ZigBee Wireless Sensor Network Research Articles

Framework for Designing of Wireless Sensor Network Using OPNET and Effect of Transport Protocols on Simulation

A Wireless sensor network can be defined as a network of devices that can communicate the information gathered from a monitored field through wireless links. The data is forwarded through multiple nodes, and with a gateway, the data is connected to other networks like wireless Ethernet. It is intended for a general application and should be able to collect data from many nodes, every node connected to several sensors. One possible application for such a network is in the medical area. At first the network will be used to display the evolution of blood pressure; the body temperature, the ambient temperature and pressure and the level of the transfusion liquid can be collected as well. The network coordinator will transmit the data to a local server for further processing. The simulation will be used to evaluate the general parameters of the wireless network and to optimize it. In this paper, we aim to evaluate the performance of a ZigBee wireless sensor network using OPNET and also study the effects of TCP and UDP on the performance of the application based on OPNET simulation software. Keywords-Sensor, wireless sensor network, ZigBee, OPNET, TCP, UDP.

T-Slot Antennas-Embedded ZigBee Wireless Sensor Network System for IoT-Enabled Monitoring and Control Systems

This research proposes a 2.4 GHz T-slot antennas-embedded ZigBee wireless sensor network system, consisting of an IoT gateway board and a sensor node board, for Internet of Things (IoT) applications. Simulations were first carried out to optimize the parameters for the T-shaped slot patch antenna. The prototypes of the IoT gateway and sensor node boards were subsequently fabricated and measurements undertaken. The measured impedance matching (|S11|), bandwidth, and gain of the proposed ZigBee sensor network system were -18 dB, 15.38%, and 1.722 dBi, respectively. Furthermore, the ZigBee IoT-based monitoring and control schemes based on the ZigBee wireless sensor network system were set up and experiments carried out in an enclosed area for the monitoring scheme and in an open area for the control scheme. The experimental results revealed that the proposed IoT-enabled 2.4 GHz ZigBee sensor network system with embedded T-slot patch antennas could efficiently be utilized in IoT-based monitoring and control systems. In essence, the novelty of this research lies in the integration of the IoT and ZigBee sensor network technologies to store data in a cloud server in a real-time fashion, as opposed to in the microcontroller memory which is common in conventional ZigBee systems. In addition, the data stored in the cloud server are retrievable and viewable via the Blynk application on smartphone, rendering the proposed 2.4 GHz T-slot antennas-embedded ZigBee wireless sensor network system operationally suitable for IoT-based monitoring and control systems.

Information Monitoring of Transmission Lines Based on Internet of Things Technology

To solve the problem of difficult real-time monitoring of current transmission lines, this article proposes an information-based monitoring system for transmission lines based on Internet of Things technology. The system utilizes the characteristics of strong scalability, good fault tolerance, low power consumption, and low cost of the Internet of Things. Taking the ultra-low power consumption MSP430 microcontroller and CC2430 radio frequency module as the core, a line monitoring system based on the Internet of Things is designed. The proposed design uses ZigBee wireless sensor network technology which is powered by solar energy. The collection, transmission, processing and judgment of various environmental parameters of the line are realized. The data information is transferred to the monitoring center of the upper computer through GPRS. When there is an abnormality, it can send a mobile phone short message to the person in charge to feedback the abnormal content in time. The distribution network's load symmetry allowed for the development of several locating procedures. For the three-phase symmetric scheme, the fault location approach based on line supply characteristics was employed, and for the three-phase asymmetric scheme, the fault location technique based on line impedance is proposed. One of the most vital uses for the Internet of Things is in the mitigation of power transmission line failures and disasters. Improved power transmission dependability, less financial loss, and fewer power outages are all possible thanks to the Internet of Things' cutting-edge sensing and communication technology. This research introduced the use of IoT in online monitoring system of electricity transmission line with a focus on the characteristics of the construction and development of smart grid. The results indicated that the system's highest temperature difference is 0.31 C, while the maximum humidity difference is 1.38%. The system increases the safety and manageability of electricity transmission while also fostering the widespread adoption and technical integration of the smart grid and the Internet of Things.

Enhancing Security in ZigBee Wireless Sensor Networks: A New Approach and Mutual Authentication Scheme for D2D Communication.

