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was stimulated using a 1cm × 1cm acrylic covered by a nitrile glove and driven by a programmable linear motor. All other signals were from human typing. 4.2.4.3 Signal Processing and Software Interface The signal acquisition, timing synchronization, and the graphical user interface were implemented using LabVIEW 2016. The signal processing including denoising, feature extraction and classification, was implemented with MATLAB® 2016b. Some core algorithms are accelerated with C++. 4.3 Self-Powered Wireless Optical Transmission of Mechanical Agitation Signals With the popularity of IoT, the ubiquitous existence of sensors has brought great convenience to daily life, but it also raised serious challenges to the wireless communication access.45, 46, 190 Current solutions for IoT communications are dominated by traditional radio frequency (RF) based techniques, e.g., the wireless local area networks (WLAN), Cellular, Bluetooth, Zigbee, and Radio-frequency identification (RFID) and etc.191-194 However, the RF band of the electromagnetic spectrum is fundamentally limited in capacity and costly since most sub-bands are exclusively licensed, resulting in spectrum crisis especially in the scenarios with dense sensors.195, 196 In this context, the optical wireless communications (OWC) which utilizes the huge and unlicensed optic bandwidth for data transmission, provides a promising alternative to alleviate the spectrum crisis.197- 199 Besides, the OWC technology has many other attractive features such as worldwide availability, radiation-free, and high-capacity, and thus is regarded as an appealing complementary communication solution for IoT applications.200 121PDF Image | HIGH PERFORMANCE TRIBOELECTRIC NANOGENERATOR AND ITS APPLICATIONS
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