Wireless Network Monitoring Research Articles

Space–Ground Remote Sensor Network for Monitoring Suspended Sediments in the Yellow River Basin

The Yellow River, China’s second-largest river, is renowned for its high sediment content. In response to the potential impacts of climate change on Yellow River water resources and water environmental management, an advanced monitoring and forecasting system for water and sediment throughout the entire Yellow River basin—from its source to the sea—is urgently needed. In this paper, based on the current status of water and sediment monitoring technologies, we proposed an integrated remote sensing monitoring network that combines satellite remote sensing, drone remote sensing, and ground-based wireless automatic monitoring networks, aiming to achieve the digital monitoring of water and sediment across the entire Yellow River basin, from its upper reaches to its estuary in the Bohai Sea. By utilizing ground-based in situ hyperspectral stations for sediment source areas in the upper reaches, such as the Qingshui River basin in Ningxia, and satellite remote sensing for midstream processes in the Xiaolangdi reservoir before the flood season in 2023, as well as downstream monitoring at the Yellow River estuary, this paper demonstrates the novelty and efficiency of the space–air–ground integrated remote sensing monitoring technology.

Zigbee-Based Wireless Sensor Network of MEMS Accelerometers for Pavement Monitoring

In this paper, we propose a wireless sensor network for pavement health monitoring exploiting the Zigbee technology. Accelerometers are adopted to measure local accelerations linked to pavement vibrations, which are then converted into displacements by a signal processing algorithm. Each device consists of an on-board unit buried in the roadway and a roadside unit. The on-board unit comprises a microcontroller, an accelerometer and a Zigbee module that transfers acceleration data wirelessly to the roadside unit. The roadside unit consists of a Raspberry Pi, a Zigbee module and a USB Zigbee adapter. Laboratory tests were conducted using a vibration table and with three different accelerometers, to assess the system capability. A typical displacement signal from a five-axle truck was applied to the vibration table with two different displacement peaks, allowing for two different vehicle speeds. The prototyped system was then encapsulated in PVC packaging, deployed and tested in a real-life road situation with a fatigue carousel featuring rotating truck axles. The laboratory and on-road measurements show that displacements can be estimated with an accuracy equivalent to that of a reference sensor.

Designing a low-cost wireless sensor network for particulate matter monitoring: Implementation, calibration, and field-test

Poor air quality can provoke severe impacts on health, necessitating environmental monitoring of atmospheric particulate matter (PM) to assess potential threats to human well-being. However, traditional continuous air quality monitoring systems are often costly and time-consuming in data treatment. Lately, there is a growing trend towards the use of low-cost wireless PM sensors, providing more detailed information than standard systems. This paper presents a system designed to measure air quality, specifically, a wireless sensor network composed of a distributed sensor network linked to a cloud system. The proposed system can efficiently measure air quality as it is cost-effective, small-sized, and consumes little power. Sensor nodes based on low-power long range (LoRa) motes transmit field measurement data to the cloud via a gateway, and a cloud computing system is implemented to store, monitor, process, and visualise the data. Advanced techniques were included in our cloud for data processing and analysis to optimise the detection of PM. Laboratory and field tests in the historic Riotinto mine validate the system's viability, offering real-time air quality information for nearby populations. Once calibrated, sensors demonstrate high accuracy, presenting mean error of −0.3% and low deviation (R2 = 0.96) when compared to regulatory systems for both low (<10 μgPM10/m3) and hazardous concentrations (300 μgPM10/m3), which makes them perfect as early warning systems for atmospheric pollution in mining.

Landslide monitoring and prediction system using geosensors and wireless sensor network

Landslides in hilly regions are a frequently occurring natural phenomenon which takes a heavy toll of human lives and causes damage to different properties. Hence, prediction of landslide is essential for averting its deleterious effects by providing early warning to neighboring residents about the impending hazard of landslide. A landslide monitoring system has been designed using geosensors and high-range wireless network for on-line monitoring and prediction of landslides with the application of multivariate statistical analysis of prevailing site parameters. The system consists of various geosensors, wireless sensor network, server, and landslide monitoring and forecasting software. Crackmeter, in-place inclinometer, raingauge, tiltmeter, piezometer and other sensors are set up in the selected hill slope prone to landslide for continuous monitoring of influencing parameters. The system measures real-time landslide parameters using the said geosensors connected with wireless nodes and establishing a dynamic wireless network to overcome redundancy issue using wireless nodes of around 1200 m communication range using a high performance low power microcontroller, integrated solar panel and additional external omni-directional antenna for monitoring landslide in a large and hazardous hilly region from a distant safer location. The application software consists of different modules, namely data monitoring, analysis, storing, viewing, prediction, and generation of audio-visual, SMS and email alerts for 3 levels of landslides situations. The paper enumerates the system architecture and the application software details.Graphical