The latest version of ZigBee offers improvements in various aspects, including its low power consumption, flexibility, and cost-effective deployment. However, the challenges persist, as the upgraded protocol continues to suffer from a wide range of security weaknesses. Constrained wireless sensor network devices cannot use standard security protocols such as asymmetric cryptography mechanisms, which are resource-intensive and unsuitable for wireless sensor networks. ZigBee uses the Advanced Encryption Standard (AES), which is the best recommended symmetric key block cipher for securing data of sensitive networks and applications. However, AES is expected to be vulnerable to some attacks in the near future. Moreover, symmetric cryptosystems have key management and authentication issues. To address these concerns in wireless sensor networks, particularly in ZigBee communications, in this paper, we propose a mutual authentication scheme that can dynamically update the secret key value of device-to-trust center (D2TC) and device-to-device (D2D) communications. In addition, the suggested solution improves the cryptographic strength of ZigBee communications by improving the encryption process of a regular AES without the need for asymmetric cryptography. To achieve that, we use a secure one-way hash function operation when D2TC and D2D mutually authenticate each other, along with bitwise exclusive OR operations to enhance cryptography. Once authentication is accomplished, the ZigBee-based participants can mutually agree upon a shared session key and exchange a secure value. This secure value is then integrated with the sensed data from the devices and utilized as input for regular AES encryption. By adopting this technique, the encrypted data gains robust protection against potential cryptanalysis attacks. Finally, a comparative analysis is conducted to illustrate how the proposed scheme effectively maintains efficiency in comparison to eight competitive schemes. This analysis evaluates the scheme's performance across various factors, including security features, communication, and computational cost.

Children Tracking System Based on ZigBee Wireless Network and Neural Network

The safety of children is one of the fundamental concerns of parents. Recently, child kidnapping has increased by a large percentage, some children have been found, and some children have not found yet. This paper proposes an indoor localization system based on ZigBee wireless sensor network (WSN) and Backpropagation Artificial Neural Network (BP-ANN) to locate the child in an indoor environment. Several ANN topologies were investigated to select the best one with minimum tracking or localization error. The Received Signal Strength Indicator (RSSI) was collected from four ZigBee XBee S2C anchor nodes by the mobile node carried by the child in an indoor area of 32m × 32m. The RSSI was collected from 127 test points inside the tested area. The measured RSSI was used to train, test, and validate the performance of BP-ANN to determine the two dimensions (2D) of the target child’s location. Different topologies of ANN have been examined for training, testing, and validation which are 5-5, 10-10, 15-15, and 20-20 neurons in the hidden layer. The findings indicate that the 20-20 ANN topology can achieve higher accuracy than other topologies. Additionally, 20-20 topology localization errors were 1.0, 1.157, and 1.356 m for training, testing, and validating ANN performance.

Integration of Agricultural Wireless Sensor Networks to Web-of-Things Through an Edge-Computing-Enriched WSNs/WoT Gateway

To connect agricultural wireless sensor networks (WSNs) to web services and applications, the agricultural WSNs/WoT gateway is empowered with local data management and network maintenance functions for downstream WSNs in addition to traditional upstream data collection. This work demonstrates a low-cost, highly scalable, rapidly deployable web of things (WoT) gateway with edge computing capabilities. First, an agricultural WSNs/WoT topology is architected, connecting a ZigBee WSNs to the Web for remote monitoring the local environmental and agronomical information, and simultaneously for managing the solar-powered WSNs for a prolonged lifespan according to the instant data scrawled from the cloud. Second, a WSNs/WoT gateway is designed with the hardware platform Raspberry Pi 3, which serves multiple needs for bidirectional information exchange and local WSNs management. Finally, experimentation demonstrates the proposed hardware platform and architecture can perform edge computing, and efficiently realize the up and down transmission and distribution of data stream.

Intelligent integrated framework towards high-accuracy machining

The thermal error is the main factor hindering the realization of the high-accuracy machining. The intelligent integrated framework towards the high-accuracy machining, which is expected to realize improve the machining accuracy, is scarcely reported so far. The self-perception is difficult due to the limited bandwidth of the industrial Internet, and the thermal error model with a strong robustness and high prediction accuracy has not been established. To address the above challenges, in this study, an intelligent integrated framework is designed towards the high-accuracy machining. The intelligent gateway is designed to conduct the data transfer and edge computing. Then the data perception and transfer are conducted with the ZigBee wireless sensor network and cluster-type network structure. Then the data computation is carried out to realize the preliminary training and fine training of the thermal error model. The Bi-directional Long Short-Term Memory Network (BILSTM) is combined with a new Residual Network (RESNET) to propose the BILSTM-RESNET (BLRNET) model, and then the Convolutional Neural Network (CNN)-BLRNET model is proposed, and the spatiotemporal features in the thermal error data are extracted. Finally, the CNN-BLRNET model is embedded into the intelligent integrated framework, and the thermal error control service is provided by the intelligent integrated framework. With the implementation of the intelligent integrated framework, the measured contour error is reduced by 41.2%, and the roundness error of the machined workpiece is reduced by 67.5%.

