Algorithm Design of Early Warning Seatbelt Intelligent Adjustment System Based on Neural Network and Big Data Analysis

With the purpose to guarantee the safety of drivers and passengers as well as lower the death rate collision, the early warning seatbelt intelligent adjustment system is designed by using big data analysis technology based on the aspects of hardware equipment, database, and software program. In the...

Full description

Saved in:
Bibliographic Details
Published inMathematical problems in engineering Vol. 2020; no. 2020; pp. 1 - 7
Main Author Zhou, Chunxu
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 2020
Hindawi
Hindawi Limited
Subjects
Algorithms
Big Data
Circuits
Data analysis
Debugging
Drivers
Driving conditions
Early warning systems
Hardware
Microcontrollers
Neural networks
Power supply
Seat belts
Sensors
Software
Tables (data)
Technology assessment
Tightening
Online AccessGet full text

Cover

More Information
Summary:With the purpose to guarantee the safety of drivers and passengers as well as lower the death rate collision, the early warning seatbelt intelligent adjustment system is designed by using big data analysis technology based on the aspects of hardware equipment, database, and software program. In the hardware system, microcontroller AT89C52 is applied as the control core. By means of the sensor detection and drive control, the early warning safety belt tightening, locking and lifting, and other functions are realized. Meanwhile, various components of the hardware system are coordinated through debugging several modules in the hardware system and using the modified circuit to connect them together. We determine the relational rules of the database and create the corresponding database table, to provide sufficient data support for the realization of software functions. Using the big data analysis method to process the real-time detection data received by the sensor, the software functions such as timely tightening of safety belt, humidity relaxation, and over-rolling prevention can be realized according to different driving conditions of drivers and vehicles, respectively. The conclusion is drawn through the system test experiment: compared with the traditional regulation system, the design system has a higher degree of regulation, and the application of the design results to the actual vehicle can reduce the crash fatality rate of about 22.4%.
ISSN:1024-123X
1563-5147
DOI:10.1155/2020/7268963