A digital twin-based energy-efficient wireless multimedia sensor network for waterbirds monitoring

Wetlands play a critical role in maintaining the global climate, regulating the hydrological cycle, and protecting human health. However, they are rapidly disappearing due to human activities. Waterbirds are valuable bio-indicators of wetland health, but it is challenging to monitor them effectively. Wireless Multimedia Sensor Networks (WMSNs) offer a promising technology for monitoring wetlands. Nonetheless, these networks are constrained in terms of energy, and also encounter challenges associated with large-scale deployments under natural environmental conditions. These conditions introduce harsh circumstances that may not have been anticipated during the pre-deployment testing phase. This paper proposes a Digital Twin (DT) based energy-efficient WMSN monitoring system specifically tailored for waterbirds in wetlands. The system utilizes a unique approach that combines local audio identification and image compression with DT technology to optimize network performance and minimize energy consumption. To reduce unnecessary image transmissions, the system employs a real-time, low-complexity local audio identification phase before triggering image capture. A denoising step is employed to achieve highly accurate bird recognition despite surrounding noises. Each image undergoes a low-complexity compression scheme prior to transmission, further enhancing energy efficiency. To enhance the system’s overall efficiency and effectiveness, DT technology is integrated to create real-time replicas of the WMSN and the monitoring application. A synergistic interaction between the two DTs enables cooperative data-making decision that ensures both QoS (Quality of Service) and QoE (Quality of Experience) requirements are met. Transmission rate control is done using a fuzzy logic decision-making technique. Real-time feedback provides rapid and accurate analysis of the current state of the WMSN, allowing for dynamic adjustments. The ”what-if scenarios” feature of the implemented DTs has been effectively leveraged to find the most suitable settings for the controller. The effectiveness and performance enhancements achieved by integrating DT into our WMSN-based surveillance system are validated through comprehensive experiments in scenarios that correspond to a real-world wetland. Comparative analyses demonstrate the undeniable benefits of the DT-integrated system compared to a conventional WMSN-based surveillance setup. In particular, the results demonstrate the system’s superior performance in terms of energy efficiency, real-time monitoring capabilities, and ability to handle multiple video sources.

Wireless sensor network for structural health monitoring using RFID based data mules

The wireless system did the huge cost-cutting in monitoring the structure so, now it can be used permanently as an integral part of the system as a smart infrastructure that will give them real-time information the structure. The wireless devices transmit the collected data about cracks, displacement, and excess vibration in slab-tracks. The train which will collect the data and train will be used as a data mule in this paper which will upload the information to a remote-control centre. The data which will be collected stored in the database and to know the status of the track a query will be fired from an application. In this paper, many design for communication systems are proposed which are efficient, with fine accuracy, and most importantly it is a low-cost system.

Smart-Systems for Precision Agriculture, Environmental Protection and Healthcare

Appearance of innovative tools of informatics in the world is determined by development of information-communication technology, microelectronics, sensor and biosensor technologies. Spreading of these technologies on precision agriculture, environmental protection and health care gives opportunity to create smart fields, gardens, greenhouses, forests and parks, and also smart health monitors, which estimate the health state of person as in rehabilitation, so in emergency situations. Results of research of authors in the development of new information technologies and creation of main components of the smart systems for different purposes on this base are shows in this paper. Main requirements for knowledge bank for precision agriculture and ecological monitoring are defined. Main principles of creating knowledge bank on base of requirements are proposed. The typical smart system models and their development stages are considered. Structure of wireless multilevel networks for the estimation of state of biological objects of different origin and their nodes are described. Developed sensor networks and smart systems for agriculture are considered. Structure of proposed smart system for agriculture and ecological monitoring is given. Approaches for chlorophyll fluorescence induction curves analysis are studied. Results of network testing for the estimation of the autonomous work time of network nodes and possible errors are given. Wireless sensor network and smart system for remote medical monitoring are described. Diagnostic smart systems for estimation of quality of life are considered. Medical communicator, computer device on base of tablet computer, was used for their development. The short form of Survey Instrument (SF-36) for life quality estimation and abnormal uterine bleeding questionnaire, which was developed in State Scientific Institution "Center for Innovative Medical Technologies of the National Academy of Sciences of Ukraine", were embedded in communicator. STEPS questionnaire which was designed for epidemiological monitoring of the prevalence of noncommunicable diseases and their risk factors in the target subpopulations could be added to communicator. Development of smart systems for estimation of quality of life and prevalence of noncommunicable diseases was made in cooperation with R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology NAS of Ukraine (department of research management and innovation), Chebotarev Institute of Gerontology of the National Academy of Medical Sciences of Ukraine, Center for Innovative Medical Technologies of the National Academy of Sciences of the Ukraine. Keywords: wireless sensor network, precision agriculture, chlorophyll fluorescence induction, express-diagnostics of plant state, quality of life, SF-36.