Design of Intelligent Parking Management System Based on ARM and Wireless Sensor Network

Motor vehicles are changing the way people live, but they are also putting a huge strain on urban traffic. In the majority of major cities, parking has become the number one problem for car owners to get around. The management efficiency of car parks directly affects the traffic of the whole city. In order to improve the management efficiency of the car park, this paper designs an intelligent parking management system based on ARM and ZigBee wireless sensor network. Firstly, according to the internal environment and economic cost of the car park, ultrasonic sensors are used to monitor whether the parking space is empty or not. The information collected by the ultrasonic sensors is transmitted to the ARM host controller through the ZigBee wireless sensor network, and the ARM host controller determines whether there are free parking spaces based on the collected information. Secondly, Faster R-CNN, a deep learning algorithm, is selected as the license plate recognition model, and the Faster R-CNNN is improved by the residual module. Finally, in order to extend the lifetime of the ZigBee wireless network, the ZigBee routing algorithm is investigated, and an improved routing algorithm based on energy averaging is proposed. The effectiveness of the improved routing algorithm is demonstrated by a simulation analysis through NS2. The test results show that the designed intelligent parking management system is able to complete the functions of parking space detection and license plate recognition normally, thus effectively improving the efficiency of the car park and providing great convenience to motorists.

Exploration of Agricultural Economic Management Methods under Internet + Mode

In order to solve the problems that the production management of agricultural greenhouses consumes large human resources, low management efficiency, and the limitations of environmental monitoring, a visualized smart agriculture based on ZigBee and WiFi dual-protocol fusion Wireless Sensor Networks (WSNs) technology is proposed. A management system is proposed. The system takes STM32 as the main control core and builds a visual cloud computing platform based on the ESP8266WiFi module. The environmental parameters of the greenhouse are sent to the ZigBee terminal device through the serial port, and the user can remotely monitor the environmental parameters of the greenhouse in real time through the computer and mobile client, and control the working status of each actuator. The test results show that: (Transmission Control Protocol/Internet Protocol, TCP/IP) communication is not abnormal; under the control of the visual management system, when the system sends out control commands, the response time of each output terminal is basically between 1 and 2 s. The response of the output control unit has high sensitivity. Affected by the network delay, the fourth group of test data is larger, and in the case of network delay, the response sensitivity of each output terminal of the system decreases accordingly. Conclusion. The system has high accuracy of data collection, strong work reliability, can realize precise remote control, and has low cost, high stability, easy operation, and has certain promotion value.

Zigbee Wireless Sensor Networks: Performance Study in an Apartment-Based Indoor Environment

Zigbee is a very popular technology for Internet of things (IoT) networks mainly because of its low power consumption and low-cost features. It shares the unlicensed 2.4 GHz Industrial, Scientific, and Medical (ISM) radio band with other wireless networks such as Wi-Fi. Usually, Zigbee and Wi-Fi networks coexist in indoor environments for their respective applications. Hence, the coexistence introduces interference for both types of networks lowering the performance of the networks, but Zigbee suffers more significant performance losses because of its lower transmission power than Wi-Fi. Since the number of IoT devices is increasing at an unprecedented rate due to numerous emerging applications and thus making the indoor environments very populous, the peaceful coexistence between Zigbee and Wi-Fi networks in proximity becomes an important research study. For this purpose, this paper presents a comprehensive performance study of a Zigbee network in the presence of a Wi-Fi interference network in a real-life apartment-based indoor environment where Wi-Fi access points of dense neighbors exist. The experiments were done in a XBee module-based Zigbee network for measuring the received signal strength indicator (RSSI), packet drop rate (PDR), and loopback throughput with and without nearby Wi-Fi traffic introduced on purpose. Various networking parameters such as the operating channels, the distances between Zigbee devices and Wi-Fi devices, the transmit timeout of Zigbee packets, and the transmission power of the Zigbee transmitter have been used in the experiments to study the network performance. Our results show that in the deployment of IoT networks in a smart home, radio interference from neighboring homes would not be an important factor, but serious considerations may need to be taken inside the same home. The experimental observations of this paper can serve as a good reference study for Zigbee network deployments in real indoor environments, particularly when interference sources are present in proximity.

