KEYWORDS: Education and training, Data modeling, Principal component analysis, Tunable filters, Receivers, Matrices, Linear filtering, Transmitters, Signal attenuation, Interference (communication)
The demand for fall detection technology in elderly individuals is increasing due to the growing global aging population. Wi-Fi's Channel State Information (CSI) based fall detection is gaining popularity as it does not require the installation of expensive cameras or sensors, is not affected by lighting and obstructions, and protects individual privacy. However, previous studies using commercial Wi-Fi and mobile hosts to acquire CSI and recognize falls are expensive. To address this issue, this paper proposes a low-cost fall detection solution based on ESP32-S3 and LSTM model. The proposed solution collects data from 52 subcarriers in the L-LTF, applies Butterworth low-pass filter, and PCA to reduce data dimensionality. The LSTM model achieves a testing accuracy of 96.03%, with 89% classification accuracy for falls. This solution can significantly reduce the cost of fall detection technology and has potential deployment on ESP32-S3. Future research could focus on improving accuracy or exploring different application scenarios.
Aiming at the problems of poor adaptability and insufficient functions of existing exploration robots in different caves and dangerous areas, this paper proposes a multi-wheel drive binocular exploration robot based on ROS system, which uses laser radar sensor and binocular depth vision camera to collect environmental data. The Gmapping algorithm is used to realize the real-time positioning and accurate map building of the robot system. The CCD vision camera collects the data of the exploration area in real time, and transmits the data to the host computer for analysis and processing. Through the ROS open source system, it is convenient to control the robot and receive the mapping data, navigation data and exploration data of the robot system on the upper computer. Through experiments,Compared with the existing exploration system, the system has the characteristics of low hardware cost, easy mastery, easy modification, strong function expandability and the like; This project has a very high application value in the exploration of caves and dangerous areas.
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