Performance Monitoring System Research Articles

Telemetry to solve dynamic analysis of a distributed system

In the modern software development world, implementing distributed solutions has become quite common due to the flexibility it brings to big companies. The downside is that when developing such systems, especially in many teams, global design problems may not be obvious and lead to a slowdown in the development process or even problems with the location of errors or degradation of overall system performance. In addition, the timely reaction to system degradation is complicated by the distributed nature of the architecture; while manually configuring rules for reporting problematic situations can be time-consuming and still incomplete, automatic detection of possible system anomalies will give engineers (especially Software Reliability Engineers) the focus on problems. For this reason, applications that can dynamically analyse the system for problems have great potential. Currently, the topic of using telemetry for system analysis is actively studied and gaining traction, so further research is valuable. The work aims to theoretically and practically prove the possibility of using telemetry to analyse a distributed information system and detect harmful architectural practices and anomalous events. To do this, firstly, a detailed overview of the problems related to the topic and the feasibility of using telemetry is provided; the next section briefly describes the history of the development of monitoring systems and the key points of the latest OpenTelemetry standard, reviews popular application performance monitoring systems, and defines innovative features to be further researched. The main part includes an explanation of the approach used to collect and process telemetry, a reasoning behind the usage of Neo4j as a data storage solution, a practical overview of graph theory algorithms that help in the analysis of the collected data, and a description outlining how the PCA algorithm is employed to detect unusual situations in the whole system instead of individual metrics. The results provide an example of using the software presented with Neo4j Bloom to visualise and analyse the data collected over several hours from the OpenTelemetry Demo test system. The last section contains additional remarks on the results of the study.

Research on fault detection and remote monitoring system of variable speed constant frequency wind turbine based on Internet of Things

In order to study the operating characteristics of variable speed constant frequency wind turbine under different working conditions and the monitoring system of wind turbine. In this paper, the simulation model of each component system of wind turbine is established by MATLAB/Simulink module, and the influence law of different wind speed and ground fault types on the output power of wind turbine is studied. The active power of wind turbines under different short-circuit fault types is compared. At the same time, in order to realize real-time monitoring of wind turbine speed and output power, an online monitoring system for wind turbine operation based on industrial Internet of Things is proposed, and the composition and operation characteristics of this remote monitoring system are given. The practical application shows that the on-line monitoring system can accurately and remotely monitor the running status of the wind turbine and avoid the unstable running of the wind turbine. The research conclusions of this paper can provide reference for the design and construction of wind turbines and the operation of connecting to the power grid.

Web-Based Education Personnel Management: An Innovation in the Development of Education Management in the 21st Century

In the 21st century, technology-based institutions require clear parameters for evaluating employee performance. Manual performance assessment processes necessitate the development of a technology-driven information system to streamline leadership's evaluation of employees. This study is dedicated to analyzing the prerequisites for designing an information technology-based performance monitoring system tailored for educational staffs, organized into four stages: defining, designing, developing, and disseminating. By involving 71 educational staffs, this study resulted in the creation of the SI-IKAH (Sistem Input Kinerja Harian Tenaga Kependidikan) or the Daily Performance Input System for Education Personnel, specifically designed for the Universitas Pendidikan Indonesia Sumedang Campus. The system comprises modules for collecting personal information, work unit details, types of tasks, work hours, work outcomes, and generating reports for educational staff. This study concludes that the implementation of this system has the potential to boost employees performance motivation, ensure the currency of institutional data, and enhance the efficiency of employee work assessments.

SiSMA‐SWMS: Signature‐based Secure Monitoring Approach for Smart Waste Monitoring Systems

AbstractWith the speedy growth of the populace, corresponding waste also grows, notably raising greater concern about the monitoring of waste in urban areas. Although the traditional method of waste monitoring has benefited city waste management systems, it remains time‐consuming, inefficient, and detrimental to public health. This situation can be improved by integrating advanced technologies, which can significantly enhance the flexibility and performance of waste monitoring systems. However, these advanced technologies encounter numerous security challenges. In this article, we have implemented a signature‐based monitoring approach to oversee the status of smart bins. To ensure the security, robustness, and reliability of the introduced protocol, we utilized tools such as AVISPA, Scyther, the ROR model, and Mao and Boyd logic. As discussed in the informal security analysis, the introduced protocol successfully fulfills the security requirements for smart waste monitoring systems. Finally, an in‐depth comparative analysis of the related works and the introduced protocol shows that the latter provides greater security, reliability, and efficiency. As a result, the reliability and hardness of the cryptographic operations used in the introduced protocol make it secure enough to use in real‐world applications.

