Wireless Monitoring System Research Articles

Ti3C2Tx MXene Functionalized via Boron Doped MoS2 Quantum Dots: A Synergy of Heterojunctions and Doping Effect Enabling Ultrasensitive SO2 Detection at Room Temperature

AbstractThe design of mixed‐dimensional heterostructures has emerged to be a new frontier of research as it induces exciting physical/chemical properties that extend beyond the fundamental properties of single dimensional systems. Therefore, rational design of heterostructured materials with novel surface chemistry and tailored interfacial properties appears to be very promising for the devices such as the gas sensors. Here, a highly sensitive gas sensor device is constructed by employing heterostructures of boron doped molybdenum disulfide quantum dots (B‐MoS2 Qdots) assembled into the matrix of Ti3C2Tx MXene. Functionalization of MXene surface with B‐MoS2 Qdots as a result of strong electrostatic attraction leads to improved charge migration behavior, active site exposure and abundant specific surface area. As a result, the Ti3C2Tx/B‐MoS2 sensor device shows ultra‐high response (28,998.3% @ 3 ppm), ultra‐fast response rate (23.1% s−1), sub‐ppm (10 ppb lowest) detection of sulfur dioxide (SO2) gas and excellent reversibility at room temperature. Density functional theory‐based calculations indicate that enhanced SO2 sensing performance results from synergy of the 2D‐0D heterostructure formation and preferential adsorption of SO2, induced by doped boron (B) heteroatoms in Qdots. Finally, a portable and wireless SO2 monitoring system is demonstrated for real‐time detection of SO2 leakage and quantification under certain circumstances.

A versatile optoelectronic device for ultrasensitive negative-positive pressure sensing applications

In the work, a versatile optoelectronic device with ultrasensitive negative-positive pressure sensing capabilities, integrated with a wireless monitoring system is fabricated and demonstrated. The device comprises a monolithic GaN chip with a polydimethylsiloxane cavity and nanograting, which effectively transduces pressure stimuli into optical changes detected by the GaN chip. The developed device exhibits an ultra-low detection limit for a mass of 0.03 mg, a pressure of 2.94 Pa, and a water depth of 0.3 mm, with a detection range of -100 kPa to 30.5 kPa and high stability. The versatility of the device is demonstrated by its ability to monitor heart pulse, grip strength, and respiration. Its integration with a wireless data transmission system enables real-time monitoring of human activity and heart rate underwater, making it suitable for precise measurements in various practical applications.

Enhancing water usage efficiency in agriculture through smart systems: a review

Abstract As the scarcity of clean water becomes more pronounced, significant challenges emerge in efforts to uphold food security and achieve sustainable progress, particularly on a global scale. Agriculture stands out as one of the primary sectors significantly contributing to water consumption. Thus, enhancing water usage efficiency within irrigated agricultural systems holds paramount importance to ensure the continued development of agricultural sustainability. One promising avenue lies in the advancement of intelligent irrigation systems, particularly leveraging wireless communications technology, monitoring systems, and advanced control strategies to optimize irrigation scheduling. This study adopts a qualitative methodology, grounded in a thorough examination of literature adhering to specific criteria, including publications in indexed journals, articles, or research papers published in the past ten years. It introduces diverse irrigation control and observation methodologies employed in recent times. An intriguing proposition emerges regarding the integration of soil, temperature, and humidity monitoring systems with predictive control models, potentially augmenting water usage efficiency. Through this review, researchers will be able to monitor and create control prospects related to irrigation agriculture as well as identify directions and gaps for future research activities in this field.

Augmented Reality-Enhanced Microwave-Based Wireless Monitoring System for Smart Coating Applications

Augmented Reality-Enhanced Microwave-Based Wireless Monitoring System for Smart Coating Applications

Integration of Automated Anomaly Detection with Real-Time Fish Stress Monitoring Using QR Code-Enabled Biosensors in Diverse Aquatic Environments

