Journal of Electronic Research and Application

Highway Foreign Body Intrusion Detection System Based on Deep Learning

Zihang Wang, Xudong Wang, Shaolong Wang, Zhen Du, Xudong Pan — Mon, 02 Dec 2024 00:00:00 +0800

This paper introduces the expressway intrusion detection system based on deep learning to improve traffic safety. The system adopts deep learning, image recognition, and foreign body detection technology to monitor the road condition in real-time through lidar and binocular camera groups to detect and distance the foreign body on the road. The system visualizes the detection results on the onboard screen to assist the driver to avoid and improve the safety of highway driving. In addition, the system also includes emergency braking, blind spot monitoring, lane departure warning, and other functions. The system has wide application prospects and development potential and is expected to be widely used in the future, providing a strong guarantee for the safe operation of expressways in China.

Study on Activation System of Thermostatic Preheating Engine

Hesong Zhao, Sen Mao, Yipeng Peng, Yi Li, Shufan Wu, Yongming He — Fri, 29 Nov 2024 10:28:51 +0800

Innovatively addressing the challenge of difficult winter starts for vehicles in northern regions, this study has developed a Thermally Controlled Preheating Engine Activation System. This system ingeniously integrates a thermal insulation kettle, an efficient water pump, precision valves, and temperature sensors, all closely linked with the engine’s coolant circulation system. In cold environments, the system automatically initiates a preheating mechanism by circulating and heating the coolant, significantly enhancing engine startup efficiency and reducing wear caused by cold starts. The anticipated outcome of this research is to substantially improve the operational reliability of vehicles in cold climates, extend their lifespan, promote energy conservation and emissions reduction, and drive the automotive industry towards greener, more efficient, and intelligent technologies, thus laying a solid foundation for industry upgrades and transformation.

Distributed Adaptive Predefined-Time Bipartite Containment Algorithm for Nonlinear Multi-Agent Systems with Actuator Faults

Honghao Wu — Fri, 29 Nov 2024 10:48:06 +0800

Distributed adaptive predefined-time bipartite containment for a class of second-order nonlinear multi-agent systems are studied with actuator faults. The communication topology of multi-agent systems is fixed and directed. To ensure that followers can reach the convex hull spanned by leaders under the conditions of actuator faults, the sliding mode method is introduced. Control protocol for multi-agent systems demonstrates its effectiveness. Finally, simulations are provided to verify the effectiveness of the proposed algorithm.

Design of Three-Element Circular Polarization Antenna Array Based on Sequentially Rotated Feed Technique

Chongwen Zhu — Fri, 29 Nov 2024 11:21:13 +0800

Circularly polarized antennas are used in communications between ground stations and satellites to achieve reliable communication links. The right-hand circular polarization and left-hand circular polarization are two types of circular polarization in satellite communications, they are used to support uplink and downlink communications. Circularly polarized antennas are used also in radar system for target detection, tracking and identification. The “three-element circularly polarized microstrip array antenna” is designed to produce left-handed circular polarization, make its size compact, make its bandwidth wider than 3.7–4.2GHz and achieve high gain. Circular polarization element antenna and three-element circularly polarized microstrip array antenna are designed and simulated in software HFSS, and the circular polarization element antenna is manufactured and tested in anechoic chamber. For circular polarization element antenna and three-element circularly polarized microstrip array antenna, the study analyzed these parameters: AR, S(1,1), VSWR, bandwidth, normalized impedance, gain and realized gain, radiation efficiency. After optimized, the study get the required results of them.

Is “Intelligence” More Capable of Promoting the Development of the Tertiary Industry? — Analysis of the Impact of Artificial Intelligence on Different Categories of Industries

Yikun Huang, ZiXuan Shi — Fri, 29 Nov 2024 11:32:13 +0800

In the new scientific and technological revolution round, artificial intelligence (AI) technology has become a key leading force for industrial change. Research shows that AI not only promoted technical transformation and industry upgrades but also played a significant role in the rapid development of emerging industries. Based on the installed number of industrial robots and the industrial data by the National Bureau of Statistics, this study establishes a theoretical framework with the econometric model and compares the impact of AI on different categories of industries through empirical analysis. Our results show that AI not only promotes economic growth but also plays a key role in promoting the tertiary industry. Hence, optimization of industrial structure and economic upgrade can be induced.