Fuzzy-Based Control System of Drilling Fluids Density and Apparent Viscosity Simultaneously: An Alternative Strategy to Support Autonomous Drilling Operations

Summary Among all the systems that make up a drilling operation, the production and correction of drilling fluid can be considered the heart of the process. Among the main objectives of the drilling fluid are to cool the drill bit and maintain the pressure gradient inside the drilling well, which is done by controlling its density. Another important function is transporting the cuttings from the bottom to the surface and keeping them in suspension in case of stoppage, which directly depends on the viscosity of the drilling fluid. Density and viscosity must be constantly maintained within an operational window, and failures can lead to serious accidents, even the loss of the well. Currently, this control is done manually: An operator collects samples of the fluid and takes them for analysis in the laboratory and subsequently makes the necessary corrections by manually adding products to the fluid. To reduce process dead time, keep personnel on board, and increase operation safety, a control and monitoring system is necessary. Fuzzy logic was chosen because it can be combined with classical methods, is cheap to develop and implement, and can be customized in terms of natural language, capturing the knowledge acquired by operators from equipment operation, bench tests, etc. This work aimed to develop a novel real-time monitoring and fuzzy-based system for simultaneous control of the apparent viscosity and density of non-Newtonian fluids, dealing with the inevitable interactions between them in a pilot experimental unit. A pilot plant was built to evaluate the fuzzy system approach for modeling and controlling of density and apparent viscosity of drilling fluids. The pilot flow loop comprises a mixing tank, solids vibrating feeders, and a water-dosing pump. The unit was instrumented with online sensors to measure fluid density, temperature, flow rate, differential pressure, and viscosity. The apparent viscosity and density of the non-Newtonian fluid were controlled by manipulating the dosage of carboxymethylcellulose (CMC), barite, and water. The proposed methodology was compared to a classical proportional-integral-derivative (PID) controller in servo and regulatory scenarios for apparent viscosity and density. The results showed that the fuzzy controller dealt adequately with the effect of variable interactions, keeping both variables within their setpoint ranges, demonstrating the ability to control them individually despite their interactions. These results also showed that the fuzzy-based controller could easily be integrated into a diagnostic-predictive monitoring system to control fluid properties, accomplishing setpoint changes and rejecting undesirable disturbances presenting a maximum overshoot of 7.5% for apparent viscosity and 0.3% for density.

Analysis of Sleep, Nocturnal Physiology, and Physical Demands of NCAA Women's Ice Hockey Across a Championship Season.

Merrigan, JJ, Stone, JD, Kraemer, WJ, Friend, C, Lennon, K, Vatne, EA, and Hagen, JA. Analysis of sleep, nocturnal physiology, and physical demands of NCAA women's ice hockey across a championship season. J Strength Cond Res 38(4): 694-703, 2024-The aims of this study were to evaluate the (a) relationships between daily physical demands and nighttime sleep, heart rate (HR), and heart rate variability (HRV); (b) weekly changes in physical demands and sleep; and (c) differences among positions and between training and competition during a competitive season in National Collegiate Athletic Association (NCAA) women's ice hockey. Twenty-five NCAA Division I women's ice hockey athletes wore a sensor at night to monitor sleep quantity or quality (e.g., time asleep and sleep efficiency) and physiology (e.g., HR and HRV). During training and competitions (31 regular season and 7 postseason), athletes wore performance monitoring systems to assess workload demands (e.g., training impulse and TRIMP). As internal workload (TRIMP, Time >80% of HRmax, Average HR) during training or competition increased, nocturnal HRV decreased, HR increased, and Sleep Duration, Sleep Score, and Readiness Score decreased that night. Across the season, athletes experienced lower HRV, but exhibited longer sleep durations. Training Distance, Duration, Time >80% HRmax, Average HR, and TRIMP decreased, whereas competition Total Distance, Duration, and TRIMP increased across weeks throughout the season. There were differences across positions and season blocks when evaluating these data at the mesocycle level. Athletes slept longer before competition compared with training, but physiological data did not differ. Competitions had greater physiological demands than training. We speculate that the increased focus on sleep hygiene, as evidenced by the increase in sleep over the season, may have served as a recovery aid to combat physiological stress of accumulated demands of competitions that increased over time into postseason tournaments.

