Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Bus crowding degree detection system and method

A detection system and detection method technology, applied in the direction of instruments, calculations, character and pattern recognition, etc., can solve the problems of increasing system overhead and difficult server support, and achieve the effects of reducing system complexity, improving efficiency, and simple processing

Inactive Publication Date: 2018-01-23
NORTH CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY
View PDF4 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Although the above idea is effective, it will undoubtedly increase the system overhead. In the face of a huge urban public transport system, it is difficult for the server to support

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Bus crowding degree detection system and method
  • Bus crowding degree detection system and method
  • Bus crowding degree detection system and method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0029] Embodiment 1: as figure 1 As shown, multiple feature points are set at the position of the passenger seat and the aisle. The bus is a large model, assuming that the load is 50 people, the seats are 30, and the aisle can stand 20 people. The roof camera is fixed at 3 positions in front of the bus and in the bus 1. At the rear roof of the car, use three roof cameras to shoot from above. The recognition areas do not overlap and cover all spaces in the car. The seat layout is double rows, with 30 feature points set on each seat, and a row of feature points in the middle of the aisle with a distance of 40 cm, 20 in total (the length of the ordinary bus is 10.2 meters, and the front and rear areas where people cannot stand are removed). The last three The weight of the feature point of the seat next to the window is 2, and the weight of other feature points is 1.

[0030] The data transmission module includes a timer, which is connected with the bus door-closing control sign...

Embodiment 2

[0032] Embodiment 2: as figure 2 As shown, multiple feature points are only set at the aisle position. The bus is a large model. Assume that the load is 50 people, the seats are 30, and the aisle can stand 20 people. The roof camera is fixed at 3 positions in front of the bus, in the bus, and behind the bus. On the roof, three roof cameras are used to shoot from above, and the recognition areas do not overlap and cover all spaces in the car. The seat layout is double-row, and a row of feature points is set in the middle of the aisle with a distance of 30 cm. There are 30 feature points in total (the length of the ordinary bus is 10.2 meters, and the front and rear areas where people cannot stand are removed). The weight of feature points is 1.

[0033] In this embodiment, the seat feature points are not considered, and the total number of equivalent feature points is 30. Generally, if there are seats in the car, it will be done. If the aisle is full of people, there must be n...

Embodiment 3

[0034] Embodiment 3: as image 3 As shown, multiple feature points are only set at the aisle position. The bus is a medium-sized bus. It is assumed that the load is 30 people, 14 seats, and 16 people can stand in the aisle. The roof cameras are fixed at two positions on the front and rear roofs , using two roof cameras to shoot from above, the recognition areas do not overlap and cover all spaces in the car. The seat layout is a single row, two rows of feature points are set in the middle of the aisle with a distance of 30 cm, and the weight of 30 (15*2) feature points is 1.

[0035] In this embodiment, seat feature points are not considered, the seats are arranged in a single row, and the aisle in the middle is relatively spacious. Passengers generally hold one end of the seat while standing, which is relatively stable, so feature points are set in two rows near the seat position, etc. The total number of effect feature points is 30. In general, if there are seats in the car...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a bus crowding degree detection system and method. The system comprises at least one camera fixed at the roof of a bus, multiple features points arranged in the bus, a data transmission module, a server, and a client, wherein the data transmission module is respectively connected with the camera and the server; the client is in network connection with the server; setting locations of multiple feature points are selected from the passenger seats and the bus passage floor. By identifying the feature points in the bus as the fixed location identification of a static image,the processing is simple, the system complexity is greatly reduced, and the efficiency is improved.

Description

technical field [0001] The invention relates to a public transport congestion detection system and method, belonging to the field of public transport services. Background technique [0002] Buses are an indispensable means of transportation for urban development. People travel more and more in modern life. They not only pursue efficiency, but also pay more attention to comfort. The handheld bus system has become very popular, and the location information of the bus can be inquired in real time. But if the waiting bus is a fully loaded bus that cannot get on, it will undoubtedly be a very failed ride experience. Existing research on bus congestion generally focuses on determining the specific number of people inside the bus. For example, patent document: CN201710150279 discloses a method and device for determining bus congestion. In order to improve the accuracy of image recognition, a very complicated The convolutional neural network algorithm and the optical flow algorith...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
Inventor 于复兴索依娜刘亚志吴亚峰苏亚光
Owner NORTH CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com