Application and Challenge of Edge Computing Based on 5G Communication in Information and Communication Systems

Zhengwei Li, Kan Cao — Fri, 29 Nov 2024 11:47:59 +0800

With the rapid development of information technology, 5G communication technology has gradually entered real life, among which the application of edge computing is particularly significant in the information and communication system field. This paper focuses on using edge computing based on 5G communication in information and communication systems. First, the study analyzes the importance of combining edge computing technology with 5G communication technology, and its advantages, such as high efficiency and low latency in processing large amounts of data. The study then explores multiple application scenarios of edge computing in information and communication systems, such as integrated use in the Internet of Things, intelligent transportation, telemedicine and Industry 4.0. The research method is mainly based on theoretical analysis and experimental verification, combined with the characteristics of the 5G network to optimize the edge computing model and test the performance of edge computing in different scenarios through experimental simulation. The results show that edge computing significantly improves the data processing capacity and response speed of ICS in a 5G environment. However, there are also a series of challenges in practical application, including data security and privacy protection, the complexity of resource management and allocation, and the guarantee of quality of service (QoS). Through the case analysis and problem analysis, the paper puts forward the corresponding solution strategies, such as strengthening the data security protocol, introducing the intelligent resource scheduling system and establishing a multi-dimensional service quality monitoring mechanism. Finally, this study points out that the deep integration of edge computing and 5G communication will continue to promote the innovative development of information and communication systems, which has a far-reaching impact and important practical significance for promoting the transformation and upgrading in the field of information technology.

Design and Application of Modern Interior Design Style System Based on Unity3D

Xiaoyu Chu, Rui Xu, Guangjun Wang — Fri, 29 Nov 2024 15:12:17 +0800

With the constant change of fashion trends, interior design styles are changing day by day. Based on Unity3D technology, this paper develops a system for modern interior-style design and application. Taking the residential interior as a case study, the interior style design is achieved through 3D modeling and texture rendering and then combined with the Unity3D engine to achieve scene roaming and interactive design. The system enables designers to express design concepts more intuitively and efficiently and also improves customer participation and satisfaction. Through the experience of designers and customers, the system is verified to have more practical value than traditional interior design solutions.

The Impact of Financial Technology and Digital Currency on Traditional Financial Industry

Chengkun Liu — Fri, 29 Nov 2024 14:35:22 +0800

To harness the potential of financial technology and digital currency and enhance the competitiveness of the traditional financial industry, this paper briefly elucidates the concepts of financial technology and digital currency, along with their current development status. Furthermore, it analyzes the impact of financial technology and digital currency on the traditional financial industry, aiming to enrich research outcomes in this field and propel the development of traditional financial institutions in China.

Real-Time Wind Speed Analysis at Wind-Damaged Tower of a Transmission Line

Jiehua Ding, Xiaoling Yang, Yongsheng Zhao — Fri, 29 Nov 2024 15:24:33 +0800

Affected by the Super Typhoon “Mangkhut,” a total of five base towers of a transmission line in the mountainous area of China collapsed. In this paper, a mathematical model is established based on the Shuttle Radar Topography Mission (SRTM) data near the accident tower. The measured wind speed in the plain area under the mountain is used as the calculation boundary condition. The wind speed at the top of the mountain is calculated by using a numerical simulation method. The design wind speed and calculated wind speed at the tower site are compared, and the influence of wind speed on tower position in this wind disaster accident is analyzed.

A Probe Into the Mixed Teaching Reform of Python Language Programming

Lei Liu — Fri, 29 Nov 2024 15:35:27 +0800

This paper first analyzes the significance of applying mixed teaching to the “Python Language Programming” course, briefly describes the current state of teaching in “Python Language Programming,” and discusses strategies for reforming mixed teaching approaches. The goal is to provide a reference for the innovative development of teaching the “Python Language Programming” course.

The Auxiliary Role of Large Language Models in Clinical Dialogues

Haipeng Luo, Yuchu Zhang — Mon, 02 Dec 2024 09:15:21 +0800

In recent years, large language models (LLMs) have made significant progress in natural language processing (NLP). These models not only perform well in a variety of language tasks but also show great potential in the medical field. This paper aims to explore the application of LLMs in clinical dialogues, analyzing their role in improving the efficiency of doctor-patient communication, aiding in diagnosis and treatment, and providing emotional support. The paper also discusses the challenges and limitations of the model in terms of privacy protection, ethical issues, and practical applications. Through comprehensive analysis, we conclude that applying LLMs in clinical dialogues is promising. However, it requires careful consideration and caution by practitioners in practice.