Investigating the suitability of online flow cytometry for monitoring full-scale drinking water ozone system disinfection effectiveness

While online monitoring of physicochemical parameters has widely been incorporated into drinking water treatment systems, online microbial monitoring has lagged behind, resulting in the use of surrogate parameters (disinfectant residual, applied dose, concentration × time, CT) to assess disinfection system performance. Online flow cytometry (online FCM) allows for automated quantification of total and intact microbial cells. This study sought to investigate the feasibility of online FCM for full-scale drinking water ozone disinfection system performance monitoring. A water treatment plant with high lime solids turbidity in the ozone contactor influent was selected to evaluate the online FCM in challenging conditions. Total and intact cell counts were monitored for 40 days and compared to surrogate parameters (ozone residual, ozone dose, and CT) and grab sample assay results for cellular adenosine triphosphate (cATP), heterotrophic plate counts (HPC), impedance flow cytometry, and 16S rRNA gene sequencing. Online FCM provided insight into the dynamics of the full-scale ozone system, including offering early warning of increased contactor effluent cell concentrations, which was not observed using surrogate measures. Positive correlations were observed between online FCM intact cell counts and cATP levels (Kendall's tau=0.40), HPC (Kendall's tau=0.20), and impedance flow cytometry results (Kendall's tau=0.30). Though a strong correlation between log intact cell removal and CT was not observed, 16S rRNA gene sequencing results showed that passage through the ozone contactor significantly changed the microbial community (p < 0.05). Potential causes of the low overall cell inactivation in the contactor and the significant changes in the microbial community after ozonation include regrowth in the later chambers of the contactor and varied ozone resistance of drinking water microorganisms. This study demonstrates the suitability of direct, online microbial analysis for monitoring full-scale disinfection systems.

Examining the Integration of a GPS-based Staff Performance Monitoring and Assessment System within Academic Settings

Research evidence of manipulations of appraisal systems of various institutions in Nigeria abound, and little is known about the application of a Geographical positioning system (GPS) enabled system in this context. To cover this gap, this study investigates the integration of a real-time staff performance monitoring and assessment system with GPS technology, within academic settings. With the increasing emphasis on quality education and efficient resource utilization, academic institutions are exploring innovative approaches to monitor staff performance and student outcomes. The integration of real-time performance systems offers a promising avenue to achieve these goals by providing timely feedback, fostering accountability, and facilitating data-driven decision-making processes. This study outlines the key components of such a system, including its technological infrastructure, data collection methods, and performance evaluation metrics. Additionally, it explores the potential benefits and challenges associated with its adoption, considering factors such as staff engagement, privacy concerns, and institutional culture. Through a comprehensive examination of existing literature and case studies, this research aims to provide valuable insights and recommendations for academic institutions seeking to leverage real-time staff performance monitoring for institutional enhancement and educational excellence. While this study highlights the significance of stakeholder collaboration and continuous improvement mechanisms in ensuring the successful integration and sustained effectiveness of the monitoring system, it introduces a nuanced novel GPS technology and highlights some design implications which will guide future human-computer interaction researchers.

Development and implementation of real-time staff performance monitoring and evaluation system based on Global Positioning System (GPS)

This work presents the development and implementation of a Real-Time Staff Performance Monitoring and Evaluation System (RT-SPMES) using Global Positioning System (GPS) technology. In line with the dynamism of the workplace, due to rapid changes in technology, existing staff performance appraisal systems have fallen short of expectations due to their manual nature. Hence, the need arises for a more robust approach to monitoring and evaluating employee work performance. To achieve this, this work carried out an exhaustive review of existing performance evaluation methods within the academic and a conceptual architecture was developed. A real-time monitoring and evaluation system was developed, using PHP programming language, Hyper Text Markup Language and Cascading Styles Sheet. The system is hosted on Azure Cloud infrastructure. Through sufficient testing of the developed system developed in this work, it was asserted effectively monitors employee performance in real-time, paving the way for an objective appraisal process devoid of bias and manipulation.

