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Design of Intelligent Sensor Network to Optimize Health Care Resources

机译:优化传感器资源的智能传感器网络设计

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Increase in number of people requiring medical care is caused by large number of baby boomers reaching retirement and passing of the Affordable Care Act (ACA). There are not enough medical professionals to meet this demand. This demand will be exasperated in the future as more and more people are shying away to go to medical school because of large costs involved. Also some of the recent medical graduates are choosing to reduce the number of hours of practice for various reasons. Smart intelligent remote monitoring system using wireless networks, smart sensors, and fuzzy logic have been discussed in the past. These methods mapped the sensor data into risk levels. The response time of the medical professional depends on the delays in receiving this information and the delay involved in processing the data before communicating to the right professional. This paper addresses the advantages of intelligent processing of sensor data at the patient level using fuzzy logic. We have also investigated the impact of communication technologies on End to End (Patient to medical facility) delay, energy consumption along with the reduction of response times after the data is received at the medical facility. In order to evaluate the performance of such a system, a simulation environment is implemented using OPNET.
机译:大量婴儿潮一代即将退休并通过《平价医疗法案》(ACA),导致需要医疗的人数增加。没有足够的医疗专业人员来满足这一需求。随着越来越多的人因为涉及高昂的费用而回避去医学院,这种需求在将来会变得更加恼怒。另外,由于种种原因,一些最近的医学毕业生也选择减少实习时间。过去已经讨论了使用无线网络,智能传感器和模糊逻辑的智能智能远程监控系统。这些方法将传感器数据映射到风险级别。医疗专业人员的响应时间取决于接收此信息的延迟以及在与合适的专业人员进行通信之前处理数据所涉及的延迟。本文阐述了使用模糊逻辑在患者级别智能处理传感器数据的优势。我们还研究了通信技术对端到端(患者到医疗机构)的延迟,能耗以及在医疗机构接收到数据后响应时间减少的影响。为了评估这种系统的性能,使用OPNET来实现仿真环境。

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