Ensuring Data Freshness in Wireless Monitoring Networks: Age-of-Information-Sensitive Coverage and Energy Efficiency Perspectives

With the development of IoT, the sensor usage has been elevated to a new level, and it becomes more crucial to maintain reliable sensor networks. In this paper, we provide how to efficiently and reliably manage the sensor monitoring system for ensuring data freshness. A sensor transmits its sensing information regularly to the data center (DC), and the sensed information generally has the correlation over the space and the time. Hence, the accuracy of the estimated information from the sensed information decreases as the target location for information estimation is further away from the sensor or the AoI, the elapsed time from the information generation, increases. Therefore, by considering the effect of the AoI and the distance from the sensor on the estimation error, we newly define an error-tolerable sensing (ETS) coverage as the area that the estimated information at the DC is with smaller error than the target value. To analyze the impact of the AoI on the ETS coverage, we derive the η-coverage probability, which is the probability that the ETS coverage is greater than η ratio of the maximum sensor coverage, and the average ETS coverage. We also provide the optimal transmission power of the sensor, which minimizes the average energy consumption while guaranteeing certain level of the η-coverage probability. Numerical results validate the theoretical analysis and show the tendency of the optimal transmission power according to the maximum number of retransmissions. This paper can pave the way to efficient design of the AoI-sensitive sensor networks.

Channel Allocation Algorithm Based on Swarm Intelligence for a Wireless Monitoring Network

In wireless networks, multiple monitoring nodes are used to collect users’ transmission data in real time, which can be used for fault diagnosis and analytical feedback of the wireless network. Due to the limited number of monitoring nodes, key issues include how to optimize and schedule the channel resources of each node to cover more users, obtain more network data, and maximize the quality of network monitoring. In this paper, a channel allocation algorithm based on swarm intelligence—“discrete bacterial foraging optimization”—is proposed based on the classic bacterial foraging optimization algorithm. The position of each dimension in the iterative process is discretized to binary 0 or 1 to encode and express the channel allocation problem of wireless monitoring networks, and the channel allocation scheme is optimized by location updates guided by bacterial foraging. Many simulation and practical experiments have proved the effectiveness of the algorithm, and it also has low complexity and provable convergence. Compared with similar algorithms, this algorithm improves monitoring quality by 1.428% while boosting speed by up to 32.602%. The algorithm has lower complexity, higher performance, and can converge to the optimal solution at a faster rate.

Evaluation of a Wireless Home Sleep Monitoring System Compared to Polysomnography

Sleep is essential for human health. Bad sleep and sleep disorders have been increasingly prevalent and are gradually becoming a social problem that cannot be ignored. The current gold standard in sleep monitoring is polysomnography (PSG) allowing nearly complete approach. Unfortunately, this wealth of information is obtained at the cost of invasive system, only usable in hospital environment under the control of sleep experts. Therefore, the development of a wireless body network for long-term home sleep monitoring is a good way to achieve this in a less-intrusive, portable and autonomous way. In this paper, an overall architecture from the sensors to the user's display is presented with a focus on the main functions and hardware. The hardware architecture is composed of simple miniaturized wearable devices. Then, we introduce the chosen indicators for sleep monitoring and the algorithms developed for sleep stages classification. Finally we show the evaluation of our approach compared to the PSG. We illustrate the sleep stage classification during one night in the sleep unit of Toulouse University Hospital and highlight correlation between body temperature on extremities and Periodic Limb Movement during Sleep. Based on the confusion matrix analysis, the results show that the T1 method appears to be effective for the detection of awake and deep sleep in particular. For PLMS detection, we define the detection rules based on the foot movement data. The results show that the total number of PLMS and the number of PLMS distributed in each sleep stage detected by our foot module are both very close to the PSG. Furthermore, we have found correlations between body temperature and hypnogram and between body temperature on extremities and PLMS. A wearable sensor system could be an alternative to PSG for long-term monitoring. Validation of the two proposed threshold-based algorithmic methods for sleep stage classification compared to the PSG gold standard shows good agreement, while the k-means based approach shows poor agreement with PSG. Furthermore, this method could be a good candidate for predicting periodic leg movements in sleep.