Research on a Comprehensive Monitoring System for Tunnel Operation based on the Internet of Things and Artificial Intelligence Identification Technology

This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations. These risks include safety control risks, increased traffic flow, extreme weather events, and movement of tectonic plates. The proposed system is based on the Internet of Things and artificial intelligence identification technology. The monitoring system will cover various aspects of tunnel operations, such as the slope of the entrance, the structural safety of the cave body, toxic and harmful gases that may appear during operation, excessively high and low-temperature humidity, poor illumination, water leakage or road water accumulation caused by extreme weather, combustion and smoke caused by fires, and more. The system will enable comprehensive monitoring and early warning of fire protection systems, accident vehicles, and overheating vehicles. This will effectively improve safety during tunnel operation.

A data-driven approach toward a machine- and system-level performance monitoring digital twin for production lines

Efficient performance monitoring in production systems holds paramount importance as it enables organizations to optimize their manufacturing processes, enhance productivity, and maintain a competitive edge in the market. Typically, machine and system level performance monitoring systems are investigated independently, whereas an integrated approach that considers both levels can offer valuable insights and benefits. This paper introduces a data-driven approach for evaluating and improving the performance of production lines by monitoring the performance of both individual machines and their interactions as a system. The approach begins with a rigorous methodology for classifying machine states recorded by the Manufacturing Execution System (MES) into finer-grained substates, enabling a comprehensive analysis of machine cycle time variability. Subsequently, these substates are leveraged as a foundation for constructing performance monitoring models at both the machine and system levels, employing probabilistic automata for the machine level and logistic regression for the system level. The system-level performance monitoring model is constructed to predict a Flow metric that enables the prediction of abnormal behaviors and deviations from production targets. This data-driven approach serves as a foundational ingredient of a system-level digital twin, designed to provide production lines with insights that enable proactive implementation of measures aimed at optimizing overall manufacturing efficiency. Through an industrial test case from the automotive industry, the results demonstrate the capability of performance monitoring, capturing errors within confidence intervals, and establishing predictive cause-and-effect relationships between machines within the production system.

OPC UA Application Study in Oil and Gas Pipeline Network Monitoring Data Forwarding

INTRODUCTION： With the continuous development of oil and gas pipeline network monitoring and control technology, the need for data transmission and communication is becoming more and more prominent. In this context, OPC UA has attracted wide attention. This study aims to explore the application of OPC UA in data forwarding for oil and gas pipeline network monitoring in order to improve the efficiency, reliability and security of data transmission.PURPOSE: The purpose of this study is to evaluate the applicability of OPC UA in oil and gas pipeline network monitoring and to verify its performance in data forwarding through empirical studies. By gaining an in-depth understanding of the characteristics of OPC UA, it aims to provide a more advanced and efficient monitoring data transfer solution for the oil and gas industry.METHOD: The study adopts a combination of field monitoring and laboratory simulation. First, the essential characteristics and requirements of monitoring data in oil and gas pipeline networks were collected. Subsequently, a monitoring system with OPC UA as the communication protocol was established and field tested. In the laboratory environment, data transmission scenarios under different working conditions were simulated, and the performance of OPC UA under different conditions was analyzed.RESULT: The field monitoring results show that the data transmission efficiency is significantly improved by using OPC UA as the communication protocol for data forwarding in oil and gas pipeline network monitoring. Meanwhile, the system performs well in different environments with high reliability and security. The laboratory simulation results further verify the stability and adaptability of OPC UA under complex working conditions.CONCLUSION: OPC UA is an effective communication protocol that can meet the data transmission requirements for oil and gas pipeline network monitoring. Its efficient, reliable, and secure characteristics make it an ideal choice for improving the communication performance of monitoring systems in the oil and gas industry. The empirical results of this study provide reliable technical support for the oil and gas industry in the field of data transmission and a vital reference for the optimization and upgrading of monitoring systems in the future.

A Critical Discussion of Alert Evaluations in the Context of Continuous Glucose Monitoring System Performance.

