is an approach through which an organization’s assets are systematically and proactively managed throughout their lifecycle — from installation through disposition. The objective of EAM is to prolong the service life and maximize utilization of the assets via adoption of leading-edge standards, practices, and technology. Organizations that implement advanced EAM benefit from reduced operating expenses (OPEX), reduced capital replacement expenses (CAPEX), increased uptime, and overall higher quality asset capability within their portfolio. Successful EAM leverages ISO55000 & IAM 2.0 standards to implement predictive, proactive and reliability centered maintenance best practices. Implementing an EAM provides leading edge technology to the rail industry to track and audit maintenance work using mobility tools, heads-up virtual reality displays, augmented reality expertise and the Internet of Things (IoT); combined with artificial intelligence and machine learning to bolster predictive maintenance and simulate asset performance based on different scenarios. EAM will evolve rapidly following the world’s rapid transformation into the IoT over the next decade. As rail and transit assets become outfitted with interconnected intelligent sensors whose outputs are collected via active and passive devices, real-time data is available for EAM to track, plan and upgrade assets. As systems are modernized, EAM will leverage the IoT revolution to provide critical information to operations in planning railway management scenarios, including predictive maintenance functionality and edge analytics.

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