MEDCO: an efficient protocol for data compression in wireless body sensor network

3区 计算机科学 Q1 Computer Science Journal of Ambient Intelligence and Humanized Computing Pub Date : 2024-09-14 DOI:10.1007/s12652-024-04858-z
Firas Salika, Hassan Harb, Chamseddine Zaki, Eric Saux
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Abstract

This paper introduces a new protocol named MEDCO for eMErgency Detection and COmpression, designed to minimize data transmission and optimize sensor energy usage in wireless body sensor networks. MEDCO operates in two stages. The first stage assesses the patient’s condition based on vital signs and compares it with the previous state to determine if the data should be transmitted to medical staff. Data is only sent if a change in the patient’s situation is detected. The second stage focuses on compressing the identified data using two algorithms: range and changed vital signs methods. The range method classifies patient readings into ranges based on the current health situation before compressing them. At the same time, the changed vital signs algorithm considers both current and previous situations during compression. Through simulations using actual patient data, we demonstrated the effectiveness of our protocol in reducing data transmission by 97% while maintaining a high level of accuracy in the transmitted information. The range method outperforms by achieving an additional data reduction of 34.6% compared to the selected protocol from state of the art, and the changed vital signs method achieves a reduction of 6.4%.

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MEDCO:无线人体传感器网络中的高效数据压缩协议
本文介绍了一种名为 "紧急检测和压缩"(MEDCO for eMErgency Detection and COmpression)的新协议,旨在尽量减少无线人体传感器网络中的数据传输并优化传感器的能源使用。MEDCO 分两个阶段运行。第一阶段根据生命体征评估病人的状况,并与之前的状态进行比较,以确定是否应将数据传输给医务人员。只有在检测到病人情况发生变化时,才会发送数据。第二阶段的重点是使用两种算法压缩已识别的数据:范围法和生命体征变化法。范围法根据当前的健康状况将病人的读数分为不同的范围,然后再进行压缩。同时,生命体征变化算法在压缩过程中会考虑当前和之前的情况。通过使用实际病人数据进行模拟,我们证明了我们的协议能有效减少 97% 的数据传输,同时保持传输信息的高准确性。与最新技术中的选定协议相比,范围法的性能更胜一筹,额外减少了 34.6% 的数据,而生命体征变化法则减少了 6.4%。
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来源期刊
Journal of Ambient Intelligence and Humanized Computing
Journal of Ambient Intelligence and Humanized Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
9.60
自引率
0.00%
发文量
854
期刊介绍: The purpose of JAIHC is to provide a high profile, leading edge forum for academics, industrial professionals, educators and policy makers involved in the field to contribute, to disseminate the most innovative researches and developments of all aspects of ambient intelligence and humanized computing, such as intelligent/smart objects, environments/spaces, and systems. The journal discusses various technical, safety, personal, social, physical, political, artistic and economic issues. The research topics covered by the journal are (but not limited to): Pervasive/Ubiquitous Computing and Applications Cognitive wireless sensor network Embedded Systems and Software Mobile Computing and Wireless Communications Next Generation Multimedia Systems Security, Privacy and Trust Service and Semantic Computing Advanced Networking Architectures Dependable, Reliable and Autonomic Computing Embedded Smart Agents Context awareness, social sensing and inference Multi modal interaction design Ergonomics and product prototyping Intelligent and self-organizing transportation networks & services Healthcare Systems Virtual Humans & Virtual Worlds Wearables sensors and actuators
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