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Implementation of Wearable Devices and Indoor Positioning System for a Smart Hospital Environment

机译:智能医院环境中可穿戴设备和室内定位系统的实现

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This study attempts to develop a Wi-Fi signal based indoor positioning system (IPS) for implementation of a smart hospital. The proposed system is composed of an arduino platform, a RedBearLab CC3200 WiFi Mini module, Li-ion battery, speaker, OLED display, cloud server, and portable client devices. In the client end, the home-made wristbands are designed to receive the strength of Received Signal Strength Index (RSSI) signals, and the corresponding Media Access Controllers (MACs) are then sent to the cloud server via UDP/IP protocol. In the server end, the computation for the extracted RSSI is automatically performed by using the trilateration and fingerprinting. Because the Wi-Fi based RSSI is within a certain variation, the extracted valuable information is then analyzed by introducing the fuzzy logic and genetic algorithm to improve the robustness of the IPS in this study. Further, some restrictions consisting of movement speed and the wall separation, are considered to suppress unreasonable positions and minimize the measuring errors. Preliminary results indicate that the proposed method achieves the error distances about 2 meters and the miss-location for room identification is nearly zero. So, the developed wearable module has some advantages such as robustness, low-power consumption and high-efficiency for providing at least four days.
机译:这项研究试图开发基于Wi-Fi信号的室内定位系统(IPS),以实现智能医院。拟议的系统由arduino平台,RedBearLab CC3200 WiFi Mini模块,锂离子电池,扬声器,OLED显示器,云服务器和便携式客户端设备组成。在客户端,设计了腕带以接收接收信号强度指数(RSSI)信号的强度,然后将相应的媒体访问控制器(MAC)通过UDP / IP协议发送到云服务器。在服务器端,通过使用三边测量和指纹识别自动执行对提取的RSSI的计算。由于基于Wi-Fi的RSSI处于一定的变化范围内,因此在本研究中,通过引入模糊逻辑和遗传算法来分析提取的有价值信息,以提高IPS的鲁棒性。此外,还考虑了一些限制,包括移动速度和壁间距,以抑制不合理的位置并使测量误差最小。初步结果表明,该方法实现了约2米的误差距离,房间识别的失误位置几乎为零。因此,所开发的可穿戴模块具有至少四天的耐用性,低功耗和高效率等优点。

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