公开(公告)号：US11503057B2

公开(公告)日：2022-11-15

申请号：US17506607

申请日：2021-10-20

Applicant: Nanjing University of Science and Technology

Inventor： Yong Qi ,  Jianye Yu

IPC: H04L9/40 ,  G06N3/08 ,  H04L67/12

Abstract: An intrusion detection method and system for Internet of Vehicles based on Spark and combined deep learning are provided. The method includes the following steps: S1: setting up Spark distributed cluster; S2: initializing the Spark distributed cluster, constructing a convolutional neural network (CNN) and long short-term memory (LSTM) combined deep learning algorithm model, initializing parameters, and uploading collected data to a Hadoop distributed file system (HDFS); S3: reading the data from the HDFS for processing, and inputting the data to the CNN-LSTM combined deep learning algorithm model, for recognizing the data; and S4: dividing the data into multiple resilient distributed datasets (RDDs) for batch training with a preset number of iterations.

公开(公告)号：US11783601B2

公开(公告)日：2023-10-10

申请号：US17043681

申请日：2020-08-18

Applicant: Nanjing University of Science and Technology

Inventor： Yong Qi ,  Yuan Zhuang

IPC: G06F9/00 ,  G08B21/18 ,  G06V20/59 ,  G06V20/40 ,  G06V10/82 ,  G06V10/776 ,  G06V10/77

CPC classification number: G06V20/597 ,  G06V10/7715 ,  G06V10/776 ,  G06V10/82 ,  G06V20/46 ,  G06V20/49 ,  G08B21/18

Abstract: A driver fatigue detection method based on combining a pseudo-three-dimensional (P3D) convolutional neural network (CNN) and an attention mechanism includes: 1) extracting a frame sequence from a video of a driver and processing the frame sequence; 2) performing spatiotemporal feature learning through a P3D convolution module; 3) constructing a P3D-Attention module, and applying attention on channels and a feature map through the attention mechanism; and 4) replacing a 3D global average pooling layer with a 2D global average pooling layer to obtain more expressive features, and performing a classification through a Softmax classification layer. By analyzing the yawning behavior, blinking and head characteristic movements, the yawning behavior is well distinguished from the talking behavior, and it is possible to effectively distinguish between the three states of alert state, low vigilant state and drowsy state, thus improving the predictive performance of fatigue driving behaviors.

公开(公告)号：US11373523B2

公开(公告)日：2022-06-28

申请号：US16969896

申请日：2018-10-16

Applicant: NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Yong Qi ,  Xian Lv ,  PengZhen Du ,  WeiBin Zhang

IPC: G08G1/04 ,  G08G1/042 ,  G08G1/052 ,  G08G1/065

Abstract: A method for vehicle detection based on single-axis geomagnetic sensor is disclosed. The method includes the following: arranging two geomagnetic sensors in tandem at a fixed distance in the same lane, and acquiring, by the two geomagnetic sensors, data when a vehicle passes by; performing data cleansing and denoising on the data acquired by the geomagnetic sensors; detecting, by the geomagnetic sensors, the vehicle by using an state machine algorithm based on a fixed threshold, and extracting moments when the vehicle enters and leaves detection ranges of the sensors; and collecting statistics on traffic flow in a predetermined period of time, and calculating the velocity and length of the vehicle. The presently disclosed method and apparatus can be independently used to obtain vehicle parameters at important traffic sections or intersections, or can be used in combination with other traffic detection devices to obtain more comprehensive traffic information. The presently disclosed method and apparatus has low power consumption, high detection sensitivity, is easy to install and resists the impact of a harsh environment.

公开(公告)号：US20210118291A1

公开(公告)日：2021-04-22

申请号：US16969896

申请日：2018-10-16

Applicant: NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY

Inventor： Yong Qi ,  Xian Lv ,  PengZhen Du ,  WeiBin Zhang

IPC: G08G1/042 ,  G08G1/065 ,  G08G1/052

Abstract: A method for vehicle detection based on single-axis geomagnetic sensor is disclosed. The method includes the following: arranging two geomagnetic sensors in tandem at a fixed distance in the same lane, and acquiring, by the two geomagnetic sensors, data when a vehicle passes by; performing data cleansing and denoising on the data acquired by the geomagnetic sensors; detecting, by the geomagnetic sensors, the vehicle by using an state machine algorithm based on a fixed threshold, and extracting moments when the vehicle enters and leaves detection ranges of the sensors; and collecting statistics on traffic flow in a predetermined period of time, and calculating the velocity and length of the vehicle. The presently disclosed method and apparatus can be independently used to obtain vehicle parameters at important traffic sections or intersections, or can be used in combination with other traffic detection devices to obtain more comprehensive traffic information. The presently disclosed method and apparatus has low power consumption, high detection sensitivity, is easy to install and resists the impact of a harsh environment.