UAV Dispatch Planning for a Wireless Rechargeable Sensor Network for Bridge Monitoring

Due to the breakthrough of wireless power transfer technology, wireless rechargeable sensor networks (WRSNs) have the potential to provide sustainable work. Most existing researches on WRSNs usually focus on the cases that mobile charging vehicle moves freely through the sensors. However, for some applications, such as bridge monitoring, WRSNs are implemented in a three-dimensional space with obstacles, so the charging path may be blocked by the obstacles. To cope with this problem, charging scheduling to replenish a wireless rechargeable sensor network for bridge monitoring by an unmanned aerial vehicle (UAV) is studied. The problem is formulated as an optimization problem through optimizing UAV navigation path and sensor energy allocation collaboratively. This optimization problem is hard to be solved as both path navigation and energy allocation are required to be optimized simultaneously. To circumvent this challenge, an improved ant colony system algorithm (IM-ACS) is proposed to plan the trajectory of the UAV between sensors. By integrating enhancement factors and dynamic pheromone intensity coefficients, the convergence of the algorithm is accelerated. Then, a two-stage algorithm is proposed to schedule charging sequence and assign energy with limited energy carried by the UAV in each charging period. Experiments and simulations show that the proposed approach achieves shorter feasible trajectory paths and longer network lifetime than those obtained by the compared methods.

Making technological innovations accessible to agricultural water management: Design of a low-cost wireless sensor network for drip irrigation monitoring in Tunisia

Unsustainable use of water resources and climate change will exacerbate the existing tensions surrounding resources, especially in the Mediterranean context. Despite investments in costly modern equipment, the performance of irrigated agriculture remains below expectations, notably because of the lack of available water data and the limited use of decision support tools. Although a variety of soil moisture sensors are available on the market, they are not widely used by the agricultural community because of their high cost and complexity. Access to information at an unprecedented level, via easily accessible low-cost and low-tech sensors, may be a major lever for improved identification of achievable gains in performance, and to guide actors toward efficient water management. To explore this hypothesis, an open source wireless soil moisture sensor, low-energy and economically and technically accessible, was developed. The tool was designed according to water users’ requirements and applied to a Tunisian irrigation scheme subject to major water use efficiency issues. The functioning of the wireless sensor network was tested on pilot plots over a growing season and compared with commercial sensors. A single parameter calibration can be performed in either the laboratory or the field. This low-cost sensor can be used for real-time irrigation monitoring and as a decision-making tool for water management.

ECCPWS: An ECC-based protocol for WBAN systems

The development of Wireless Body Area Network (WBAN) and Wearable Health Monitoring Systems (WHMS) play a key role in healthcare monitoring. WBAN includes medical sensors that monitor vital signs of patients, collect data and usually transmit them to medical servers via wireless channels. Therefore, the patient’s sensitive information sent over the channel can be vulnerable to various attacks. Hence, designing lightweight authentication security protocols for these systems with the lowest computational and communication costs has become a major challenge. Recently, Sowjanya et al. (2020) presented a lightweight authentication scheme for WHMS based on Elliptic Curve Cryptography (ECC), which provides optimal security features and low storage, communication and computational costs. In this paper, the security of their scheme is evaluated and passive insider secret disclosure and replay attacks against their scheme are presented. It is obvious that other attacks such as desynchronization attack and impersonation attack can be applied to this protocol by obtaining the secret value of network manager. The complexity of our proposed attacks is just one run of the protocol and their success probability equals to one. Finally, by remedying the Sowjanya et al. (2020) ’s protocol, a lightweight ECC-based authentication scheme called ECCPWS is proposed. Moreover, the proposed protocol’s security proof is performed via informal methods and also formally through Real-Or-Random (ROR) model, BAN logic, Scyther and AVISPA tools. The security verification results of ECCPWS show that the ECCPWS has complete security against various security vulnerabilities and attacks.