Many continuous glucose monitoring (CGM) systems provide functionality which alerts users of potentially unwanted glycemic conditions. These alerts can include glucose threshold alerts to call the user's attention to hypoglycemia or hyperglycemia, predictive alerts warning about impeding hypoglycemia or hyperglycemia, and rate-of-change alerts. A recent review identified 129 articles about CGM performance studies, of which approximately 25% contained alert evaluations. In some studies, real alerts were assessed; however, most of these studies retrospectively determined the timing of CGM alerts because not all CGM systems record alerts which necessitates manual documentation. In contrast to assessment of real alerts, retrospective determination allows assessment of a variety of alert settings for all three types of glycemic condition alerts. Based on the literature and the Clinical and Laboratory Standards Institute's POCT05 guideline, two common approaches to threshold alert evaluation were identified, one value-based and one episode-based approach. In this review, a critical discussion of the two approaches, including a post hoc analysis of clinical study data, indicates that the episode-based approach should be preferred over the value-based approach. For predictive alerts, fewer results were found in the literature, and retrospective determination of CGM alert timing is complicated by the prediction algorithms being proprietary information. Rate-of-change alert evaluations were not reported in the identified literature, and POCT05 does not contain recommendations for assessment. A possible approach is discussed including post hoc analysis of clinical study data. To conclude, CGM systems should record alerts, and the episode-based approach to alert evaluation should be preferred.

Sensor Technologies for Hydraulic Valve and System Performance Monitoring: Challenges and Perspectives

AbstractHydraulic fluid power systems are essential for a range of engineering applications such as transportation, heavy industry, and robotics. The scale of the industry is such that hydraulic pumps are estimated to account for 15% of all the energy consumption in the European Union and yet the average efficiency of fluid power systems is only 22%. The digitalization of hydraulic systems offers significant advantages in terms of energy efficiency, performance, reduced maintenance, and automation. However, this requires advances in the integration of smart sensing technologies to provide real‐time feedback on the operation and health of hydraulic components. This review details developing trends in hydraulic fluid power research and provides an overview of progress related to the digitalization of these systems and their integration within an Industry 4.0 framework. The fundamentals of relevant sensor technologies and innovative approaches for integrating sensors into hydraulics systems are discussed. Methods to deliver power to the sensors and associated electronics through harvested pressure ripples are also reviewed. An outlook with respect to future directions in this field is given, including an assessment of the potential for exploiting advanced manufacturing technologies, in particular additive manufacturing, to facilitate successful sensor integration into hydraulic fluid power systems.

Обобщённое неравенство Крамера – Рао в случае совместного пеленгования по азимуту и углу места в условиях сложной электромагнитной обстановки

In this work, a generalized expression is obtained for the Cramer–Rao lower bound in the case of a joint estimation of azimuth and elevation angle in an arbitrary coordinate system in which the vector complex radiation pattern is determined, under conditions of a complex electromagnetic environment, including the presence of noise correlation in spatial channels and differences in its intensity. A theorem is formulated for the Fisher information of joint estimates of azimuth and elevation angle in the case of a multi-channel detector-direction finder with an antenna system described in the selected coordinate system by a vector complex radiation pattern. Dependences of the root-mean-square error of direction finding in azimuth and elevation on the signal-to-noise ratio and true directions to the radio source are obtained, calculated using known and generalized expressions for the Cramer–Rao lower bound. The condition for the applicability of the existing and proposed in the article expression for the Fisher information matrix is obtained. The concept of the “energy” center of the antenna system is given. To confirm the reliability of the obtained generalized expressions for the lower bound of the dispersion of the Cramer–Rao inequality, statistical modeling is carried out. The use of the obtained expressions in practice will allow the most optimal synthesis of antenna devices depending on the structure and characteristics of the direction finder antenna system, the number of antennas and the characteristics of the radio receiving path. Generalized expressions for the lower Cramer–Rao bound are the foundation for organizing the operation of intelligent radio monitoring systems, allowing for a well-founded choice of the optimal antenna array structure that provides the required direction-finding efficiency.

Review: update on performance assessment and monitoring systems for ophthalmologists

Review: update on performance assessment and monitoring systems for ophthalmologists

Low-Power and Wireless Communication Research on Underground Displacement Three-Dimensional Monitoring System.

