Monitoring Management System Research Articles

Spatio-temporal envolutional graph neural network for traffic flow prediction in UAV-based urban traffic monitoring system

With the advancement of modern UAV technology, UAVs have become integral to creating traffic management monitoring systems. Additionally, UAV-based traffic monitoring systems can predict traffic flow by integrating machine learning methods. Specifically, traffic flow data contains both spatial and temporal information, which can be effectively processed by graph neural networks (GNNs). However, GNNs often face the challenge of oversmoothing, which hinders their ability to capture complex structures in the data. The Spatio-Temporal Graph Ordinary Differential Equations (STGODE) model addresses this issue by introducing Neural Ordinary Differential Equations (NODEs) to construct deeper GNNs. Despite this, STGODE relies on initially predefined semantic neighborhood matrices, which do not adapt well to the dynamic nature of traffic information. To overcome this limitation, we propose an evolutionary graph neural network for traffic prediction, capable of continuously updating the semantic adjacency matrix throughout the training process. This dynamic evolution of the semantic adjacency matrix allows it to adapt to the features and semantic relations of the current data, enhancing its ability to capture the complexity and variability of traffic patterns. We validate our approach through experiments on several real-world datasets, demonstrating that our method outperforms state-of-the-art benchmarks.

PLTS/ARAS-based financing risk resilience capability evaluation for fisheries enterprise: A case study of green transformation and upgrading

Clearly delineating the key capabilities of organizational resilience for fisheries enterprises holds significant practical implications, as it can mitigate financing risks and foster the sustainable development of the fisheries industry. Based on the “dynamic capabilities perspective”, this study constructs an analytical framework for the resilience capabilities of fisheries enterprises against financing risk. A hybrid method comprising the probabilistic linguistic term set, the decision-making trial and evaluation laboratory, and the additive ratio assessment is applied to a case study of Homey Group, examining the diverse pathways through which financing risk forms and impacts outcomes. The main findings are: (1) In the comprehensive assessment of the role of resilience capabilities in addressing the “Risk-Seeking-Decline Type” financing risk factors, market diversification and sustainable practices are accorded higher weights surpassing financial resources as the two most value-enhancing resilience capabilities. Enterprises characterized by a “Risk-Seeking-Loss Type” profile tend to assign higher weights to market diversification and technological infrastructure when evaluating financing risk resilience capabilities. (2) Regarding the key capabilities of organizational resilience, Homey Group possesses a weak risk management system for monitoring and evaluating significant risks and implementing control activities. (3) With regards to suggestions for improvement, it is advisable to delegate oversight of the risk identification process to a designated risk committee or specialists in risk management. The conclusions contribute to a deeper understanding of the nature and mechanism of resilience capabilities for fisheries enterprises and provides implications for risk management and sustainable development.

The Role of Monitoring and Evaluation and Project Implementation Management System for Non-Profit Project Performance in Developing Countries

Abstract This study examines the relationship between monitoring and evaluation (M&E), project implementation management system (PIMS) for financial monitoring, and project performance within the framework of the resource-based view (RBV), dynamic capabilities, and knowledge management theory. It focuses on non-profit projects in a developing context, particularly in countries such as Bosnia and Herzegovina (BiH). Developmental assistance and non-profit projects have an important role to play in the economic performance of developing countries. The research highlights the significance of understanding factors influencing project performance in non-profit projects in developing countries such as BiH. The findings indicate that both M&E and PIMS for financial monitoring significantly influence three key knowledge management processes - knowledge internalization, knowledge accumulation, and knowledge transfer and integration, which in turn positively influence project performance. The study underscores the importance of synergy between M&E, PIMS, and knowledge management for enhancing project performance, offering valuable insights for policymakers, donors, the international community, and academia.

Development of a quality management monitoring system for social and pedagogical educational programs

This paper underscores the pressing need to address educational challenges in Kazakhstan. The government's educational system development policy seeks to comprehensively modernize education across all levels emphasizing innovative teaching methods and tools. A crucial responsibility that necessitates the development of effective procedures and methods is ensuring the efficacy of educational programmes. This research employs both theoretical methods (such as analysis, generalization and classification) and empirical methods (including surveys and mathematical statistics) to investigate this topic. The statistical significance of the results can be determined by applying the student's t-test after the survey data has undergone mathematical processing. This rigorous approach adds credibility to the findings and enhances the reliability of the research. This paper posits that internal monitoring of educational programs yields significant insights into educational quality. This approach evaluates indicators related to student satisfaction and learning outcomes, recognizing that program quality is dynamic and influenced by evolving educational needs, teacher competence and material and technical infrastructure. In a nutshell, educational program monitoring assumes a pivotal role in enhancing the quality of education in Kazakhstan. This monitoring system contributes to continuous efforts to modernize and align the education system with changing demands and standards by evaluating learning results and student satisfaction. This provides valuable information for programme enhancement.

