ZigBee Wireless Network Research Articles

Design and Implementation of Intelligent Fire Monitoring System Based on Multi-Sensor Data Fusion

Abstract To reduce the losses caused by fire, this paper proposes an intelligent fire monitoring system based on multi-sensor data fusion. Through the design of the temperature, smoke and flame sensors, based on the weighted least squares WLS and improved fuzzy support degree of similar sensors and dissimilar sensors data fusion, respectively, in the ZigBee wireless network based on the design of the fire remote monitoring and control alarm for monitoring, and add the local storage and emergency module. In addition, whether the router nodes work on the ZigBee wireless network during the fire test depends on multi-sensor data fusion. The test shows that the node communication distance is extended and can reach the acceptable requirements in the range of 70m, the highest probability of fire occurrence is 0.92, the lowest probability is 0.14, the overall probability of occurrence is in the range of 0.4 to 0.6, and the error between the predicted value of the probability of occurrence of the fire and the expected value is within ±0.05.

Remote Early Warning System for Mountain Floods with Robust ZigBee Wireless Networks

Remote Early Warning System for Mountain Floods with Robust ZigBee Wireless Networks

Address direction finding of ZigBee devices

Statement of problem. The active use of wireless technologies requires the development of means of monitoring devices and data transmission networks and, in particular, ZigBee wireless personal networks. Therefore, the detection and localization of working ZigBee devices is an urgent task of radio monitoring services. Correlation-interferometric direction finders based on two-channel radio receiving equipment cyclically connected to various pairs of elements of a multi-element antenna system can serve as a tool for bearing radio signals. For the direction finding of packet radio signals, the direction finder accumulates time samples from different antenna pairs over long time intervals; joint processing of these data allows determining the direction of arrival of radio signals. An obstacle to the direction finding of ZigBee devices is the fact that many similar devices can simultaneously operate in the same frequency range, generating a chaotic alternation of packets in the air. As a consequence, the accumulation of information from a specific ZigBee device for different antenna pairs of the direction finder becomes problematically. Purpose of the work is to develop a method for joint identification and bearing of detected devices of ZigBee networks. Results. the presented method of address bearing is implemented on the basis of the mobile direction finder ARTICLE-M, used to search for and locate unauthorized sources of radio emissions, and allows detecting signals of the 802.15.4 standard, identifying personal network devices, as well as forming estimates of directions to these sources of radio emissions. Practical importance. the use of address bearing of ZigBee network devices increases the functionality of existing radio monitoring equipment, and also allows the localization of unauthorized radio sources masquerading as Internet of Things devices.

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.

Power aware air quality sensing system with efficient data storage capability


 
 
 
 Introduction: This paper presents a portable device of Air QualityMonitoring System (AQMS) based on a sensor platform. The purpose of the study is to power awareness, warning indication, and minimal data storage capability.
 Materials and methods: AQMS is developed by embedded design methodology. The software part is based on the C programming language. AQMS device is made up of “transmitter” and “receiver” sections through the Zigbee wireless network. The objective is to collect concentrations of CO, NO2, CO2, humidity, and temperature to check air pollution for health awareness. A power-saving strategy is adopted in the "transmitter" of AQMS through a Demultiplexer circuit. To minimize the space complexity of storage and availability of long-term data, data encoding techniques are implemented.
 Results: By implementing switching activity on the sensors in AQMS, the active mode of sensing operations are controlled and a power saving of 18.41% is achieved. Extending the duration of transmission operation increases data storage in the “receiver” unit. Hence, two encoding techniques are developed where real-time data are encoded in binary form: 2-bit encoding and 3-bit encoding. According to the results, 2-bit encoding saves 50% of storage space and 3-bit encoding saves 25%, compared to not utilizing any encoding strategy, sacrificing data accuracy by less than 5%.
 Conclusion: AQMS design is created with the implementations of low power consumption and low storage. Additionally, an alarming condition is set in AQMS for indicating the level of pollutants in the air to determine the risk level of exposure which is dangerous for human health.
 
 
 

Architecture design of grid-connected exploratory photovoltaic power generation based on Internet of Things and construction of power marketing system

Abstract Solar energy, as a prominent clean energy source, is increasingly favored by nations worldwide. However, managing numerous photovoltaic (PV) power generation units via wired connections presents a considerable challenge. The advent of the Internet of Things (IoT) and cloud service technologies has facilitated the creation of an efficient and convenient PV grid-connected management system. This paper investigates IoT technology and PV grid-connected systems, integrating wireless sensor network technology, cloud computing service platforms and distributed PV grid-connected systems. We propose a Zigbee wireless network featuring ad hoc network functionality and Narrow Band Internet of Things (NB-IoT) smart gateway with multi-protocol and multi-device support. This system enables the collection and uploading of PV grid-connected system data to cloud service platforms, addressing daily operation and maintenance as well as intelligent management of distributed PV power stations. Furthermore, it expedites the aggregation and analysis of PV power generation data, streamlining power marketing across various regions.