The Effect of Water Flow Velocity on Heat Collection Performance of Active Heat Storage and Release System for Solar Greenhouses

Fri, 29 Nov 2024 08:50:59 +0800

In order to explore the influence of water velocity on the heat collection performance of the active heat storage and release system for solar greenhouses in Table l and, six different flow rates were selected for treatment in this experiment. The comprehensive heat transfer coefficient of the active heat storage and release system at the heat collection stage was calculated by measuring the indoor solar radiation intensity, indoor air temperature and measured water tank temperature. The prediction model of water temperature in the heat collection stage was established, and the initial value of water temperature and the comprehensive heat transfer coefficient were input through MATLAB software. The simulated value of water temperature was compared with the measured value and the results showed that the best heat transfer effect could be achieved when the water flow speed was 1.0 m³h^-1. The average relative error between the simulated water tank temperature and the measured value is 2.70–6.91%. The results indicate that the model is established correctly, and the variation trend of water temperature can be predicted according to the model in the heat collection stage.

Exploration of the Maturity Evaluation of College Students’ Innovation and Entrepreneurship Projects Based on Computer Database Technology

Shuai Yuan — Mon, 02 Dec 2024 09:25:59 +0800

The college innovation and entrepreneurship program is a powerful means to enhance students’ innovation and entrepreneurship skills. Evaluating the maturity of innovation and entrepreneurship projects can stimulate students’ enthusiasm and initiative to participate. Utilizing computer database technology for maturity evaluation can make the process more efficient, accurate, and convenient, aligning with the needs of the information age. Exploring strategies for applying computer database technology in the maturity evaluation of innovation and entrepreneurship projects offers valuable insights and directions for developing these projects, while also providing strong support for enhancing students’ innovation and entrepreneurship abilities.

Research on the Construction of Electrical and Electronic Experimental Teaching Platforms in Higher Vocational Colleges

Huihao Huang, Shuyan Wang — Mon, 02 Dec 2024 10:09:09 +0800

With the advancement of vocational education reform, education informationization, and digitalization have become the important direction of the reform of electrical and electronic teaching in high vocational colleges. In this context, intelligent product development of professional electrical and electronic teaching should also do a good job in practice and innovation, especially in actively building a digital experimental teaching platform and promoting the reform of experimental teaching mode, so that students can learn more useful knowledge and skills in the new platform, and cultivate more applied and skilled talents for society. While analyzing the problems existing in the traditional electrical and electronic experimental teaching mode, this paper analyzes the significance and practical path of the construction of electrical and electronic experimental teaching platforms in higher vocational colleges which can be of reference in future research.

Intelligent Solar Chasing Street Light System Design and Fabrication Summaries

Liyan Zhang, Qingying Zhou, Yueming Zhan, Hu Guo — Mon, 02 Dec 2024 10:28:47 +0800

This project adopts an advanced microcontroller as the core control unit, which accurately commands the servo drive, realizes the real-time light chasing and charging function of the solar panel, and effectively manages the power supply system of the street light. At the same time, the system is able to continuously monitor the operation status of the servo within the range of 0 ° to 180 ° to ensure that it is trouble-free and not offline. The hardware system construction consists of five modules: a power module, solar panel module, servo module, street light module, and Organic Light-Emitting Diode (OLED) display module. Each module works together to support the stable operation of the whole system. The system workflow is to accurately determine the direction of the light source by collecting real-time light intensity data through four precision photoresistors. Subsequently, the microcontroller intelligently controls the helm module based on these data to drive the solar panel to rotate within a range of 180 ° to accurately track the sun’s orientation. The street light provides two lighting modes, automatic and manual, to meet the needs of different scenarios. During the daytime, the solar panels work actively to monitor and collect solar energy efficiently in real-time, meanwhile, when night falls, the solar panels switch to standby mode and the streetlights light up automatically, illuminating the road ahead for pedestrians. Compared with the traditional solar street lights on the market, the intelligent solar light chasing road system introduced in this project has significant advantages. Its unique light-chasing algorithm enables the solar panel to continuously track the light source from sunrise to sunset, thus significantly improving the charging efficiency. Compared with traditional street lights, the biggest advantage of this project is the proposed light-chasing algorithm, which can always charge from sunrise until sunset, making the charging efficiency increase by 38% to 47%. The charging efficiency is 20% to 38% higher than that of traditional street lamps. Simultaneously, the biggest advantage of this project is that the power storage capacity is higher than 35% of the traditional solar street light. Bringing users a more durable and stable lighting experience.