Tele-Rapid Response Team (Tele-RRT): The effect of implementing patient safety network system on outcomes of medical patients-A before and after cohort study.

Rapid Response Teams were developed to provide interventions for deteriorating patients. Their activation depends on timely detection of deterioration. Automated calculation of warning scores may lead to early recognition, and improvement of RRT effectiveness. This was a "Before" and "After" study, in the "Before" period ward nurses activated RRT after manually recording vital signs and calculating warning scores. In the "After" period, vital signs and warning calculations were automatically relayed to RRT through a wireless monitoring network. When compared to the before group, the after group had significantly lower incidence and rate of cardiopulmonary resuscitation (CPR) (2.3 / 1000 inpatient days versus 3.8 / 1000 inpatient days respectively, p = 0.01), significantly shorter length of hospital stay and lower hospital mortality, but significantly higher number of RRT activations. In multivariable logistic regression model, being in the "After" group decreases odds of CPR by 33% (OR = 0.67 [95% CI: 0.46-0.99]; p = 0.04). There was no difference between groups in ICU admission. Automated activation of the RRT significantly reduced CPR events and rates, improved CPR success rate, reduced hospital length of stay and mortality, but increased the number of RRT activations. There were no differences in unplanned ICU admission or readmission.

Target location service system in microgrid operation based on internet of things

Abstract With the gradual reduction of conventional energy sources, the problem of environmental pollution is becoming more and more serious. Environmentally friendly, efficient and flexible power generation models are widely favored, and microgrids emerge as the times require. Microgrid is a medium and low voltage network including power distribution, storage devices, loads and other equipment. It can operate in grid-connected mode or as a stand-alone system in an island environment, continuing to supply power to users even when the large grid is disrupted. Compared with traditional power grids, microgrids have small capacity and changeable operation modes, making it difficult to locate distribution areas and short-circuit currents. At the same time, it is difficult to trace the faults during operation. So far, microgrids have had a lot of technical issues in operation that need to be resolved quickly. In recent years, IoT technology has developed rapidly. The Internet of Things is a comprehensive network that integrates location services, monitoring services, information identification and monitoring services through information exchange and communication technologies, such as video recognition technology, positioning technology, and wireless sensor technology. In order to monitor the operation mode of the microgrid in real time, find the source of the fault and locate the operation target, based on the Internet of Things technology, this paper installs wireless sensors in the line segment to monitor the line and other applications. This paper uses wireless sensor networks to record positioning variables, processes and data analysis to achieve the accuracy of microgrid operation target positioning. In addition, in order to improve the positioning accuracy of wireless sensor monitoring network and solve the problem of energy limitation, DV-Hop algorithm EB-IDMF algorithm and R-A algorithm are also introduced. Finally, the feasibility of the system is verified through experiments and tests. With the blessing of the positioning algorithm, the positioning accuracy is improved by 4.9%, which has great practical value for the target positioning of microgrid operation.

Zigbee-Based Low Power Consumption Wearables Device for Voice Data Transmission

Short-range wireless technologies can transmit real-time voice, audio, picture, and video communications. Such networks’ energy usage and transmission reach are crucial, especially for portable and power autonomous devices. Voice over Zigbee technology’s goal is to create a competitive service that excels in these performance factors. IEEE standard 802.15.4 specifies two layers for low-rate WPANs: the physical layer and the media access control layer, with a data rate limit of 250 kbps. This partnership used low-level PHY and MAC layers as the foundation for developing the Zigbee network protocol, security, and applications. To overcome the problem of lowering costs and power usage to make this technology more accessible to the general public. This system displays the network’s operational data, such as wireless voice communication. This effort was made to minimize the overall cost of manufacturing such gadgets that contribute to home automation systems and related projects. The primary goal of the research was to communicate voice through low-power microcontrollers such as 8-bit microcontrollers using Zigbee. In this study, we developed a wireless sensor network (WSN) communication system based on Zigbee to securely transfer speech data over a medium-range distance (medium) and lower the equipment cost and communication expenses by 30% without compromising the data integrity. A testbed has been established to validate the fundamental functionality of the proposed ZigBee-based home network system. The suggested system’s network coverage capabilities were evaluated, as well as its packet loss and energy savings in long-term wireless network monitoring duties.