Comparative Evaluation of the Performance of ZigBee and LoRa Wireless Networks in Building Environment

ZigBee and LoRa are communication technologies widely used in the application of the Internet of things (IoT), especially in the field of smart building environmental monitoring. The main purpose of this study is to compare and analyze the transmission performance of ZigBee and LoRa wireless communication networks in the building. Through two indicators of packet loss rate (PLR) and round-trip time (RTT), this paper discusses in detail the transmission performance of ZigBee and LoRa technologies in whole buildings under the same working conditions. We set up three experimental scenarios of line-of-sight, horizontal and vertical to evaluate the communication performance of these two networks by changing the baud rate and packet length, and cost and power consumption were considered. Experiments have shown that LoRa networks outperform ZigBee networks in most cases and are the best choice for building communication networks. The experimental results provide basic data support and engineering reference for the application of these two technologies in buildings, especially for the deployment of communication networks throughout buildings. The innovation and contribution of this paper are to discuss the effect of packet length, baud rate, distance, and different locations within a building on the performance of ZigBee and LoRa transmissions, using RTT and PLR as metrics through three experimental scenarios.

Application of Intelligent Sensor in Mining Electrical Equipment Collection

In order to meet the informatization requirements of coal mine safety monitoring, the author proposes a method for the application of smart sensors in the acquisition of mine electrical equipment. The system uses a variety of sensor fusion methods, with the help of Zigbee wireless network nodes, and passes the data collected by the sensor to the MCU core processor; thus, the collected data are processed, and then, the RS-485 communication protocol is used to upload the data to the upper station; finally, the monitoring of coal mine safety is realized through the background monitoring interface. Experimental results show that, among the five randomly selected nodes, most of the errors between the actual measured results and the collected results are concentrated within the 2% error range. Conclusion. The effect of the abovementioned acquisition scheme in coal mine application is verified, so as to realize the scientific monitoring of coal mine safety.

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.

Office intelligent lighting system based on the natural lighting and the ZigBee wireless network.

A comfortable and healthy lighting environment cannot only make people comfortable and improve work efficiency, but also avoid visual fatigue caused by the discomfortable lighting environment. In order to solve these problems, this paper proposes an intelligent lighting system that takes natural lighting and the occupancy situation as input and dimming factor K (0<K<1) as output. The linear function between illuminance of the working surface and natural lighting, the occupancy situation, illuminance components of adjacent luminaires, and dimming factor K is obtained through the control algorithm. The simplex method is one of the most commonly used and effective algorithms for solving linear programming problems, so the optimal dimming factor K of each luminaire is obtained. The intelligent lighting system uses the ZigBee tree network structure to transmit the dimming factor to each lamp, making the office lighting environment reach the target value. Opnet is used as a network simulation software to verify system information, such as delay, throughput, and load. The results show that the network transmission delay is only 0.011 s, and the load and throughput are both above 3.0×104bits/s. As an optical software, DIAlux simulates the lighting environment under the control system in two modes: day and night. The results show that the illuminance of the occupied working surface under the system reaches 500l×, and the illuminance of the unoccupied working surface reaches 300l×. The uniformity of illuminance is greater than 0.7. In the day mode, the uniformity of illuminance is improved compared to without any control system. Finally, the energy-saving efficiency of the control system reached 34% and 25% during the day and night, respectively.

Medical Big Data and Postoperative Nursing of Fracture Patients Based on Cloud Computing.

Based on the standards for wireless sensor system identification, the sensor node identity OID identification and the management object OID identification in the SNMP MIB are merged, and a management object OID identification coding mechanism for the SNMP-based wireless sensor system is proposed to make the node management system only. The identity, attributes, and multiple entities of the target sensor node in the wireless sensor network can be identified and managed by the node management object OID. The source of abnormal medical big data generally uses two models of multidimensional data and sliding window for detection and verification. First, the sliding window can be used to detect abnormalities. The result is that under this condition, the detection rate of medical big data is more than 95%; the effect is very good, but in different dimensions, the detection rate of four-dimensional data is 2.9% higher than that of a single-dimensional one. On the basis of the ZigBee wireless network, the terminal signal transmission of fracture treatment can be realized. On this basis, combined with the actual needs of fracture treatment, it can be built with its wireless module. The wireless network has a certain basic function. The reform of the nursing system was carried out on the basis of the safety and reliability of the nursing system, the efficiency of the nursing system was improved, and timely and safe nursing services were achieved.

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.

Information Monitoring of Animal Husbandry Industry Based on the Internet of Things and Wireless Communication System.