Design of a Student Recommendation Platform Based on Learning Behavior and Habit Training

Xiaoyun Zhu — Mon, 02 Dec 2024 11:46:45 +0800

This study innovatively built an intelligent analysis platform for learning behavior, which deeply integrated the cutting-edge technology of big data and Artificial Intelligence (AI), \mined and analyzed students’ learning data, and realized the personalized customization of learning resources and the accurate matching of intelligent learning partners. With the help of advanced algorithms and multi-dimensional data fusion strategies, the platform not only promotes positive interaction and collaboration in the learning environment but also provides teachers with comprehensive and in-depth students’ learning portraits, which provides solid support for the implementation of precision education and the personalized adjustment of teaching strategies. In this study, a recommender system based on user similarity evaluation and a collaborative filtering mechanism is carefully designed, and its technical architecture and implementation process are described in detail.

Theoretical Analysis and Design Implementation of FM Broadcast Receiving System based on SDR

Yalan Yin, Qi Wang, Jianrui Li, Chunliu He — Mon, 02 Dec 2024 13:28:26 +0800

ADALM Pluto is a software-defined radio product. Based on theoretical analysis, this paper designs a Frequency Modulation (FM) broadcast receiving system using ADALM Pluto as a wireless receiver on the Simulink platform. The simulation results show that the theoretical analysis is correct and the parameter settings are reasonable, and the Software-Defined Radio (SDR) has the characteristics of high performance, high ease of use, and low cost.

A Review of Research on Accurate Segmentation of Multimodal Tumor Images

Hao He, Zixuan Yin, Mingzhu Dong — Mon, 02 Dec 2024 00:00:00 +0800

Accurate segmentation of tumor images is a key core technology for the diagnosis and treatment of tumor diseases. In this paper, we analyze a variety of novel and targeted algorithms to solve these problems, summarize, and elaborate the method based on multimodal tumor image processing given the characteristics of serious grayscale inhomogeneity, texture instability, and diversity complexity of tumor images.

Design of Car Based on 5G Network Control

Dan Tong, Boqi Zhang — Mon, 02 Dec 2024 14:36:37 +0800

The role of smart cars is pivotal, and this project designs and implements a four-wheel vehicle control system leveraging 5G communication technology. The system aims to enhance the portability of smart cars, reduce their costs, enable remote control functionality, and improve mobility to meet the needs of modern Internet of Things (IoT) applications. The system integrates an ESP8266 Wi-Fi module with the Blinker IoT platform to enable remote, real-time control of car movement via a smartphone app. Using Access Point (AP) mode for fast network configuration, users can input Wi-Fi credentials and a Blinker key through a web interface for easy setup. Through the custom app interface, users can send commands to control the car’s forward, backward, turning, and stopping actions, as well as adjust speed and operation delay. Additionally, the system includes Electrically Erasable Programmable Read-Only Memory (EEPROM) data storage to ensure the persistent saving of configuration information, and it features a remote wireless camera for external monitoring of the car’s surroundings. The Android-based remote control design allows users to monitor and control the car’s movement anytime and anywhere. Experimental results show that the system is stable, provides smooth control, operates at low cost and low power consumption, and offers good portability. Therefore, this intelligent car control system offers valuable insights for smart car development and application. It can also be integrated with popular smart homes, IoT, and other emerging technologies, offering broad application potential and promising development prospects.

An Ensemble Learning Method for SOC Estimation of Lithium-Ion Batteries Using Machine Learning

Mon, 02 Dec 2024 00:00:00 +0800

Accurately assessing the State of Charge (SOC) is paramount for optimizing battery management systems, a cornerstone for ensuring peak battery performance and safety across diverse applications, encompassing vehicle powertrains and renewable energy storage systems. Confronted with the challenges of traditional SOC estimation methods, which often struggle with accuracy and cost-effectiveness, this research endeavors to elevate the precision of SOC estimation to a new level, thereby refining battery management strategies. Leveraging the power of integrated learning techniques, the study fuses Random Forest Regressor, Gradient Boosting Regressor, and Linear Regression into a comprehensive framework that substantially enhances the accuracy and overall performance of SOC predictions. By harnessing the publicly accessible National Aeronautics and Space Administration (NASA) Battery Cycle dataset, our analysis reveals that these integrated learning approaches significantly outperform traditional methods like Coulomb counting and electrochemical models, achieving remarkable improvements in SOC estimation accuracy, error reduction, and optimization of key metrics like R² and Adjusted R². This pioneering work propels the development of innovative battery management systems grounded in machine learning and deepens our comprehension of how this cutting-edge technology can revolutionize battery technology.