Internet of things based wireless sensor network: a review

Recently, Internet of Things (IoT) technologies are developing technology with a variety of applications. The Internet of Things (IoTs) is defined as a network of ordinary objects such as Internet TVs, smartphones, actuators and sensors that are smartly connected together to enable new types of communication between people and things as well as between things themselves. Wireless sensor networks (WSNs) play an important part in Internet of Things (IoT) technology. A contribution to wireless sensor networks and IoT applications is wireless sensor nodes’ construction with high-speed CPUs and low-power radio links. The IoT-based wireless Sensor network (WSN) is a game-changing smart monitoring solution. ZigBee standard is an important wireless sensor network (WSN) and Internet of Things (IoT) communication protocol in order to facilitate low-power, low-cost IoT applications and to handle numerous network topologies. This paper presented a review on the energy efficient and routing topologies of ZigBee WSN, applications of IoT enabled Wireless Sensor Network as well IoT WSN security challenges.

Performance research on ZigBee wireless sensor network self-organizing network for 220 kV four-circuit transmission lines on the same tower

With the integration of massive power transmission equipment and the Internet of Things (IoT), it is particularly important to choose a suitable low-power sensor networking structure, when facing a large amount of on-site sensing data. To select a suitable ZigBee network structure with a large number of embedded sensing nodes, for 220 kV four-circuit transmission lines on the same tower, this paper uses OPNET simulation software to conduct three different ZigBee wireless sensor network (WSN) models, respectively with star, tree and mesh topologies. Then, the performance of the Media Access Control (MAC) layer (delay and throughput performance), application layer (end-to-end delay and traffic received performance), and network layer (number of hops and packets dropped performance) is further investigated and compared for these three different ZigBee WSNs under 220 kV transmission scenario. Considering that quantity of sensing nodes would influence the ZigBee WSN performance greatly, thus, the simulation results under two application scenarios, 220 kV four-circuit transmission lines on the same tower and 500 kV double-circuit transmission lines on the same tower, were thoroughly compared and analyzed in this paper.

Intelligent Supply Chain and Logistics Route Optimization Algorithm in Wireless Sensor Network.

This article first proposes the design of the ZigBee wireless sensor network node based on Arduino, from the design and implementation of the node hardware system to the design and implementation of the node software system, and expands on the design details. The node function was applied to the node design environment, and simulation tests were performed, and execution was tested to confirm the feasibility and practicability of the design. Based on this, the article proposes the service construction process of the software and hardware platform of the smart supply chain system, and then clarifies the basic mathematical problem of the distribution plan in line with the service strategy, that is, “the logistics route optimization algorithm with capacity and time constraint optimization,” which aims to study statically design, define, and model, and test two precise solutions representing heuristic genetic algorithms and analyze their results. In addition, additional hardware such as smart supply chain and cabinet boards are tested and designed according to system requirements, and the interaction mechanism is adapted to the user interface and supporting structure design so as to ensure the completion of user-related business processes. Combining the existing theoretical knowledge, the first priority is to meet customer needs, build a smart supply chain model under the premise of on-time delivery, and solve the model in time. Based on this point, this article tries to use hybrid branch algorithm link and tabu search algorithm to increase the consideration of traffic conditions, collect accurate algorithms, and modern heuristic algorithms to solve the actual situation of the case. At the end, the article proposes some related issues for the above problems. Suggesting through the research of wireless sensor network, this paper applies it to the research of intelligent supply chain and logistics route optimization algorithm and promotes the development of more intelligent supply chain in the future.

Design of Nuclear Radiation Monitoring System in Floor Exploration Based on Deep Learning.