An intelligent agriculture management system for rainfall prediction and fruit health monitoring

Contrary to popular belief, agriculture is becoming more data-driven with artificial intelligence and Internet-of-Things (IoT) playing crucial roles. In this paper, the integrated processing executed by various sensors combined as an IoT pack and driving an intelligent agriculture management system designed for rainfall prediction and fruit health monitoring have been included. The proposed system based on an AI aided model makes use of a Convolutional Neural Network (CNN) with long short-term memory (LSTM) layer for rainfall prediction and a CNN with SoftMax layer along with a few deep learning pre-trained models for fruit health monitoring. Another model that works as a combined rainfall predictor and fruit health recognizer is designed using a CNN + LSTM and a multi-head self-attention mechanism which proves to be effective. The entire system is cloud resident and available for use through an application.

도시재생사업의 성과측정에 관한 연구

The urban regeneration project started under the Park Geun-hye administration and was promoted more heavily as a New Deal project under the Moon Jae-in administration. However, as the urban regeneration project progressed, problems arose that residents could not feel due to poor implementation performance and low execution ability. Accordingly, in this study, in order to establish and achieve the goals of the urban regeneration revitalization plan, a management system and performance indicators for monitoring, evaluation, and feedback are presented to systematically and comprehensively manage everything from plan establishment to performance and effect derivation, and a resident satisfaction survey to measure performance. We conducted an investigation. In order to accurately measure performance, the ‘Comprehensive Performance Index’ presented by the central government was used as a common indicator, and the ‘Local Government Performance Index’ was comprehensively analyzed and used as an auxiliary indicator. In this study, research was conducted targeting the ‘Jeonju Station Area Urban Regeneration Area’, which is currently under construction, to select indicators for performance measurement, and practical data was presented in relation to the research method.

VEHICLE IDENTIFICATION IN PARKING AREAS USING ADAPTIVE BRIGHTNESS THRESHOLDING

The problem of parking systems on the street is a classic problem that occurs from year to year, manysolutions are offered in solving the parking problem on the street. The problem is not only related to trafficjams due to in and out of vehicles from the parking spaces but also the parking management issues becomepolemic at this time. A prototype of parking management monitoring system tries to provide solution inmanaging parking by using image processing based smart camera. In a prototype the system test performedon day and night conditions, to anticipate the very contrast difference intensity of pixels during the day or night so as to develop vehicle detection program using adaptive brightness thresholding. The results showthat the program has been running quite well to identify vehicles during day and night timeframe

BMMS: Bus Monitoring Management System

BMMS: Bus Monitoring Management System

Analysis of Sindh School Monitoring System Smartphone App of Government Schools of Sindh

The attendance of employees is crucial in both public and private organizations as it indicates their dedication. In the schools of Government of Sindh the monitoring of attendance of teachers has become increasingly challenging, for that, the Government of Sindh has introduced an android based smart phone app called the Sindh School Monitoring Management System (SSMS app) in April 2016 to collect, analyze and disseminate the real-time data regarding school, teachers and students. The app was implemented in 15 districts in the first phase and has since been expanded to cover the entire province, resulting in improved teachers attendance, education quality and school monitoring at government schools. Previously, attendance was tracked manually, which was not secured and had flaws such as teachers not adhering to policy for signature, timing and signing in advance. While the SSMS app has improved the performance, it still faces implementation and design challenges. This research examines the SSMS app in detail, highlighting its weaknesses and aiming to improve its efficiency through a questionnaire designed with input from experts. An analysis is presented based on the feedback of monitoring assistants (MAs) on the indicators such as teacher’s attendance, punctuality, multi modal representation of SSMS, monitoring, data collection, data loading, data fetching.