Background and Objectives:In our laboratory, we have developed a biosensor capable of monitoring fish blood glucose levels as an indicator of stress response in real time. Previous studies faced challenges with traditional communication systems using radio waves or visible light, which were susceptible to interference from water mediums and ambient light. Therefore, this research aimed to develop a stress response monitoring system that could transmit information even in seawater and freshwater environments, utilizing QR code technology with error correction capabilities and automatically detecting abrupt anomaly changes in sensor response values.Materials and Methods:The glucose biosensor was constructed using a needle-type electrode with a Pt/Ir wire (φ: 0.178 mm) as the working electrode and Ag/AgCl as the reference electrode, with glucose oxidase immobilized on the working electrode surface for glucose oxidation. A microcontroller development kit (M5Stack Core2) was employed to convert sensor response values into QR codes, allowing for voltage application to the sensor and QR code display based on sensor response values. An iOS application was developed as a reading module to enable communication via QR codes. Stress response was monitored using freshwater fish (Nile tilapia, Oreochromis niloticus) and saltwater fish (Largescale Blackfish, Girella punctata). Additionally, a model capable of detecting abnormal sensor data using a One-Class Support Vector Machine was created utilizing baseline glucose concentration data. This model was integrated into a webcam control program to attempt real-time and automatically detect abnormal data.Results and Discussion:The QR code display system using M5Stack Core2 proved effective in applying voltage to the glucose biosensor, converting sensor response values to QR codes, and displaying them on the LCD screen. Stress response monitoring of freshwater and saltwater fish resulted in data retrieval rates of 100% and 84.6%, respectively, demonstrating the feasibility of wireless monitoring via QR codes regardless of water type. Furthermore, the stress response monitoring system incorporating abnormal data detection capabilities successfully identified communication issues and variations in response values due to stress induction, providing user feedback. These results highlight the capability of the system to monitor fluctuations in fish blood glucose levels in real time, potentially contributing to addressing issues such as the spread of fish diseases and mortality caused by stress. Future efforts will incorporate cloud storage and remote access features to enable real-time data monitoring and analysis from any location.Conclusion:Developing a real-time wireless monitoring system using QR code technology significantly advances understanding and addressing fish stress responses. By enabling continuous monitoring of glucose levels in fish, the system has the potential to mitigate the adverse effects of stress-related diseases and mortality. Further enhancements, including cloud integration and remote access, aim to enhance the system's usability and accessibility for researchers and aquaculture professionals, ultimately contributing to improved fish welfare and management practices. Figure 1

The application of the non-quadratic regularization method for direction finding and adaptive signal processing

The paper considers the issues of detection, spatial localization, and isolation of individual radio signals from their additive mixture received by the elements of an antenna array with digital signal processing. To solve the above issues, the method of non-quadratic regularization is applied in the signal model, which takes into account signal delays on the antenna array elements to a first approximation. Using the Lagrange multiplier method, the adaptive estimates of signals were obtained and a direction finding function was constructed. The function maxima are identified with the directions to the radiation sources. An effective method for iterative solution of the problem in Lp space for any p values is proposed. The simulation results are set out for p = 1, demonstrating the possibility of detecting and estimating the parameters of weak signals. The signal level does not exceed the noise and interference level against the background of interfering intense radiation sources. The proposed method can significantly increase the effectiveness of solving problems of detecting and direction finding signals from stationary objects and tracking mobile objects both in the traditional single-site radio monitoring systems and passive location radio systems.

Smart Sensor Placement For Thermal Monitoring Of Concrete

Structural health monitoring (SHM) has become an inevitable part in a life span of a structure due to its potential to ensure the public safety and to increase the life span of the structure. Monitoring any kind of structures for various parameters, using wireless smart sensors has gained popularity in recent past. This paper discusses the development of low cost real time wireless smart sensor monitoring system to monitor early age concrete temperature in real time. Temperature of two early age concrete mixes (Mix1, Mix2) were measured in real time for 24 hours by using DS18B20 sensors connected with the Node Mc u, which is an open source IOT platform. Temperature measurements were saved and visualized in real time using Thing Speak TM which is an open IoT online platform with MATLAB analytics. The temperature sensor DS18B20 was selected such that it is suitable to measure temperature readings of the concrete without any interference of the chemical reactions in concrete. Calibration methods and temperature variation with different concrete mixes are also discussed. It could be seen that the wireless temperature monitoring system performed adequately and it can be considered as a better low cost alternative for traditional wired temperature monitoring system.