Nuclear radiation environmental monitoring has become an important issue in floor surveys. From the perspective of regional environmental nuclear radiation monitoring, it is of great practical significance to establish a scientific and reliable wireless sensor monitoring network for timely and accurately grasping nuclear radiation status and ensuring nuclear safety. In this article, we design a regional environmental nuclear radiation monitoring system based on Zigbee wireless sensor network by using Zigbee wireless technology. First, the network topology suitable for nuclear radiation environment monitoring is designed. Second, the JN5121 module is selected as the core of the Zigbee wireless sensor to build the network hardware platform. Finally, the article focuses on the receiving mechanism, data transmission, coordination between network nodes, network structure, and dynamic network management, and carries on the software development to the Zigbee wireless environment monitoring network. The system can measure the data in real time, display the dose rate of y radiation effectively, and realize the functions of remote control, field control, security alarm, and environmental monitoring. It has good promotion and application value.

Dolphin echolocation optimized sailfish algorithm for energy efficient and secured routing based on trust management in ZigBee wireless sensor network

AbstractSecurity is the vital phenomenon of wireless sensor network (WSN) to preserve the energy. Traditional techniques does not concern the security of routing purpose, it has limitation like low energy resource, unsecure communication channel. In this article, a dolphin echolocation optimized sailfish (DESF) algorithm for energy efficient (EE) and secured routing based on trust management in ZigBee WSN is proposed. The proposed method is combination of enhanced shortcut tree routing based dolphin echolocation sailfish (EOSTR) and DESF, hence it is called EOSTR‐DESF. Here, hybrid DESF with enhanced routing technique is used to select the optimal route. The proposed approach is implemented in NS2 and the performance of the proposed collaborative trust and tree routing based on DESF in ZigBee is compared with the existing approaches like particle swarm optimization‐ant colony optimization, firefly algorithm‐Hirschberg Sinclair, and whale optimization algorithm‐simulated annealing algorithm. Moreover, the performance is analyzed with metrics like delay, packet delivery ratio, energy consumption, throughput, and residual energy. The simulation results demonstrate that the proposed method is more efficient with varying nodes of 33.25%, 20.17%, 8.04% for different data transfer rate of 31.36%, 15.62%, 9.10%.

Design and Research of a Vehicle Approaching Reminder Device Based on ZigBee Wireless Sensor Network

In recent years, wireless sensor networks have developed rapidly, and at the same time, they are also an important support for the Internet of Things and have attracted worldwide attention. A wireless sensor network is composed of many self-organized sensor nodes, which provide a good foundation for it. As a wireless communication technology, ZigBee technology can realize energy-saving and high-efficiency wireless communication. Its sensor nodes are usually small computing devices with radio antennas. They are usually equipped with sensors that can detect one or more environmental parameters. The energy is limited. The function is simple. With the development of the Internet of Things and 5G technology, the scope of wireless sensor networks is becoming wider and wider. This article will apply it to vehicle driving. In today’s society, more and more people use cars as a means of transportation, resulting in a large number of road traffic every year. The accident caused a large number of casualties and material losses. For traffic accidents caused by these factors, the collision between a car hitting a person and a car is the most common, so the research on how to avoid a car collision is urgent. Among the many factors that cause road traffic accidents, the driver is the main reason. Therefore, the combination of the driver’s abnormal driving behavior and the implementation of the vehicle approaching reminder can effectively reduce traffic accidents. At the same time, the vehicle’s collision avoidance warning system is also a vehicle. One of the most important content in driving, we also made research. Through the research of wireless sensor network, this paper applies its relatively mature zigBee technology to the devices and systems of vehicle driving, so that the vehicle approach reminder device and anticollision warning system are developed vigorously.

Grassland Ecological Protection Monitoring and Management Application Based on ZigBee Wireless Sensor Network

Grassland plays a key role in human production and life, especially in the protection and improvement of the natural environment, which cannot be replaced by other ecosystems, such as maintaining water and soil, preventing wind and sand fixation, maintaining carbon balance, affecting climate change, and producing biological products,.. More importantly, contemporary society attaches great importance to the development of agriculture and animal husbandry. Protecting and nurturing grassland plants and animals, maintaining biodiversity, rational grazing, and maintaining the sustainable development of the grassland ecological environment have become the top priorities. In view of the current serious grassland degradation and the decline of livestock carrying capacity, this paper proposes a grassland environmental monitoring system based on the ZigBee wireless sensor network. The system consists of a grassland wireless monitoring network and a remote PC, which realizes real-time and remote monitoring of environmental information, such as air temperature and humidity, light intensity, and rainfall that affect the growth of grassland pastures. Based on the requirements of the agricultural field data monitoring system, the overall framework of the system was designed and built. The system mainly includes two parts: the ZigBee wireless sensor network subsystem and the remote management software subsystem, and data communication is realized between the two through the Ethernet system data exchange protocol. Among them, the ZigBee wireless sensor network subsystem is deployed in the grassland area and mainly realizes the functions of real-time collection, processing, and wireless transmission of grassland data. The remote management software subsystem is mainly used for data reception, storage, and display and can maintain communication with the gateway node to support real-time monitoring of grassland data by remote browsers.

