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A Low Cost Wireless Acoustic Sensor for Ambient Assisted Living Systems

机译:用于环境辅助生活系统的低成本无线声学传感器

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摘要

Ambient Assisted Living (AAL) has become an attractive research topic due to growing interest in remote monitoring of older people. Development in sensor technologies and advances in wireless communications allows to remotely offer smart assistance and monitor those people at their own home, increasing their quality of life. In this context, Wireless Acoustic Sensor Networks (WASN) provide a suitable way for implementing AAL systems which can be used to infer hazardous situations via environmental sounds identification. Nevertheless, satisfying sensor solutions have not been found with the considerations of both low cost and high performance. In this paper, we report the design and implementation of a wireless acoustic sensor to be located at the edge of a WASN for recording and processing environmental sounds which can be applied to AAL systems for personal healthcare because it has the following significant advantages: low cost, small size, audio sampling and computation capabilities for audio processing. The proposed wireless acoustic sensor is able to record audio samples at least to 10 kHz sampling frequency and 12-bit resolution. Also, it is capable of doing audio signal processing without compromising the sample rate and the energy consumption by using a new microcontroller released at the last quarter of 2016. The proposed low cost wireless acoustic sensor has been verified using four randomness tests for doing statistical analysis and a classification system of the recorded sounds based on audio fingerprints.
机译:由于对老年人的远程监测的兴趣日益增长,环境辅助生活(AAL)已成为一个有吸引力的研究课题。传感器技术的开发和无线通信的进步允许远程提供智能帮助,并在自己的家中监控这些人,提高他们的生活质量。在这种情况下,无线声学传感器网络(WASN)提供了一种用于实现AAL系统的合适方式,该系统可以通过环境声音识别来推断出危险情况。然而,尚未发现满足传感器解决方案,考虑到低成本和高性能。在本文中,我们报告了无线声学传感器的设计和实现位于WASN的边缘,用于记录和处理环境声音,这些声音可以应用于个人医疗保健的AAL系统,因为它具有以下显着优势:低成本音频处理的小尺寸,音频采样和计算能力。所提出的无线声学传感器能够记录至少10kHz采样频率和12位分辨率的音频样本。此外,它能够在不损害对2016年度释放的新微控制器的情况下进行音频信号处理,而不会影响采样率和能量消耗。所提出的低成本无线声学传感器已经使用四个随机性测试来进行统计分析进行验证以及基于音频指纹的录制声音的分类系统。

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