Central China Normal University

Jianwen Sun

Zongkai Yang

Sannyuya Liu

Qing Li

Zhicheng Dai

Liang Zhao

Hao Li

Xiaoliang Zhu

Dongbo Zhou

Jiangbo Shu

Disclosed are a millimeter-wave (mmWave) radar-based non-contact identity recognition method and system. The method comprises: emitting an mmWave radar signal to a user to be recognized, and receiving an echo signal reflected from the user; performing clutter suppression and echo selection on the echo signal, and extracting a heartbeat signal; segmenting the heartbeat signal beat by beat, and determining its corresponding beat features; and comparing the beat features of the user with the beat feature sets of a standard user group; if the beat features of the user matches one of the beat feature set of in the standard user group, the identity recognition being successful; otherwise, being not successful. According to the method, the use of a heartbeat signal for identity recognition has high reliability, and the use of an mmWave radar technology for non-contact identity recognition has high flexibility and accuracy.

Millimeter-wave (mmWave) radar-based non-contact identity recognition method and system

The present disclosure provides a non-contact fatigue detection system and method based on rPPG. The system and method adopt multi-thread synchronous communication for real-time acquisition and processing of rPPG signal, enabling fatigue status detection. In this setup, the first thread handles real-time rPPG data capture, storage and concatenation, while the second thread conducts real-time analysis and fatigue detection of rPPG data. Through a combination of skin detection and LUV color space conversion, rPPG raw signal extraction is achieved, effectively eliminating interference from internal and external environmental facial noise; Subsequently, an adaptive multi-stage filtering process enhances the signal-to-noise ratio, and a multi-dimensional fusion CNN model ensures accurate detection of respiration and heart rate. The final step involves multi-channel data fusion of respiration and heartbeats, succeeding in not only learning person-independent features for fatigue detection but also detecting early fatigue with very high accuracy.

Non-contact fatigue detection system and method based on RPPG

The disclosure discloses a method for analyzing educational big data on the basis of maps. The method includes acquiring educational resource data and storing the educational resource data into databases according to certain data structures; constructing theme map layers for each analysis theme, classifying and indexing data according to the analysis themes, and superimposing the theme map layers onto base maps to form data maps; analyzing data of the theme map layers according to the analysis themes and acquiring theme analysis results; extracting the data of the multiple theme map layers in target regions, fusing the data and acquiring region analysis results; acquiring learning preference of users; combining the learning preference of the users according to content of user requests and searching the region analysis results in response to the user requests. The disclosure further discloses a system for analyzing the educational big data on the basis of the maps.

Method and system for analyzing educational big data on basis of maps

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Hubei, China

Jianwen Sun