A wearable, self-sustainable, and wireless plantar pressure and temperature monitoring system for foot ulceration prognosis and rehabilitation

Continuous foot temperature and pressure monitoring are desirable for prevention and care of foot health conditions such as Diabetic foot ulceration (DFU). However, monitoring these parameters simultaneously is complex, and mostly rely on sensors with undisrupted power supply integration. Herein, we propose high-performance self-sustainable smart footwear capable of monitoring foot pressure and temperature at various locations for real-time applications. The footwear consists of three modules of an integrated electromagnetic generator (EMG) and triboelectric (TENG) self-powered pressure sensors operated by very elastic 3D printed thermoplastic polyurethane (TPU) springs formed by stacking circular plates that allow TENG pressure sensors to be embedded within. Additionally, Laser-induced graphene (LIG) temperature sensors are used for monitoring foot temperature. The embedded EMG can deliver high output power during various activities: walking (38 mW), running (154 mW), and jumping (75 mW), sufficient to power signal processing and transmission circuitries for wireless monitoring of foot temperature and pressure. TENG-based pressure sensors and LIG temperature sensors (LTS) embedded in this design allow mapping of foot pressure (0.2 V/kPa at 1 Hz) and foot temperature (0.55 Ω °C−1) continuously. Finally, footwear was assembled successfully to demonstrate wireless self-sustainable multisensory smart footwear for monitoring foot pressure and temperature to prevent and rehabilitate diabetic foot ulcers.

Comparison of mathematical and experimental studies of the radio technical characteristics of an acousto-optoelectronic spectrum analyzer for RF monitoring devices

Formulation of the problem. To analyze radio frequency monitoring systems and complexes that can operate in a wide frequency band with high performance parameters, devices such as acousto-optical spectrum analyzers (AOS) are used. This class of devices has several types of implementation. The objective of this article is to increase efficiency in the development of acousto-optoelectronic devices in radio frequency monitoring systems. Target. Based on theoretical and experimental studies, it is necessary to determine which version of the acousto-optical spectrum analyzer will ensure the operation of radio frequency monitoring tools with the best values of radio frequency characteristics, such as dynamic range and signal-to-noise ratio. Results. A calculation of the dynamic range of an acousto-optical spectrum analyzer is presented, as well as a comparative analysis of several acousto-optical spectrum analyzers (an acousto-optic spectrum analyzer with time integration and an acousto-optic spectrum analyzer with spatio-temporal integration) to determine the most effective type of device for radio frequency monitoring systems. Practical significance. The use of the selected design of an acousto-optical spectrum analyzer will make it possible to replace other devices and replace less efficient analogues of the device, which will improve the operation of radio frequency monitoring systems and complexes.

The method of "joint" determination of coordinates of radio-emitting objects by aerial radio monitoring systems based on the principle of two-channel Petrov

Problem statement. The growing use of information received by airborne radio monitoring systems (VRM) in real time also places increased demands on the accuracy of determining the coordinates of radio-emitting objects (RIO). An important, and in some cases the main reason preventing the achievement of the required levels of accuracy in determining the coordinates of RIO by VRM systems using classical bearing methods are all kinds of interfering factors in the observation channel. Solutions known in the field of VRM to reduce the influence of interfering factors on the accuracy of determining the coordinates of the RIO are based on the use of various ways to eliminate (weaken) them, as a rule, in places of occurrence, the implementation of which does not always provide the required efficiency, and in some cases is problematic. Goal. To develop, based on the Petrov two-channel principle, a new method for determining the coordinates of terrestrial RIO by VRM systems, which would ensure a reduction (compensation) of the influence of interfering factors on the accuracy of estimating their (RIO) location. Results. The necessary conditions for the applicability of the Petrov two-channel principle in passive VRM systems are substantiated; a method has been developed to reduce (compensate) the influence of interfering factors on the accuracy of estimating the coordinates of terrestrial RIO, including the operations and variants of the proposed method; a methodology has been developed for the analytical synthesis of optimal algorithms for calculating the values of errors in determining the coordinates of RIO at certain points in the state space of objects according to their known values in others; for a special case, algorithms for the implementation of the proposed method are synthesized using the example of the angle-measuring method for determining the coordinates of ground-based fixed objects; the results of the computational experiment confirmed the operability and higher (compared with the classical angle-measuring method) efficiency (in terms of the size of the working area and accuracy) of the proposed method. Practical significance. The proposed method for determining the coordinates of RIO by VRM systems can be used both independently and as an addition to classical passive radar methods to increase their working areas and (or) accuracy.

