Journal ArticleDOI
Device-Free Sensing for Personnel Detection in a Foliage Environment
Reads0
Chats0
TLDR
This is the first time that a DFS-based sensing approach is demonstrated to have a potential to distinguish between human and small-animal targets in a foliage environment.Abstract:
In this letter, the possibility of using device-free sensing (DFS) technology for personnel detection in a foliage environment is investigated. Although the conventional algorithm that based on statistical properties of the received-signal strength (RSS) for target detection at indoor or open-field environment has come a long way in recent years, it is still questionable if this algorithm is fully functional at outdoor with the changing atmosphere and ground conditions, such as a foliage environment. To answer this question, a variety of the measured data have been taken using different targets in a foliage environment. Applying these data along with support vector machine, the impact on detection accuracy due to different classification algorithms is studied. An algorithm that based on the extraction of the high-order cumulant (HOC) of the signals is presented, while the conventional RSS-based one is used as a benchmark. The measurement results show that the classification accuracy of the HOC-based algorithm is better than the RSS-based one by at least 17%. Moreover, to ensure the reliability of the HOC-based approach, the impact on classification accuracy due to different numbers of training samples and different values of signal-to-noise ratio is extensively verified using experimentally recorded samples. To the best of our knowledge, this is the first time that a DFS-based sensing approach is demonstrated to have a potential to distinguish between human and small-animal targets in a foliage environment.read more
Citations
More filters
Journal ArticleDOI
Object detection in real time based on improved single shot multi-box detector algorithm
TL;DR: This paper has increased the classification accuracy of detecting objects by improving the SSD algorithm while keeping the speed constant, and applied along with the multilayer convolutional neural network which uses a larger number of default boxes and results in more accurate detection.
Journal ArticleDOI
Dense People Counting Using IR-UWB Radar With a Hybrid Feature Extraction Method
TL;DR: A hybrid feature extraction method based on the curvelet transform and the distance bin and compared with three other features: cluster features, activity features, and features extracted by a convolutional neural network reveal that the proposed hybrid features are stable, and their performance is substantially more effective than that of the others.
Journal ArticleDOI
Impact of Seasonal Variations on Foliage Penetration Experiment: A WSN-Based Device-Free Sensing Approach
TL;DR: An experiment is conducted in four seasons of WSN-based device-free sensing for FOPEN, and it is shown that the average classification accuracy of the presented approach can be improved by at least 20% under all seasons with an ensured robustness.
Journal ArticleDOI
Multilocation Human Activity Recognition via MIMO-OFDM-Based Wireless Networks: An IoT-Inspired Device-Free Sensing Approach
TL;DR: A multiple-input–multiple-output (MIMO)-orthogonal frequency-division multiplexing (OFDM) technology-based prototype system is utilized to collect data samples at 24 different locations in a cluttered office environment and shows ensured robustness produced by the method.
Journal ArticleDOI
Indoor Motion Detection Using Wi-Fi Channel State Information in Flat Floor Environments Versus in Staircase Environments.
TL;DR: Compared with existing systems, this system is validated to have a better performance in both flat floor and staircase environments, and further utilized to verify the superior CSI motion detection performance in staircase environments versus flat floor environments.
References
More filters
Statistical learning theory
TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
Proceedings ArticleDOI
A review of induction motors signature analysis as a medium for faults detection
TL;DR: In this article, the authors present a tutorial overview of induction motors signature analysis as a medium for fault detection, and introduce the fundamental theory, main results, and practical applications of motor signature analysis for the detection and the localization of abnormal electrical and mechanical conditions that indicate, or may lead to, a failure of inductive motors.
Journal ArticleDOI
See-Through Walls: Motion Tracking Using Variance-Based Radio Tomography Networks
Joey Wilson,Neal Patwari +1 more
TL;DR: A new method for imaging, localizing, and tracking motion behind walls in real time by taking advantage of the motion-induced variance of received signal strength measurements made in a wireless peer-to-peer network is presented.
Journal ArticleDOI
Human Detection and Activity Classification Based on Micro-Doppler Signatures Using Deep Convolutional Neural Networks
Youngwook Kim,Taesup Moon +1 more
TL;DR: This letter applies the DCNN, one of the most successful deep learning algorithms, directly to a raw micro-Doppler spectrogram for both human detection and activity classification problem and shows that it can achieve accuracy results of 97.6% and 90.9% respectively.
Journal ArticleDOI
RF Sensor Networks for Device-Free Localization: Measurements, Models, and Algorithms
Neal Patwari,Joey Wilson +1 more
TL;DR: In this paper, the authors discuss the emerging application of device-free localization (DFL) using wireless sensor networks, which find people and objects in the environment in which the network is deployed, even in buildings and through walls.