{"title":"Cognitive Radio Sensor Network-Based Urgent Communication for Field Hospitals","authors":"Huseyin Ekici;Muhammed Enes Bayrakdar","doi":"10.1109/JSEN.2024.3519494","DOIUrl":null,"url":null,"abstract":"In this study, a medical sensor network structure based on cognitive wireless regional area network (WRAN) technology is proposed for urgent communication in field hospitals. WRAN technology is based on cognitive radio network approach, which is exploited for opportunistic spectrum access in places without internet access. In cognitive radio-based WRAN technology, a consumer premises equipment (CPE) and a base station communicate opportunistically by sensing available radio channels. In our network structure, CPEs use the time-division multiple access (TDMA) technique with channel bonding to detect patient-related data and transmit it to the base station. With the help of our node placement approach, many sensor nodes were placed in the field hospital environment. Because urgent communication is important in field hospitals, a fuzzy logic-based relay selection approach is proposed to improve network sustainability. Sensor nodes are placed to cover the entire region to detect parameters around the field hospital. The values detected by the sensor nodes were collected by the collector station fixed in the center. The simulation model of our proposed approach was implemented using riverbed modeler software. Thanks to our proposed node placement and relay node selection approaches, the field hospital was monitored safely with a minimum number of wireless sensor nodes.","PeriodicalId":447,"journal":{"name":"IEEE Sensors Journal","volume":"25 3","pages":"5595-5602"},"PeriodicalIF":4.3000,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Journal","FirstCategoryId":"103","ListUrlMain":"https://ieeexplore.ieee.org/document/10812719/","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, a medical sensor network structure based on cognitive wireless regional area network (WRAN) technology is proposed for urgent communication in field hospitals. WRAN technology is based on cognitive radio network approach, which is exploited for opportunistic spectrum access in places without internet access. In cognitive radio-based WRAN technology, a consumer premises equipment (CPE) and a base station communicate opportunistically by sensing available radio channels. In our network structure, CPEs use the time-division multiple access (TDMA) technique with channel bonding to detect patient-related data and transmit it to the base station. With the help of our node placement approach, many sensor nodes were placed in the field hospital environment. Because urgent communication is important in field hospitals, a fuzzy logic-based relay selection approach is proposed to improve network sustainability. Sensor nodes are placed to cover the entire region to detect parameters around the field hospital. The values detected by the sensor nodes were collected by the collector station fixed in the center. The simulation model of our proposed approach was implemented using riverbed modeler software. Thanks to our proposed node placement and relay node selection approaches, the field hospital was monitored safely with a minimum number of wireless sensor nodes.
期刊介绍:
The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following:
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-Optical Sensors
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-Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting
-Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data)
-Sensors in Industrial Practice