Automated wireless system for monitoring the technical condition of chimneys

The present paper considers the technology of monitoring the technical condition of chimneys in order to identify areas of increased heat losses. The technology involves an automated wireless monitoring system that includes an unmanned aircraft with additional equipment. Aim. To study the operation safety of reinforced concrete chimneys used in hazardous industrial facilities. The presented monitoring technology tackles the task of prompt identification of defects and damages to reduce the risks of potentially hazardous conditions. While developing technology for monitoring the technical condition, special attention is paid to its autonomy and intelligence. At the first stage, sensors, coordinators and remote thermometry system are installed with the transmission of data on the temperature of the chimney trunk to the control center. At the next stage, the outer surface of the chimney is examined using an unmanned aicraft equipped with a thermal imaging camera to verify information about heat losses. The final stage involves creating a thermogram of the object and a scheme of the possible locations of the identified defects in order to plan repair works. In addition, the paper introduces main advantages of the suggested technology.

Fabric-based lamina emergent MXene-based electrode for electrophysiological monitoring

Commercial wearable biosignal sensing technologies encounter challenges associated with irritation or discomfort caused by unwanted objects in direct contact with the skin, which can discourage the widespread adoption of wearable devices. To address this issue, we propose a fabric-based lamina emergent MXene-based electrode, a lightweight and flexible shape-morphing wearable bioelectrode. This work offers an innovative approach to biosignal sensing by harnessing the high electrical conductivity and low skin-to-electrode contact impedance of MXene-based dry electrodes. Its design, inspired by Nesler’s pneumatic interference actuator, ensures stable skin-to-electrode contact, enabling robust biosignal detection in diverse situations. Extensive research is conducted on key design parameters, such as the width and number of multiple semicircular legs, the radius of the anchoring frame, and pneumatic pressure, to accommodate a wide range of applications. Furthermore, a real-time wireless electrophysiological monitoring system has been developed, with a signal-to-noise ratio and accuracy comparable to those of commercial bioelectrodes. This work excels in recognizing various hand gestures through a convolutional neural network, ultimately introducing a shape-morphing electrode that provides reliable, high-performance biosignal sensing for dynamic users.

МАТЕМАТИЧЕСКАЯ МОДЕЛЬ ПРОЦЕССА ДОСТАВКИ ТЕЛЕМЕТРИЧЕСКИХ СООБЩЕНИЙ В СИСТЕМЕ МЕДИЦИНСКОГО ИНТЕРНЕТА ВЕЩЕЙ

Currently, research and development are relevant aimed at increasing the efficiency of transmission of telemetry messages in wireless remote monitoring systems used by medical workers to provide timely assistance to patients under observation. The technical basis for transmitting such messages is provided by medical Internet of Things systems. The article is devoted to the development of a mathematical model of the process of delivering telemetric messages in such a system. In the course of the study, analytical expressions were obtained that make it possible to estimate the average delivery time of messages from the patient’s sensory device to the healthcare worker’s wireless device, depending on the response intervals of the retransmission timers installed in the transmitting and receiving elements of the system. The results obtained allow us to theoretically substantiate the choice of retransmission timeout values that ensure minimization of the average message delivery time at the current level of bit error intensity.

Gold Nanowire Sponge Electrochemistry for Permeable Wearable Sweat Analysis Comfortably and Wirelessly.

Electrochemistry-based wearable and wireless sweat analysis is emerging as a promising noninvasive method for real-time health monitoring by tracking chemical and biological markers without the need for invasive blood sampling. It offers the potential to remotely monitor human sweat conditions in relation to metabolic health, stress, and electrolyte balance, which have implications for athletes, patients with chronic conditions, and individuals for the early detection and management of health issues. The state-of-the-art mainstream technology is dominated by the concept of a wearable microfluidic chip, typically based on elastomeric PDMS. While outstanding sensing performance can be realized, the design suffers from the poor permeability of PDMS, which could cause skin redness or irritation. Here, we introduce an omnidirectionally permeable, deformable, and wearable sweat analysis system based on gold nanowire sponges. We demonstrate the concept of all-in-one soft sponge electrochemistry, where the working, reference, and counter electrodes and electrolytes are all integrated within the sponge matrix. The intrinsic porosity of sponge in conjunction with vertically aligned gold nanowire electrodes gives rise to a high electrochemically active surface area of ∼67 cm2. Remarkably, this all-in-one sponge-based electrochemical system exhibited stable performance under a pressure of 10 kPa and 300% omnidirectional strain. The gold sponge biosensing electrodes could be sandwiched between two biocompatible sweat pads, which can serve as natural sweat collection and outflow layers. This naturally biocompatible and permeable platform can be integrated with wireless communication circuits, leading to a wireless sweat analysis system for the real-time monitoring of glucose, lactate, and pH during exercise.