Development of a Weather Station with Water Level and Waterflow Detection using Arduino

Weather data monitoring is important due to the drastic changes of weather around the world in recent years. Weather-related parameters are commonly measured using weather stations. Low-cost Arduino based weather station is suitable for public use to monitor local weather conditions in the vicinity of their residential area. This will enable quick response in natural disaster caused by the weather. In this work, the integration of water level and waterflow rate detection to the weather station allows hydrological data measurement in addition to the meteorological data. This capability makes the weather station suitable for further expansion into a wireless sensor network for flood monitoring and prediction. This weather station was developed using NodeMCU ESP32 microcontroller, ultrasonic sensor, BMP280 sensor, rain sensor and waterflow sensor. The remote data monitoring capability was realized using Blynk IoT platform. A prototype of this weather station was developed and tested in a simulated environment. Results show that this weather station is able to provide good measurement of meteorological and hydrological data.

PkCOs: Synchronization of Packet-Coupled Oscillators in Blast Wave Monitoring Networks

Blast waves with a large amount of energy, from the use of explosive weapons, is a major cause of traumatic brain injury in armed and security forces. The monitoring of blast waves is required for defence and civil applications. The utilization of wireless sensing technology to monitor blast waves has shown great advantages, such as easy deployment and flexibility. However, due to drifting embedded clock frequency, the establishment of a common timescale among distributed blast monitoring sensors has been a challenge, which may lead to a network failing to estimate the precise acoustic source location. This work adopts a packet-coupled oscillators (PkCOs) protocol to synchronize drifting clocks in a wireless blast wave monitoring network. In order to address packet collisions caused by the concurrent transmission, an anti-phase synchronization solution is utilized to maintain clock synchronization, and the corresponding superframe structure is developed to allow the hybrid transmission of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Sync</i> packet and the blast wave monitoring data. As a network scales up and the hop distance grows, the packet exchange lag increases during a superframe. This, along with the drifting clock frequency, leads to the degradation of synchronization performance while the clock frequency is usually assumed to be zero and nondrifting. Thus, a compensation strategy is proposed to eliminate the joint impacts and to improve synchronization precision. The theoretical performance analysis of the PkCOs algorithm in the network is presented along with verification by simulation means. Finally, the performance of the PkCOs synchronization protocol is evaluated on an IEEE 802.15.4 hardware testbed. The experimental results show that the PkCOs algorithm provides an alternative clock synchronization solution for blast wave monitoring networks.

Design and implementation of wireless sensor network for environmental monitoring

Wireless Sensor Networks (WSN) are being developed in the agriculture and weather station sectors to monitor and manage a number of objects. Sensor network hardware platforms are low-power embedded systems featuring a variety of sensors, such as on-board sensors and analogue I/O ports for adding sensors. The design of genuine environmental monitoring and communication systems is greatly aided by the creation of a WSN. A WSN is a collection of sensors that are geographically spread and specialized for monitoring and recording environmental variables and storing the findings in a central location. Limited power consumption as sensor nodes works on batteries, Nodes are mobile opposed to conventional wires, Usage in harsh environment, Nodes can be deployed in any fashion over an area, Easy to use and multi-layer design operation these are the main characteristics of WSN. Limits imposed on the energy storage device by their applications and deployment settings are less relevant to WSN environment-monitoring applications than controlling power consumption and optimizing data transmission. A WSN is used to record real-time traffic and environmental data in order to develop descriptive and predictive models for determining the optimum routes to reduce traffic congestion and, as a result, urban pollution. C

Network Monitoring Measurements for Quality of Service: A Review

One crucial challenge confronting operators worldwide is how to ensure that everything runs smoothly as well as how to monitor the network. The monitoring system should be accurate, easy to use, and quick enough to reflect network performance in a timely way. Passive network monitoring is an excellent tool for this. It could be used to look for issues with a single network device or a large-scale issue affecting the whole LAN or core network. However, passive network monitoring is not limited to issue resolution; it could also be used to generate network statistics and measure network performance. As shown in this review, it is a very strong tool, as seen by the sheer volume of data published on Google Scholar. The main objective of this review is to analyze and comprehend monitoring measurements for quality of service to serve as a resource for future research and application. Essential terms and concepts of network monitoring and their quality of service are presented. Network monitoring measurements (which can be passive, active, or hybrid) and their wireless network monitoring tools (which can be public domain or commercial tools) are also covered in terms of relevance, advantages, and disadvantages. Finally, the review is summarized.