Mohammed Moutaib;Tarik Ahajjam;Mohammed Fattah;Yousef Farhaoui;Badraddine Aghoutane;Moulhime El Bekkali
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However, these issues significantly slow down the development and rapid deployment of this technology. The main causes of wasted energy from connected objects include collisions that occur when two or more nodes send data simultaneously and the leading cause of data retransmission that occurs when a collision occurs or when data are not received correctly due to channel fading. The distance between nodes is one of the factors influencing energy consumption. In this article, we have proposed direct communication between nodes to avoid collision domains, which will help reduce data retransmission. The results show that the distribution can ensure the performance of the system under general conditions compared to the centralization and to the existing works.","PeriodicalId":52355,"journal":{"name":"Big Data Mining and Analytics","volume":"5 4","pages":"302-308"},"PeriodicalIF":7.7000,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8254253/9832761/09832765.pdf","citationCount":"1","resultStr":"{\"title\":\"Application of Internet of Things in the Health Sector: Toward Minimizing Energy Consumption\",\"authors\":\"Mohammed Moutaib;Tarik Ahajjam;Mohammed Fattah;Yousef Farhaoui;Badraddine Aghoutane;Moulhime El Bekkali\",\"doi\":\"10.26599/BDMA.2021.9020031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Internet of Things (IoT) is currently reflected in the increase in the number of connected objects, that is, devices with their own identity and computing and communication capacities. 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Application of Internet of Things in the Health Sector: Toward Minimizing Energy Consumption
The Internet of Things (IoT) is currently reflected in the increase in the number of connected objects, that is, devices with their own identity and computing and communication capacities. IoT is recognized as one of the most critical areas for future technologies, gaining worldwide attention. It applies to many areas, where it has achieved success, such as healthcare, where a patient is monitored using nodes and lightweight sensors. However, the powerful functions of IoT in the medical field are based on communication, analysis, processing, and management of data autonomously without any manual intervention, which presents many difficulties, such as energy consumption. However, these issues significantly slow down the development and rapid deployment of this technology. The main causes of wasted energy from connected objects include collisions that occur when two or more nodes send data simultaneously and the leading cause of data retransmission that occurs when a collision occurs or when data are not received correctly due to channel fading. The distance between nodes is one of the factors influencing energy consumption. In this article, we have proposed direct communication between nodes to avoid collision domains, which will help reduce data retransmission. The results show that the distribution can ensure the performance of the system under general conditions compared to the centralization and to the existing works.
期刊介绍:
Big Data Mining and Analytics, a publication by Tsinghua University Press, presents groundbreaking research in the field of big data research and its applications. This comprehensive book delves into the exploration and analysis of vast amounts of data from diverse sources to uncover hidden patterns, correlations, insights, and knowledge.
Featuring the latest developments, research issues, and solutions, this book offers valuable insights into the world of big data. It provides a deep understanding of data mining techniques, data analytics, and their practical applications.
Big Data Mining and Analytics has gained significant recognition and is indexed and abstracted in esteemed platforms such as ESCI, EI, Scopus, DBLP Computer Science, Google Scholar, INSPEC, CSCD, DOAJ, CNKI, and more.
With its wealth of information and its ability to transform the way we perceive and utilize data, this book is a must-read for researchers, professionals, and anyone interested in the field of big data analytics.