This paper was aimed at discussing the information monitoring of animal husbandry based on the Internet of Things and wireless communication system. The breeding and health of animals in the breeding industry has always been a topic that people talk about. The advent of the wireless communication system has made monitoring and positioning technologies more and more simple. The wireless communication network technology is applied to the environmental monitoring of animal breeding farms, and a real-time reporting system is designed to pay attention to animal health in real time. This article focuses on the connection between the two. First, this article briefly describes the state of the wireless communication network and the aquaculture industry, furthermore explains the research methods, such as the livestock breeding environment monitoring system model, which needs to have the characteristics of humanization, fast and simple, easy to maintain, high reliability, compatibility, scalability, and intelligence, and designs related monitoring systems and hardware systems to integrate carbon dioxide, ammonia, and other gas sensors with temperature and humidity sensors to sense the environment. Next, this article shows the wireless communication network monitoring and positioning algorithm, namely, the TOA-based wireless communication positioning algorithm and the LTE prediction algorithm. The predicted time is used as the link weight, and the weight within the wide link cluster is defined according to the time threshold, making the link maintain stability for a short time to enhance the network topology. Then, this article conducts experiments based on ZigBee wireless communication network sensor combined with improved genetic algorithm in the temperature and humidity test of farms, designs the environmental monitoring system, improves the algorithm, and cooperates with experiments and analysis to verify the feasibility and apply it to the temperature and humidity test of the livestock farm. The results are good, and the temperature and humidity errors are reduced by 88.28% and 84.21%, respectively. It has a certain degree of guidance. Finally, it is discussed and summarized. It can be seen that the system and algorithm designed in this paper have a good prospect in the development of animal husbandry. However, this algorithm takes a long time and has a broader research space.

Artificial Intelligence Monitoring System Using ZigBee Wireless Network Technology in Warehousing and Logistics Innovation and Economic Cost Management

The study expects to reduce the development cost and energy consumption of the storage environment monitoring and improve the efficiency of the storage monitoring environment. Firstly, the storage environment monitoring system is designed in detail using ZigBee. It includes the design of terminal nodes, router nodes, coordinator nodes, and upper computer software. Here is a detailed description of the process of establishing a communication network for three different types of devices in the ZigBee network. The address allocation mechanism of the ZigBee network is introduced. Then, through the application of activity-based costing, the cost reduction is achieved as expected. Finally, the evaluation model of the storage logistics cost level is established, and the various reasons that affect the storage logistics cost are analyzed. The completed warehouse environment monitoring system is a tree topology network composed of a ZigBee coordinator, several ZigBee routing nodes, and terminal devices through the above design. The coordinator in the network is responsible for establishing the network, and it can communicate with the host computer through the serial port. The terminal node collects environmental parameter information and feeds the data back to the ZigBee coordinator through wireless multihop. The ZigBee routing node is mainly used to expand the range of the network to achieve the purpose of wireless monitoring of the entire storage environment. This provides a reference for the combination of wireless communication technology and sensor technology.

Brokerage System for Integration of LrWPAN Technologies.

The prevalent demand for remote data sharing and connectivity has catalysed the development of many wireless network technologies. However, low-power and low-rate wireless network technologies have emerged as the preferred choice (due to cheap procurement and maintenance cost, efficiency, and adaptability). Currently, these groups of wireless networks are adopted in homes, health, and business sectors. The increase in existing WSNs has resulted in the incompatibility of wireless network protocols and poses a problem that results in high acquisition or maintenance costs, increased complexity, reliability inadequacies in some instances, lack of uniformity within similar standards, and high energy consumption. To address this problem, we develop a novel machine-to-machine software-based brokerage application (known as JosNet) for interoperability and integration between Bluetooth LE, Zigbee, and Thread wireless network technologies. JosNet allows one network protocol to exchange data packets or commands with each other. In this paper, we present a novel working network brokerage model for a one-to-one network protocol to communication (e.g., from Zigbee to Bluetooth) or one-to-many network protocol communication (e.g., from Bluetooth to Zigbee, Thread, etc.) to securely send messages in a large-scale routing process for short or long-range connections. We also present a large-scale implementation of JosNet using a routing table for large areas. The results show an industry standard performance for end-to-end latency time and throughput.

Real-time tracking of a moving target in an indoor corridor of the hospital building using RSSI signals received from two reference nodes.

