scholarly journals Research on Workshop-Based Positioning Technology Based on Internet of Things in Big Data Background

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
FengChun Liu ◽  
YaLou Liu ◽  
DongHao Jin ◽  
XueYong Jia ◽  
TingTing Wang
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Internet Of Things ◽  
Signal Strength ◽  
The Internet ◽  
Localization Algorithm ◽  
The Difference ◽  
Positioning Algorithm ◽  
Received Signal Strength Indication ◽  
The Internet Of Things

This paper first analyzes the data collection and data management of the workshop, obtains the data of the workshop changes with time, and accumulates the data. There are bottleneck problems such as big data being difficult to be fully used. Then, the concept of the Internet of Things was introduced into the workshop positioning to realize the comprehensive use of the big data in the workshop. Finally, aiming at the positioning problem of manufacturing workshop items, the ZigBee positioning algorithm, the received signal strength indication algorithm RSSI and the trilateration algorithm, is applied, and the trilateral positioning algorithm is applied to the CC2430 wireless MCU, and the positioning node is designed and implemented. The three-sided localization algorithm was used to locate and simulate the horizontal and vertical comparisons of six groups of workshop terminals. The results showed that the difference between the simulated position and the actual position did not exceed 1m, which was in line with the positioning requirements of the workshop.

Challenges and Solutions of Big Data and IoT

2019 ◽  
pp. 264-272
Author(s):  
Jayashree K. ◽  
Abirami R. ◽  
Rajeswari P.
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Collection ◽  
Internet Of Things ◽  
Data Processing ◽  
The Internet ◽  
Huge Amount ◽  
Collection Data ◽  
Different Sources ◽  
The Internet Of Things

The successful development of big data and the internet of things (IoT) is increasing and influencing all areas of technologies and businesses. The rapid increase of more devices that are connected to IoT from which enormous amount of data are consumed indicates the way how big data is related with IoT. Since huge amount of data are obtained from different sources, analysis of these data involves much of processing at each and every level to extract knowledge for decision making process. To manage big data in a continuous network that keeps expanding leads to few issues related to data collection, data processing, analytics, and security. To address these issues, certain solution using bigdata approach in IoT are examined. Combining these two areas provides several opportunities developing new systems and identify advanced techniques to solve challenges on big data and IoT.

scholarly journals Lightweight Coordination Patterns for Applications of the Internet of Things

2020 ◽  
Vol 25 (2) ◽  
pp. 117-123
Author(s):  
Waseem Akhtar Mufti
Keyword(s):  
Big Data ◽  
Data Collection ◽  
Internet Of Things ◽  
Computer Network ◽  
Programming Model ◽  
Data Communication ◽  
The Internet ◽  
Automatic Data ◽  
Distributed Cluster ◽  
The Internet Of Things

AbstractApplications of the Internet of Things (IoT) are famously known for connecting devices via the internet. The main purpose of IoT systems (wireless or wired) is to connect devices together for data collection, buffering and data gateway. The collected large size of data is often captured from remote sources for automatic data analytics or for direct decision making by its users. This paper applies the programming pattern for Big Data in IoT systems that makes use of lightweight Java methods, introduced in the recently published work on ClientNet Distributed Cluster. Considering Big Data in IoT systems means the sensing of data from different resources, the network of IoT devices collaborating in data collection and processing; and the gateways servers where the resulting big data is supposed to be directed or further processed. This mainly involves resolving the issues of Big Data, i.e., the size and the network transfer speed along with many other issues of coordination and concurrency. The computer network that connects IoT may further include techniques such as Fog and Edge computing that resolve much of the network issues. This paper provides solutions to these problems that occur in wireless and wired systems. The talk is about the ClientNet programming model and its application in IoT systems for orchestration, such as coordination, data communication, device identification and synchronization between the gateway servers and devices. These devices include sensors attached with appliances (e.g., home automations, supply chain systems, light and heavy machines, vehicles, power grids etc.) or buildings, bridges and computers running data processing applications. As described in earlier papers, the introduced ClientNet techniques prevent from big data transfers and streaming that occupy more resources (hardware and bandwidth) and time. The idea is motivated by Big Data problems that make it difficult to collect it from different resources through small devices and then redirecting it. The proposed programming model of ClientNet Distributed Cluster stores Big Data on the nearest server coordinated by the nearest coordinator. The gateways and the systems that run analytics programs communicate by running programs from other computers when it is essentially required. This makes it possible to let Big Data rarely move across a communication network and allow only the source code to move around the network. The given programming model greatly simplifies data communication overheads, communication patterns among devices, networks and servers.

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.

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