Wireless Sensor Network based Forest Fire Early Detection Systems: Development and Implementation

The article is devoted to the development of a monitoring system based on wireless sensor networks. The purpose of the article is to implement a system for environmental monitoring using wireless sensor networks, as well as to solve the problem of covering the area with this network. Wireless sensor networks and their involvement in environmental monitoring are investigated and interactions between wireless networks and data communication protocols are described. The monitoring system is considered and analyzed. An experiment is conducted in which it has been checked at what maximum distance the temperature parameters can be transmitted, the experiment is conducted with and without interference. Routing algorithms for how they work and how parameters (temperature) are transmitted from sensors to the server are considered. A terrestrial monitoring system layout for environmental monitoring is investigated and developed based on Zigbee wireless sensor network construction technology, given that it can be added to this network new units or their replacement. The Mesh topology is selected and the separate physical devices that are the nodes of this network are identified. Nodes are also designed, using modules from Digi called XBee as a base station for Arduino sensors and as a ZigBee data base. These nodes are investigated for noise immunity and stability using flame, smoke and temperature sensors. The study found that XBee nodes are very unstable working near Wi-Fi routers and interfering in the form of forest. The conclusion about the result of the experiment is formulated, as well as how the system can be further upgraded, which can be added and what parameters can be observed. The proposed method for the location of the ground forest fire monitoring system’s equipment ensures full control and the flame detection preciseness.

A Research of Neural Network Optimization Technology for Apple Freshness Recognition Based on Gas Sensor Array

In the process of growth, apples’ ripening, storage, transportation, and processing, the appearance and internal physiological characteristics will have some changes because of the effect of time and physical attributes. A series of problems, such as the false ripeness and putrefaction of fruit, will bring huge economic losses to fruit vendors and harm to consumers. In this paper, an odor recognition system has been designed for the fast evaluation of the freshness characteristics of apples, which is based on the freshness characteristics of Fuji apple. A series of apple-air mixture with equivalent model was established by studying the change of gas concentration during the growth and storage of apples. The continuous projection algorithm (Successive Projections Algorithm, SPA) is used to optimize the sensor array to solve the problems of collinearity and overlap and also to eliminate the abnormal and redundant sensors. ZigBee wireless sensor network is adopted to send data to host computer, and BP (Error Backpropagation) neural network algorithm optimized by SFLA (shuffled complex evolution, SCE + Particle Swarm Optimization, PSO) algorithm is used to recognize gas data, which greatly improves the training speed and precision of neural network. The experimental results show that the detection accuracy of the Fuji apples freshness is 98.67% and can quickly and comprehensively identify the freshness of apples.

Spread channel of dialectical materialism epistemology based on ZigBee wireless sensor network technology

With the vigorous development of the Internet of Things technology, various Internet of Things devices and technologies are widely used in various fields. As an important member of wireless sensor network technology, ZigBee network protocol is applied to the spread of dialectical materialism epistemology because of its specific advantages. The purpose of this article is to study the dialectical materialism epistemology propagation method based on ZigBee wireless sensor network technology. This article first analyzes the role of ZigBee wireless sensor network technology in the spread of dialectical materialism epistemology. Combining the characteristics of the current stage of the new media era and the actual situation of dialectical materialist epistemology dissemination, this paper investigates the use of ZigBee wireless sensor network technology in universities and the current situation of dialectical materialist epistemology dissemination. Develop an effective method of dissemination of dialectical materialist epistemology, so that dialectical materialist epistemology can be spread more efficiently. According to the survey data, the current dialectical materialist epistemology of H universities mainly relies on classroom teaching, accounting for 5939.54%, followed by the use of WeChat official accounts and Weibo accounts at 10.16% and 9.59%, reflecting the dialectical materialist epistemology of universities Lectures are still the main way of education, and students mainly listen to lectures.