Application of a specialist nurse–led wireless smart monitoring system in elderly patients with persistent atrial fibrillation

Background: With the increase in the elderly population, the prevalence of persistent atrial fibrillation (AF) among older adults has significantly risen, becoming one of the crucial cardiovascular diseases affecting the health and quality of life of the elderly. Patients with persistent AF require continuous cardiac function monitoring to prevent possible complications such as stroke and heart failure. Traditional monitoring methods often necessitate frequent hospital visits, increasing the economic burden and psychological stress on patients. With advancements in medical technology, wireless smart monitoring systems have emerged as a new remote health care technology, offering a more convenient and effective monitoring option for patients with persistent AF. Specialist nurses play a pivotal role in monitoring and managing patients using these systems. Their professional knowledge and skills are vital for improving monitoring efficiency and patient compliance. Therefore, this study aims to explore the application of wireless smart monitoring systems led by specialist nurses in elderly patients with persistent AF, in hopes of providing a scientific basis for improving the monitoring and management of this patient group. Methods: A total of 88 elderly patients with persistent atrial fibrillation admitted to the Cardiology Ward of a tertiary hospital in Weifang City from October 2021 to April 2023 were selected as research subjects. They were divided into an intervention group and a control group with conventional care, with 44 cases in each group, according to the order of admission. The control group received conventional hospitalization guidance, while the intervention group utilized a wireless smart monitoring system led by specialist nurses. The effects before and after the intervention in both groups were compared. Results: The intervention group patients had better scores in terms of mental stress, sleep quality, and comfort compared with the control group, and the nursing shift change time during hospitalization for the intervention group was shorter than that of the control group (P<0.05). Conclusions: The wireless smart monitoring system led by specialist nurses can improve the mental stress and sleep conditions of elderly patients with persistent atrial fibrillation, increase comfort, and enhance the efficiency of nursing shift changes.

Hardware-software implementation of a local Wi-Fi network for the transmission of biomedical signals

The object of this study is a wireless local Wi-Fi network for broadcasting biomedical signals, its structure, and principles of construction. The task of minimizing the power consumption of a Wi-Fi transmitter has been addressed, which provides the possibility of building a wireless system for long-term monitoring of biomedical signals. As a result, a functional diagram of a wireless Holter monitoring system based on an ESP32 microcontroller was constructed, which includes a subsystem for setting up and diagnosing system units using MATLAB software packages, an ECG signal generator, and a multifunctional PCIe board from National Instruments. Evaluation criteria and methods for minimizing power consumption by an autonomous Wi-Fi transmitter have been proposed. Methods for synchronizing the working cycles of the transmitter and receiver of the Holter monitoring system were determined. A procedure for determining the optimal biosignal measurement frequency is presented, at which the distortion of ECG signals would be minimal, which means that the signal could be transmitted without losses. The concept of constructing an algorithm for implementing a program for a Wi-Fi transmitter has been developed, ensuring parallel execution of ECG signal measurement operations and their transmission over a local network. The data from semi-naturalistic tests with an experimental Holter monitoring system with a pre-setup subsystem and using external measuring devices, a computer, and the MATLAB software environment are presented. A comparative analysis of the experimental data with primary ECG signals and ECG signals at the receiver output showed a fairly stable correspondence between the input and output ECG signals. The proposed algorithms make it possible to reduce the average current consumption of the ESP32 microcontroller to 50.5 mA. The results of the study demonstrate the possibility of constructing an energy-efficient wireless system for long-term monitoring of biomedical signals based on the Wi-Fi interface

Localization algorithm of soil moisture monitoring in irrigation area based on weighted correction of distance measurement