Analysis of Software Development and Operation Measures from the Perspective of Security Technology

Yan Gao — Mon, 02 Dec 2024 15:21:38 +0800

Security technology is crucial in software development and operation in the digital age. Secure software can protect user privacy and data security, prevent hacker attacks and data breaches, ensure legitimate business operations, and protect core assets. However, the development process often faces threats such as injection attacks, Cross-Site Scripting (XSS), and Cross-Site Request Forgery (CSRF), mainly due to code vulnerabilities, configuration errors, and risks from third-party components. To meet these challenges, this paper discusses the application of security technology in development and operation, emphasizing security requirements analysis, design principles, coding practices, and testing during the development phase. Along with focusing on environmental configuration, continuous monitoring, emergency response, disaster recovery, and regular auditing and updating during the operation phase. These measures can significantly enhance the security of software systems and protect user and corporate data.

A Method for Determining the Importance of Critical Emergency Indicators Based on Multi-granularity Uncertain Language

Yongguang Yi, Zengqiang Wang — Fri, 29 Nov 2024 09:02:48 +0800

In view of the complexity of emergencies and the subjectivity of decision-makers, a method of determining key emergency indicators based on multi-granularity uncertainty language is proposed. Firstly, decision members use preferred uncertain language phrases to represent the importance of each key indicator and use transformation functions to carry out the consistent transformation of this multi-granularity uncertain language information. Secondly, the group evaluation vector is obtained by using the extended weighted average operator of uncertainty, and then the weight vector of each key index is obtained by using the decision theory of uncertain language. Finally, an example is given to verify the practicability and effectiveness of the proposed method.

Research on Determining the Weights of Key Influencing Factors Based on Multi-Grained Binary Semantics

Yun Li, Weizhe Shu — Mon, 02 Dec 2024 16:06:44 +0800

To effectively address the complexity of the environment, information uncertainty, and variability among decision-makers in the event of an enterprise emergency, a multi-granularity binary semantic-based emergency decision-making method is proposed. Decision-makers use preferred multi-granularity non-uniform linguistic scales combined with binary semantics to represent the evaluation information of key influencing factors. Secondly, the weights were determined based on the proposed method. Finally, the proposed method’s effectiveness is validated using a case study of a fire incident in a chemical company.

Future Point Estimation Method for Unpowered Gliding Targets

Shoufeng Wang — Fri, 29 Nov 2024 09:20:16 +0800

In modern warfare, unpowered glide munitions, represented by JDAM, are widely used. Accurately predicting the future trajectory of such targets is crucial for intercepting them. This paper proposes a future point prediction method for unpowered gliding targets based on attitude computation. By estimating the current state of the target, we derive the target’s attitude coordinate system. Subsequently, the paper analyzes the forces acting on the target and updates the state transition matrix, ultimately calculating the future position of the target. Experimental results show that, compared to traditional methods, this approach improves the accuracy of future point predictions by 9% to 45%.

Exploration of Industrial Internet Security Technology and Application from the Perspective of Generative Artificial Intelligence

Dinggao Li, Shengda Liao, Zhuo Zheng — Fri, 29 Nov 2024 13:21:37 +0800

In recent years, artificial intelligence technology has developed rapidly around the world is widely used in various fields, and plays an important role. The integration of industrial Internet security with new technologies such as big models and generative artificial intelligence has become a hot research issue. In this regard, this paper briefly analyzes the industrial Internet security technology and application from the perspective of generative artificial intelligence, hoping to provide some valuable reference and reference for readers.

Research on Electronic Forensics Based on Blockchain Technology

Shanshan Hu — Fri, 29 Nov 2024 13:31:56 +0800

The development of high technology, for public life to provide a justification at the same time, also encouraged the spirit of cybercrime, to become more and more rampant. In network crime, electronic data is usually used as the main evidence to determine the facts of the crime and plays an important role in the smooth trial of the case. But because electronic data on dependent, concealment, easy destructive strong science and technology, the forensics work is now in trouble. The mature use of blockchain technology can avoid existing problems to a certain extent, which is helpful to the smooth progress of electronic forensics. This paper on electronic evidence how to more effectively, combined with research blockchain technology, improve the efficiency of electronic evidence collection work.

