People counting based on CNN using IR-UWB radar

Yang, Xiuzhu; Yin, Wenfeng; Zhang, Lin

doi:10.1109/iccchina.2017.8330453

Cited by 21 publications

(5 citation statements)

References 14 publications

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“…Furthermore, UWB has also been used to count people in different confined environments such as room, building lobby, and people queuing in open spaces. experimental results show that the system produced accurate counting all of three conditions [35].…”

Section: Counting the Number Of People Going Into And Out Of A Building Or A Roommentioning

confidence: 84%

“…Radar can be used to count the number of people in a confined place. Such an example can be found in [35], where they used UWB radar to count the number of people in a lift. Experimental results showed that the radar was able to count the number of people in a lift in a random position with high accuracy (87%).…”

Section: Counting the Number Of People Going Into And Out Of A Building Or A Roommentioning

confidence: 99%

See 1 more Smart Citation

Opportunities and Challenges for Radar Sensing For Pandemics: COVID-19

Shariff¹,

Rahim²,

Hussin³

et al. 2020

IJETER

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Non-contact sensing using radar technologies is a prospective technology in combating pandemic diseases such as the COVID-19. Current literature shows the capability of radar for cardiopulmonary signs detection and for securing social distancing, i.e. to count the number of people in a confined place. Nonetheless, the ability of radar ating frequency, and environments. Besides the different radar approaches and signal processing for reliable sensing, many new challenges for practical applications arise. In this paper, we review the state-of-the-art related applications and challenges of radar for combating the pandemic disease. Additionally, as a departure from the conventional approach, radar technique requires some basic explanation. This paper also provides an overview of radar sensing including its physical sensing basis.

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Section: Counting the Number Of People Going Into And Out Of A Building Or A Roommentioning

confidence: 84%

Section: Counting the Number Of People Going Into And Out Of A Building Or A Roommentioning

confidence: 99%

Opportunities and Challenges for Radar Sensing For Pandemics: COVID-19

Shariff¹,

Rahim²,

Hussin³

et al. 2020

IJETER

View full text Add to dashboard Cite

show abstract

“…Due to the good resolution UWB radar has, individual persons can be separated from the received probing signal. This solution is presented in [ 14 ], where convolutional neural networks were used to improve counting accuracy.…”

Section: Introductionmentioning

confidence: 99%

Ultra-Wideband Radar-Based Indoor Activity Monitoring for Elderly Care

Hämäläinen

Mucchi

Caputo

et al. 2021

Sensors

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In this paper, we propose an unobtrusive method and architecture for monitoring a person’s presence and collecting his/her health-related parameters simultaneously in a home environment. The system is based on using a single ultra-wideband (UWB) impulse-radar as a sensing device. Using UWB radars, we aim to recognize a person and some preselected movements without camera-type monitoring. Via the experimental work, we have also demonstrated that, by using a UWB signal, it is possible to detect small chest movements remotely to recognize coughing, for example. In addition, based on statistical data analysis, a person’s posture in a room can be recognized in a steady situation. In addition, we implemented a machine learning technique (k-nearest neighbour) to automatically classify a static posture using UWB radar data. Skewness, kurtosis and received power are used in posture classification during the postprocessing. The classification accuracy achieved is more than 99%. In this paper, we also present reliability and fault tolerance analyses for three kinds of UWB radar network architectures to point out the weakest item in the installation. This information is highly important in the system’s implementation.

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“…Regarding to people counting using UWB radar, there are some researches have been implemented in people counting applications [9][10][11][12][13]. A feature extraction method was developed based on the Log-normal distribution of the UWB radar signal [9].…”

Section: Introductionmentioning

confidence: 99%

“…A Convolutional Neural Network (CNN) model was proposed to count the number of people queueing in a line and not moving. The CNN model was build based on LeNet structure with 7 hidden layers, and it could count to a maximum of 3 people with an accuracy over 99% [11]. The number of people in this research is too low; thus, it is difficult to apply in a real-life application.…”

Section: Introductionmentioning

confidence: 99%

Convolutional neural network for people counting using UWB impulse radar

Pham¹,

Luong²,

Nguyen³

et al. 2021

J. Inst.

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People counting plays a crucial role in various sensing applications such as in smart cities and shopping malls. In this paper, we propose a data-driven solution that uses a low power ultra-wideband impulse (UWB) radar to count the number of random walking people in an indoor space. A pre-processing signal processing method is applied to clean clutter signals from UWB radar. Instead of the conventional counting methods, which manually extract features and learned from effective data patterns, we investigated deep convolutional neural networks (CNNs) that automatically learn from the data to count the number of people in an indoor space. The CNN model could accurately predict up to 97% accuracy for up to 10 people random walking in an area of 5 × 5 m. The different settings of the CNN models, such as the data input window size, and kernel size in each layer, will be investigated.

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People counting based on CNN using IR-UWB radar

Cited by 21 publications

References 14 publications

Opportunities and Challenges for Radar Sensing For Pandemics: COVID-19

Opportunities and Challenges for Radar Sensing For Pandemics: COVID-19

Ultra-Wideband Radar-Based Indoor Activity Monitoring for Elderly Care

Convolutional neural network for people counting using UWB impulse radar

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