At present, Wireless Sensor Network technology are widely used in the fields of agricultural environment monitoring. Whether we use ground network or ground-air coordination, the position coordinates of unknown nodes are an important feature of sensor information collection. To achieve the goal of a wireless monitoring system for field soil irrigation and its node positioning, we proposed an RSSI (Received Signal Intensity Indication)-based agricultural environment irrigation monitoring system. The algorithm has three stages: RSSI ranging, error correction, and localization. In the RSSI ranging phase, we obtain inter-node measurement distance by wireless channel modeling. In the distance-weighted correction phase, considering the difference between the measured distance of the beacon nodes and the actual distance, we analyze and select the relative error coefficient for the beacon nodes to correct the measured distance between the unknown nodes and the beacon nodes within their communication range. In the positioning stage for the nodes to be located, we estimated the required node coordinates using a weighted centroid localization method. In addition, by analyzing the monitoring data, we know the changes in soil moisture in real-time, which provides new ideas for irrigation automation and the efficient utilization of water resources. When designing the algorithm, we thoroughly considered the influence of RSSI ranging inaccuracy and the quantity of beacon nodes on the localization precision. The test demonstrated that the method presented in this paper has higher localization precision and lower computation cost.

The simulation of wireless body temperature monitoring system based on Internet of Things

Traditional body temperature monitoring technology has some problems, such as inaccurate manual reading, unable to monitor continuously for a long time, and difficult data storage and analysis. To solve these problems, this paper designs an application scenario of Internet of Things in body temperature monitoring, which integrates Internet of Things, network communication, network programming and other technologies, designs the overall architecture, topology structure and IP address allocation scheme of the system, and realizes real-time acquisition, transmission, storage, analysis, and display functions based on the Packet Tracer simulation platform. The performance evaluation and optimization are also carried out. The system realizes wireless monitoring and analysis of the body temperature data collected by the temperature sensor through the home gateway and single chip microcomputer and other devices. After testing, the designed system is stable, which provides a solution for the application of Internet of Things in body temperature monitoring.

Research on wireless monitoring system and algorithms for preload force utilizing machine learning and electromechanical impedance

The root mean square deviation is a common way to measure the electromechanical impedance of piezoceramic transducers that are used for traditional preload monitoring. However, due to the impedance signal’s high sensitivity to temperature, most current research is carried out under the same temperature conditions to avoid its effects. Even so, it is impossible to ignore the temperature factor in practical engineering, which hinders the application of impedance technology. Therefore, this paper proposes a novel approach for preload monitoring in actual engineering: using a wireless impedance signal acquisition platform to collect long-distance impedance signals and then establishing a predicted model based on machine learning (ML) considering the temperature. The wireless impedance signal acquisition platform includes a smart washer, a piezoelectric impedance wireless sensing device, and the host computer software. This test established a dataset under various operating conditions and developed a machine-learning-based predictive model. After comparing five typical ML algorithms, it was discovered that XGBoost performed better in prediction accuracy and generalization ability. Moreover, the Shapley additive explanation method is utilized to further analyze and interpret the XGBoost model. It indicates that ML primarily relies on numerical features (such as the area of each subinterval) to identify the impedance signal and predict the prestress, whereas information features (such as temperature value, peak, etc.) have little influence on the model’s output. Finally, the results above demonstrate that the ML-based models can predict the preload at different temperatures, effectively reducing temperature interference.

Risk-based asset management framework for highway retaining wall systems using wireless structural health monitoring data

Retaining walls are important structural systems used in the construction of highways. With asset management methods for retaining wall inventories lagging those developed for highway bridges, there is a need to develop risk management methods for these critical structural systems. A major challenge is the vast inventories of retaining walls that asset managers must manage and the inherent limitations of visual inspections. This study proposes an asset management framework for retaining walls based on risk assessments using structural monitoring data. First, a long-term wireless monitoring solution is proposed to measure wall tilt and strain over long periods of time. Second, an analytical framework is developed to separate wall thermal responses from lateral earth pressures responses with the latter used to extract estimated lateral earth pressure distributions. A statistical distribution of lateral earth pressures are used in a reliability assessment of the wall to provide a measure of failure probability that can be combined with failure consequences to estimate asset risk. To illustrate the proposed methodology, a reinforced concrete cantilever retaining wall panel is selected for long-term structural health monitoring. A wireless structural health monitoring system is installed to measure the tilt, strain, and temperature response of the wall continuously over 15 months. The study reveals the wall exhibits strong diurnal and seasonal variations offering insight into wall behavior under operational conditions. Hypothesized levels of corrosion in the steel reinforcement at the base of the wall are explored to estimate the wall reliability. Even under the assumption of 20% reinforcement section loss, the monitored wall was found to have a reliability index well above 3.0.