The Planning and Design of Digital Smart Campus

Lixia Zhao — Fri, 29 Nov 2024 09:34:32 +0800

Under the background of “Digital Liaoning, Smart Province,” as the application of a new generation of network information technology in colleges and universities, the digital smart campus is an important part of digital Liaoning education informationization. Combined with the overall actual situation of the university campus, in line with the principle of “People-oriented, Service-oriented, Information Interoperability and Data Sharing,” through the idea of “management + service,” the traditional application system with management as the core to the service as the core is realized. On the basis of digital information and networks, a new digital smart campus is built based on several information technologies. From the aspects of architecture design, platform and application integration, systematic overall design and scientific and reasonable deployment, to create an efficient one-stop digital intelligent information service platform to fully optimize the use of digital information resources, to provide timely, accurate and efficient campus information services for teachers, students and staff, and to provide cross-departmental business management and convenient information services for the whole school users through the virtual digital means for display and publicity. The overall planning of the campus is carried out step by step, and the campus network, digitalization, virtualization and intelligence are gradually realized. Expand the time and space dimension of the real campus, improve the overall operation efficiency, and then improve the quality of talent training, management level and management efficiency.

Computer Network and Database Security Technology Optimization

Kachen Zhang — Fri, 29 Nov 2024 09:41:31 +0800

With the continuous development of computer network technology, its applications in daily life and work have become increasingly widespread, greatly improving efficiency. However, certain security risks remain. To ensure the security of computer networks and databases, it is essential to enhance the security of both through optimization of technology. This includes improving management practices, optimizing data processing methods, and establishing comprehensive laws and regulations. This paper analyzes the current security risks in computer networks and databases and proposes corresponding solutions, offering reference points for relevant personnel.

Study on Preparation of Cathode Material of Lithium Iron Phosphate Battery by Self-Craning Thermal Method

Maosen Pan, Yali Ge, Bo-hao Lin — Fri, 29 Nov 2024 14:19:43 +0800

The cathode material of carbon-coated lithium iron phosphate (LiFePO₄/C) lithium-ion battery was synthesized by a self-winding thermal method. The material was characterized by X-ray diffraction (XRD) and scanning electron microscope (SEM). The electrochemical properties of LiFePO₄/C materials were measured by the constant current charge-discharge method and cyclic voltammetry. The results showed that the LiFePO₄/C material prepared by the self-propagating heat method has a typical olivine crystal structure, and the product had fine grains and good electrochemical properties. The optimal sintering temperature is 700 ℃, the sintering time is 24 h, the particle size of the lithium iron phosphate material is about 300 nm, and the maximum discharge capacity is 121 mAh/g at 0.1 C rate.

Performance Testing and Analysis of Automotive-Grade CMOS Sensors in Different Environments

Zhiyu Gao — Mon, 02 Dec 2024 16:21:12 +0800

Automotive-grade Complementary Metal-Oxide-Semiconductor (CMOS) sensors play a crucial role in automotive electronic systems, especially in the context of the rapid development of Advanced Driver Assistance Systems (ADAS) and autonomous driving technologies. Their performance is directly related to the safety and reliability of vehicles. However, automobiles will face a variety of complex environmental conditions during the actual operation, such as high temperature, low temperature, vibration, humidity changes, and light changes, which may have an impact on the performance of CMOS sensors. Therefore, it is of great significance to study the performance of automotive-grade CMOS sensors in different environments.

Deep Learning-Based Control System Design for Emergency Vehicles through Intersections

Dingru Li, Yinghui He, Yuanbo Yang, Jiale Xu — Mon, 02 Dec 2024 16:34:35 +0800

This paper addresses the challenge of integrating priority passage for emergency vehicles with optimal intersection control in modern urban traffic. It proposes an innovative strategy based on deep learning to enable emergency vehicles to pass through intersections efficiently and safely. The research aims to develop a deep learning model that utilizes intersection violation monitoring cameras to identify emergency vehicles in real time. This system adjusts traffic signals to ensure the rapid passage of emergency vehicles while simultaneously optimizing the overall efficiency of the traffic system. In this study, OpenCV is used in combination with Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) to jointly complete complex image processing and analysis tasks, to realize the purpose of fast travel of emergency vehicles. At the end of this study, the principle of the You Only Look Once (YOLO) algorithm can be used to design a website and a mobile phone application (app) to enable private vehicles with emergency needs to realize emergency passage through the application, which is also of great significance to improve the overall level of urban traffic management, reduce traffic congestion and promote the development of related technologies.