Underground displacement monitoring is a crucial means of preventing geological disasters. Compared to existing one-dimensional methods (measuring only horizontal or vertical displacement), the underground displacement three-dimensional measurement method and monitoring system proposed by the author's research team can more accurately reflect the internal movement of rock and soil mass, thereby improving the timeliness and accuracy of geological disaster prediction. To ensure the reliability and long-term operation of the underground displacement three-dimensional monitoring system, this article further introduces low-power design theory and Bluetooth wireless transmission technology into the system. By optimizing the power consumption of each sensing unit, the current during the sleep period of a single sensing unit is reduced to only 0.09 mA. Dynamic power management technology is employed to minimize power consumption during each detection cycle. By using Bluetooth wireless transmission technology, the original wired communication of the system is upgraded to a relay-type wireless network communication, effectively solving the problem of the entire sensing array's operation being affected when a single sensing unit is damaged. These optimized designs not only maintain monitoring accuracy (horizontal and vertical displacement errors not exceeding 1 mm) but also enable the monitoring system to operate stably for an extended period under harsh weather conditions.

Real-Time Monitoring of Photovoltaic Systems and Control of Electricity Supply for Smart Micro Grid-PV using IoT

This paper aims to develop a photovoltaic (PV) performance monitoring system applied on a micro scale using the Internet of Things (IoT). Previous monitoring systems had limitations in platform flexibility, low-cost devices, hardware complexity, and stability of the data transfer process. For this reason, this research proposes an IoT architecture that uses Arduino devices, mini WIFI and an open-source platform, so that it can be easily developed further. This research also develops innovations in controlling the use of electrical energy sources from PV and utility networks. This monitoring system is applied to PV installations with a capacity of 1KW which is capable of monitoring electrical data in the form of current, voltage, power, energy and frequency obtained from PV panels, batteries, loads and electrical utilities. Monitoring data is displayed in a visual form that can be accessed via web-based and mobile applications. This research has developed an innovation in controlling the use of electrical energy sources from PV and Utility networks by using several sensors as parameters to determine the right time and condition in controlling the use of electrical resources.

Interface-Based Loan Fund Performance Monitoring And Evaluation System At BKM Ngesrep Semarang

The monitoring and evaluation system is a routine process of collecting data and measuring progress on program objectives/monitoring changes, which focuses on processes and outputs. Monitoring involves accounting for what is done. Monitoring involves observing the quality of the services provided while evaluation is the use of social research methods to systematically investigate program effectiveness/assess the program's contribution to change (goal/objective) and assess the need for improvement, continuation or expansion of the program (recommendations). The first aim of this system is to be able to process data efficiently and accurately, the second aim is to assist the financial management unit (UPK) in inputting loan fund installments to make it easier to process data so as not to make calculation errors and record errors and to improve services to Community Self-Help Groups (KSM) better as borrowers, the third objective is to facilitate monitoring of loan fund evaluation which can be monitored and evaluated at any time, both the rate of return of loan funds and the level of loan fund congestion. In this system, the interface-based monitoring and evaluation model is one of the services provided by the operating system as a means of interaction between the user and the operating system. The interface is an operating system component that comes into direct contact with the user. This application was created using Microsoft Visual Basic 6.0 and a Client Server-based MySQL database.

Transparency and Monitoring of Public Procurement Contract Performance

This study analyzes the monitoring of public procurement contracts’ performance in six countries under EU public procurement rules: Finland, Portugal, Slovenia, Italy, Hungary, and Serbia. Through an in-depth comparative analysis, we explore the nexus between perceived corruption in these countries and the contract performance monitoring systems established or in the making. The analysis centers on four key aspects: the organizational framework, the redress system, the IT infrastructure, and the level of data publicity in each country’s procurement landscape. Expert evaluations conducted by national specialists unveil which countries pay less attention to public contract performance monitoring and transparency. Our findings indicate that countries facing higher corruption rates tend to place greater emphasis on transparency and contract performance monitoring. Moreover, countries greatly differ in their organizational setup, objectives, and monitoring tools, including IT adoption. The insights derived from this study can influence policy and reform efforts focused on the contract phase of public procurement, leading to a more accountable and efficient procurement landscape across Europe.