In this paper, implementation and validation of a target tracking system based on the received signal strength indicator (RSSI) for an indoor corridor environment of the hospital is presented. Six tracking methods of a moving target (i.e., equipment, robot, or human) using RSSI signals measured from two stationary reference nodes located at the different sides of the corridor are proposed. A filter with its optimal weight value is also applied to smoothen and increase the accuracy of estimated position results (i.e., the x-position in the corridor). Additionally, a determination approach for finding the optimal parameters assigned for the proposed tracking methods and the filter are also introduced. The proposed methods are implemented in MATLAB/Simulink, and experiments using a 2.4 GHz, IEEE 802.15.4/ZigBee wireless network have been carried out in the indoor corridor of the hospital building. Experimental results obtained from the corridor size of 22 m demonstrate that our proposed methods can automatically and efficiently track the moving target in real time. The average distance errors, in the case of varying and manual tuning the optimal parameters of the proposed methods and the filter, reduce from 5.14 to 1.01 m and 4.55 to 0.86 m (i.e., two test cases; slow moving speed and double moving speed). Here, the errors decrease by 80.35% and 81.10%, respectively. For the case using the optimal parameters determined by the optimization approach, the average errors can reduce to 0.97 m for the first test case and 0.78 m for the second test case, respectively.Graphical abstractAn RSSI-based real-time tracking system for a moving target in an indoor corridor of the hospital building

Researching, building the routing algorithm in Zigbee networks

Zigbee wireless network built on IEEE 802.15.4 standard is becoming one of the most popular wireless networks in modern IoT devices. One of the disadvantages of Zigbee networks is the short transmission distance between devices. This paper focuses on researching and comparing routing algorithms in Zigbee networks, thereby building the optimal routing algorithm in the existing system. The paper’s objective is to form the basis for making Zigbee tree and mesh networks, which improves the transmission distance for Zigbee networks better than the star network.

Research on temperature acquisition system of printing machine oven based on wireless Sensor network

Aiming at the problems such as limited transmission distance of traditional temperature data, complex wiring and aging line, ZigBee wireless network is introduced into the temperature acquisition system of the intaglio printing machine oven, which makes the whole system easy to operate and simple, and greatly improves the transmission distance of temperature signal. The composition of the temperature monitoring system and the hardware circuit of the ZigBee master node are described, including DC 5 V power supply circuit and USB interface power supply circuit, the connection circuit between the RADIO frequency board and the backboard, to realize the construction of the network and the wireless reception of temperature data. To realize the construction of the network and wireless reception of temperature data. It combines ZigBee wireless communication technology to complete real-time transmission of multi-point temperature data, realize real-time LCD display of multi-point temperature data collected by DS18B20, and realize ZigBee networking function based on ZigBee protocol stack.

Reliable Bidirectional Data Transfer Approach for the Internet of Secured Medical Things Using ZigBee Wireless Network

Nowadays, the Internet of Things (IoT) performs robust services for real-time applications in monitoring communication systems and generating meaningful information. The ZigBee devices offer low latency and manageable costs for wireless communication and support the process of physical data collection. Some biosensing systems comprise IoT-based ZigBee devices to monitor patient healthcare attributes and alert healthcare professionals for needed action. However, most of them still face unstable and frequent data interruption issues due to transmission service intrusions. Moreover, the medical data is publicly available using cloud services, and communicated through the smart devices to specialists for evaluation and disease diagnosis. Therefore, the applicable security analysis is another key factor for any medical system. This work proposed an approach for reliable network supervision with the internet of secured medical things using ZigBee networks for a smart healthcare system (RNM-SC). It aims to improve data systems with manageable congestion through load-balanced devices. Moreover, it also increases security performance in the presence of anomalies and offers data routing using the bidirectional heuristics technique. In addition, it deals with more realistic algorithm to associate only authorized devices and avoid the chances of compromising data. In the end, the communication between cloud and network applications is also protected from hostile actions, and only certified end-users can access the data. The proposed approach was tested and analyzed in Network Simulator (NS-3), and, compared to existing solutions, demonstrated significant and reliable performance improvements in terms of network throughput by 12%, energy consumption by 17%, packet drop ratio by 37%, end-to-end delay by 18%, routing complexity by 37%, and tampered packets by 37%.

Intelligent instrument fault diagnosis and prediction system based on digital twin technology

In the context of informatization and intelligent manufacturing systems, digital twin technology provides new technical ideas for intelligent decision-making. Aiming at instruments with high cost and low output, this paper develops low-cost high-efficiency fault diagnosis system to realize rapid feedback and fault of fault diagnosis results. The system includes three layers: data layer, control layer and output layer. In the data layer, this uses MEMS sensors and Zigbee wireless transmission network to construct a data link the physical end and the virtual model. In the control layer, this paper stores the collected twin data through cloud technology, extracts and calls relevant data according to the function module and then maps it to the output layer. In the output layer, this paper constructs a characteristics interpretation system, which divides the test set and training set through the dynamic database, to complete the classifier and results output. The results are fed back to the judgment framework and control layer to evaluate the effects of fault diagnosis and prediction, which provides a new method for model optimization.