Internet of Things

2021 ◽  
pp. 81-112
Author(s):  
Vaibhav Bhatnagar ◽  
Ramesh Chandra
Keyword(s):  
Data Analysis ◽  
Internet Of Things ◽  
Sensors And Actuators ◽  
Transfer Data ◽  
Communication Technique ◽  
Information And Communication ◽  
Data Transferring ◽  
Agriculture Development ◽  
Data Acquiring ◽  
Conceptual Overview

Internet of things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. It has three layers. First layer is data acquisition through sensors and actuators, data transferring using different devices and last is data analysis with different analytic techniques. In this chapter, a conceptual overview of internet of things is mentioned. Different sensors and actuators which are responsible for data acquiring are described with their specification. Networking devices which are responsible for transferring data from sensors to server are also described with their applications. Data analytics techniques like descriptive, predictive, and perspective are also explained. Internet of things is now proven as boon for agriculture development. In the last section, different techniques are explained that are used in information and communication technique-enabled agriculture practices.

Architecture of IoT and Challenges

2021 ◽  
pp. 31-54
Author(s):  
Margaret Mary T. ◽  
Sangamithra A. ◽  
Ramanathan G.
Keyword(s):  
Internet Of Things ◽  
External Environment ◽  
The Internet ◽  
Sensors And Actuators ◽  
Ip Address ◽  
Complex Tasks ◽  
Transfer Data ◽  
Internal States ◽  
High Degree ◽  
Manual Assistance

Internet of things (IoT) architecture is an ecosystem of connected physical objects that are accessible through the internet. The ‘thing' in IoT could be a person with a heart monitor or an automobile with built-in-sensors (i.e., objects that have been assigned an IP address and have the ability to collect and transfer data over a network without manual assistance or intervention). The embedded technology in the objects helps them to interact with internal states or the external environment, which in turn affects the decisions taken. IoT world where all the devices and appliances are connected to a network and are used collaboratively to achieve complex tasks that require a high degree of intelligence, and IoT is an interaction between the physical and digital words using sensors and actuators. Furthermore, the IoT architecture may combine features and technologies suggested by various methodologies. IoT architecture is designed where the digital and real worlds are integrating and interacting constantly, and various technologies are merged together to form IoT.

scholarly journals Information and Communication Technology Solutions for the Circular Economy

2020 ◽  
Vol 12 (18) ◽  
pp. 7272 ◽  
Author(s):  
Konstantinos Demestichas ◽  
Emmanouil Daskalakis
Keyword(s):  
Data Analysis ◽  
Internet Of Things ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Circular Economy ◽  
Digital Platforms ◽  
Integral Role ◽  
Information And Communication ◽  
Virtual And Augmented Reality

The concept of circular economy (CE) is becoming progressively popular with academia, industry, and policymakers, as a potential path towards a more sustainable economic system. Information and communication technology (ICT) systems have influenced every aspect of modern life and the CE is no exception. Cutting-edge technologies, such as big data, cloud computing, cyber-physical systems, internet of things, virtual and augmented reality, and blockchain, can play an integral role in the embracing of CE concepts and the rollout of CE programs by governments, organizations, and society as a whole. The current paper conducts an extensive academic literature review on prominent ICT solutions paving the way towards a CE. For the categorization of the solutions, a novel two-fold approach is introduced, focusing on both the technological aspect of the solutions (e.g., communications, computing, data analysis, etc.), and the main CE concept(s) employed (i.e., reduce, reuse, recycle and restore) that each solution is the most relevant to. The role of each solution in the transition to CE is highlighted. Results suggest that ICT solutions related to data collection and data analysis, and in particular to the internet of things, blockchain, digital platforms, artificial intelligence algorithms, and software tools, are amongst the most popular solutions proposed by academic researchers. Results also suggest that greater emphasis is placed on the “reduce” component of the CE, although ICT solutions for the other “R” components, as well as holistic ICT-based solutions, do exist as well. Specific important challenges impeding the adoption of ICT solutions for the CE are also identified and reviewed, with consumer and business attitude, economic costs, possible environmental impacts, lack of education around the CE, and lack of familiarization with modern technologies being found among the most prominent ones.

STEGANOGRAPHIC METHODS FOR EMBEDDING INFORMATION IN DIGITAL OBJECTS TO PROVIDE INFORMATION SECURITY IN THE CONCEPT OF "INTERNET OF THINGS"

2019 ◽  
pp. 110-116
Author(s):  
Hristo Terziev
Keyword(s):  
Information Security ◽  
Internet Of Things ◽  
Information And Communication Technologies ◽  
Communication Technologies ◽  
Virtual Space ◽  
Least Significant Bit ◽  
Computer Environment ◽  
Information And Communication ◽  
Digital Objects ◽  
Effective Service

Internet of Things is a new world for connecting object space in the real world with virtual space in a computer environment. To build IoT as an effective service platform, end users need to trust the system. With the growing quantity of information and communication technologies, the need to ensure information security and improve data security is increasing. One of the potential solutions for this are steganographic methods. Steganography based on the least significant bit (LSB) is a popular and widely used method in the spatial domain.

IoT system of news by image for internal enterprise communication

2018 ◽  
Vol 1 (2) ◽  
pp. 12
Author(s):  
Pedro Vitor de Sousa Guimarães ◽  
Sandro César Silveira Jucá ◽  
Renata Imaculada Soares Pereira ◽  
Ayrton Alexsander Monteiro Monteiro
Keyword(s):  
Internet Of Things ◽  
Embedded System ◽  
Mobile Devices ◽  
Information And Communication Technology ◽  
Communication Technology ◽  
Internal Communication ◽  
Project Based Learning ◽  
The Internet ◽  
Digital Information ◽  
Information And Communication

This paper describes the use of a Linux embedded system for use in digital information and communication technology in order to generate image warnings using Internet of Things (IoT) prin- ciples. The proposed project generated a product, developed using concepts of project-based learning (ABP), called SECI (electronic internal communication system) that is accessed by students to view online warnings by distributed monitors and also by mobile devices connected to the Internet.

scholarly journals A monitoring method of semiconductor manufacturing processes using Internet of Things–based big data analysis

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771772181 ◽  
Author(s):  
Seok-Woo Jang ◽  
Gye-Young Kim
Keyword(s):  
Time Series ◽  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Real Time ◽  
Semiconductor Manufacturing ◽  
Reference Model ◽  
Big Data Analysis ◽  
Monitoring Method ◽  
Manufacturing Equipment

This article proposes an intelligent monitoring system for semiconductor manufacturing equipment, which determines spec-in or spec-out for a wafer in process, using Internet of Things–based big data analysis. The proposed system consists of three phases: initialization, learning, and prediction in real time. The initialization sets the weights and the effective steps for all parameters of equipment to be monitored. The learning performs a clustering to assign similar patterns to the same class. The patterns consist of a multiple time-series produced by semiconductor manufacturing equipment and an after clean inspection measured by the corresponding tester. We modify the Line, Buzo, and Gray algorithm for classifying the time-series patterns. The modified Line, Buzo, and Gray algorithm outputs a reference model for every cluster. The prediction compares a time-series entered in real time with the reference model using statistical dynamic time warping to find the best matched pattern and then calculates a predicted after clean inspection by combining the measured after clean inspection, the dissimilarity, and the weights. Finally, it determines spec-in or spec-out for the wafer. We will present experimental results that show how the proposed system is applied on the data acquired from semiconductor etching equipment.

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