Ethereum Blockchain for Securing the Internet of Things: Practical Implementation and Performance Evaluation

2019 ◽  
Author(s):  
Subhi Alrubei ◽  
Jonathan Rigelsford ◽  
Callum Willis ◽  
Edward Ball
Keyword(s):  
Performance Evaluation ◽  
Internet Of Things ◽  
The Internet ◽  
Practical Implementation ◽  
And Performance ◽  
The Internet Of Things

Data collection of safety accidents in sports training of athletes with Internet of Things technology

2021 ◽  
pp. 1-7
Author(s):  
Zhiping Wang ◽  
Xinxin Zheng ◽  
Zhichen Yang
Keyword(s):  
Information Technology ◽  
Data Collection ◽  
Internet Of Things ◽  
The Internet ◽  
Sports Training ◽  
Accident Data ◽  
And Performance ◽  
Control Technologies ◽  
Internet Of Things Technology ◽  
The Internet Of Things

The Internet of Things (IoT) technology is an information technology developed in recent years with the development of electronic sensors, intelligence, network transmission and control technologies. This is the third revolution in the development of information technology. This article aims to study the algorithm of the Internet of Things technology, through the investigation of the hazards of athletes’ sports training, scientifically and rationally use the Internet of Things technology to collect data on safety accidents in athletes’ sports training, thereby reducing the risk of athletes’ sports training and making athletes better. In this article, the methods of literature research, analysis and condensing, questionnaire survey, theory and experiment combination, etc., investigate the safety accident data collection of the Internet of Things technology in athletes’ sports training, and provide certain theories and methods for future in-depth research practice basis. The experimental results in this article show that 82% of athletes who are surveyed under the Internet of Things technology will have partial injuries during training, reducing the risk of safety accidents in athletes’ sports training, and better enabling Chinese athletes to achieve a consistent level of competition and performance through a virtuous cycle of development.

scholarly journals Performance Evaluation and Validation of QCM (Query Control Mechanism) for QoS-Enabled Layered-Based Clustering for Reactive Flooding in the Internet of Things

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 283
Author(s):  
Fawad Ali Khan ◽  
Rafidah Md Noor ◽  
Miss Laiha Mat Kiah ◽  
Ismail Ahmedy ◽  
Mohd Yamani ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Energy Consumption ◽  
Internet Of Things ◽  
Control Mechanism ◽  
Performance Measure ◽  
The Internet ◽  
Control Mechanisms ◽  
Wide Range ◽  
The Internet Of Things ◽  
Network Flooding

Internet of Things (IoT) facilitates a wide range of applications through sensor-based connected devices that require bandwidth and other network resources. Enhancement of efficient utilization of a heterogeneous IoT network is an open optimization problem that is mostly suffered by network flooding. Redundant, unwanted, and flooded queries are major causes of inefficient utilization of resources. Several query control mechanisms in the literature claimed to cater to the issues related to bandwidth, cost, and Quality of Service (QoS). This research article presented a statistical performance evaluation of different query control mechanisms that addressed minimization of energy consumption, energy cost and network flooding. Specifically, it evaluated the performance measure of Query Control Mechanism (QCM) for QoS-enabled layered-based clustering for reactive flooding in the Internet of Things. By statistical means, this study inferred the significant achievement of the QCM algorithm that outperformed the prevailing algorithms, i.e., Divide-and-Conquer (DnC), Service Level Agreements (SLA), and Hybrid Energy-aware Clustering Protocol for IoT (Hy-IoT) for identification and elimination of redundant flooding queries. The inferential analysis for performance evaluation of algorithms was measured in terms of three scenarios, i.e., energy consumption, delays and throughput with different intervals of traffic, malicious mote and malicious mote with realistic condition. It is evident from the results that the QCM algorithm outperforms the existing algorithms and the statistical probability value “P” < 0.05 indicates the performance of QCM is significant at the 95% confidence interval. Hence, it could be inferred from findings that the performance of the QCM algorithm was substantial as compared to that of other algorithms.

scholarly journals Advances and Opportunities in Passive Wake-Up Radios with Wireless Energy Harvesting for the Internet of Things Applications

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3078 ◽  
Author(s):  
Hilal Bello ◽  
Zeng Xiaoping ◽  
Rosdiadee Nordin ◽  
Jian Xin
Keyword(s):  
Energy Harvesting ◽  
Internet Of Things ◽  
The Internet ◽  
Practical Implementation ◽  
Media Access Control ◽  
Rf Energy Harvesting ◽  
Harvesting Technique ◽  
Idle Listening ◽  
Rf Energy ◽  
The Internet Of Things

Wake-up radio is a promising approach to mitigate the problem of idle listening, which incurs additional power consumption for the Internet of Things (IoT) wireless transmission. Radio frequency (RF) energy harvesting technique allows the wake-up radio to remain in a deep sleep and only become active after receiving an external RF signal to ‘wake-up’ the radio, thus eliminating necessary hardware and signal processing to perform idle listening, resulting in higher energy efficiency. This review paper focuses on cross-layer; physical and media access control (PHY and MAC) approaches on passive wake-up radio based on the previous works from the literature. First, an explanation of the circuit design and system architecture of the passive wake-up radios is presented. Afterward, the previous works on RF energy harvesting techniques and the existing passive wake-up radio hardware architectures available in the literature are surveyed and classified. An evaluation of the various MAC protocols utilized for the novel passive wake-up radio technologies is presented. Finally, the paper highlights the potential research opportunities and practical challenges related to the practical implementation of wake-up technology for future IoT applications.

scholarly journals Some Aspects of Using the Concept of «the Internet of Things» in Crime Counteraction

2020 ◽  
Vol 14 (3) ◽  
pp. 453-460
Author(s):  
Aleksandr Smuskin
Keyword(s):  
Law Enforcement ◽  
Internet Of Things ◽  
Large Scale ◽  
The Internet ◽  
Practical Implementation ◽  
Smart Environment ◽  
Smart House ◽  
Smart Things ◽  
Smart Cars ◽  
The Internet Of Things

The author states that the era of the Internet of Things has come. It is noted that Russian law publications do not pay sufficient attention to the practical issues of law enforcement that arise from the implementation of the Internet of Things, specifically, criminalistic research and the use of smart things by law enforcement bodies. This study a first attempt at a general criminalistic analysis of implementing the concept of the Internet of Things in Russian research publications. While analyzing the practical implementation of this concept, the author concludes that it is necessary not just to single out a smart house, a smart car or smart things as different categories, but to unite them into a system of smart environment. It is noted that the elements of the public sphere of application for the Internet of Things deserve separate studies, while this article will only focus on everyday application. Modern obstacles to a large-scale implementation of the Internet of Things are identified. The criminalistic research of the Internet of Things and smart environment makes it possible to identify key systems that modern appliances form in this sphere, requirements to them, subsystems of a smart house, functions of smart cars and gadgets. It is stated that the criminalistic research of the subsystems of smart environment is possible with the help of scientific criminalistic findings in the sphere of electronic digital traces and electronic evidence. Key points of finding these traces are identified. The author methodically analyzes the kinds of criminalistically relevant information that could be obtained through the examination of sensors and the memory of smart things, a smart car and a smart house. The author also determines the functions whose analysis is vital for collecting evidentiary and orientation information. It is stated that all information from sensors and information devices is, in the end, accumulated in the management center, as well as in cloud and network services servers that work with the Internet of Things. It is stressed that all interactions with electronic digital traces in the devices that implement the concept of the Internet of Things should happen with the participation of a specialist to avoid a loss of data.

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