ADS-B overlapping signals separation based on minimum dispersion criterion

As a new generation of air traffic management (ATM) monitoring system, the airborne automatic dependent surveillance-broadcast (ADS-B) transmitters will broadcast their position, speed, and other information to enhance the efficiency and safety of air traffic. However, due to the asynchronous nature of ADS-B transmitters broadcasting their information on the same frequency, it is inevitable for multiple ADS-B signals from different aircraft to overlap. This paper proposes an ADS-B signal separation algorithm based on the minimum dispersion criterion (MD), which takes advantage of the non-Gaussian distribution properties exhibited by ADS-B signals. Firstly, the non-Gaussian distribution properties of overlapping ADS-B signals are illustrated by analyzing their probability density distribution and kurtosis. Secondly, the separation problem is formulated as a non-convex optimization problem based on the minimum dispersion criterion. Finally, the alternating direction method of multipliers (ADMM) is employed to tackle the formulated optimization problem. Simulations will demonstrate the effectiveness of the proposed algorithm.

Current Stock Monitoring System with Expiry Alerts

The main objective of this project is manage a stock for a Developing a “CURRENT STOCK MONITORING SYSTEM WITH EXPIRY ALERTS” is illustrates the designing and implementation of a Current Stock Monitoring Management System with expiry alert system. The primary aim of is to improve accuracy and enhance safety and efficiency in the pharmaceutical store. Today management is one of the most essential features of all form. The Management provides sophistication toper form any kind of task in a particular form. This is pharmacy management system; it is used to manage most pharmacy related activities in the pharmacy. computerized system designed for user to manage the stock inventory and monitoring the stock facility. The stand alone stock inventory system provides alert of expire date and minimum quantity of each product and also searching algorithm technique applied in this system. Are search and analysis on the current system and searching technique was done to get better understanding of the system. The RAD methodology was used in this project development implements iterative development which is suitable for standalone applications requirements that changes from time to time. Testing is done every phase of the development life cycle to make sure that the system working properly.

Remote fault detection and location of power fiber optic cable based on a logistic regression model

Abstract The current fiber optic communication network presents the characteristics of network scale, complexity, and efficiency, and the use of traditional means for the maintenance of power fiber optic cable has been greatly limited. In this paper, based on the characteristics of simple structure, convenient construction, strong randomness, strong sequence autocorrelation, and good iterative performance of chaos theory in a logistic regression model, a logistic-based remote fault detection and location system for power fiber optic cables is proposed. The fault location test is carried out through with TMS200 series fiber optic cable automatic monitoring management system and GIS method. The fault location error of the logistic-based fault detection method is less than ±3m, that of the GIS method is less than ±10m, and that of the TMS200 series cable automatic monitoring and management system is less than ±15. The comparison shows that this paper’s fault detection and location system is more accurate and can help maintenance personnel have a faster and more comprehensive understanding of the line situation. Realize the rapid repair work of faults, which provides great help to maintain the fiber optic cable lines.

An In-Depth Analysis of Smart Healthcare Monitoring Systems for Humans Based on IoT

Smart healthcare monitoring systems make use of IoT, the most recent technology. As a result, IoT incorporates one of its most critical applications, the health monitoring and control system. Within those systems, individuals commonly use pulse rate sensing devices, ECG sensor systems, and blood pressure sensor with various embedded systems to collect observations from the identification modules and send them to a database machine so that records can be transferred with the patient and the physician in an Android app. This investigation makes it easier to imagine how IoT could be used in difficult medical procedures. The remote health monitoring management system (HMS) is a key IoT app that allows users to connect to smart sensors, people, healthcare professionals, networks, and other connected devices. Clinicians can now constantly monitor their own patients from afar thanks to the tried method, the internet of things.

Modeling of Distributed Control System for Network of Mineral Water Wells

The article is devoted to solving the problem of designing a distributed control system for a network of production wells on the example of mineral water deposits in the Caucasus Mineral Waters region, Russia. The purpose was to determine the set of parameters of the control system to ensure technologically effective and safe operating modes of mineral water deposits. A mathematical model of the deposit was developed taking into account the given configuration and production rate of the network of the wells. The detailed algorithm is presented for designing the control system under consideration based on the frequency concept of analysis and synthesis for distributed control systems. The experimental tests and model validation were performed at the production wells facility of “Narzan”, Kislovodsk, Russia. The results of modeling and field experiments confirmed the adequacy of the mathematical model and the effectiveness of the proposed algorithm. The authors came to the conclusion that the adapted mathematical model can be used to create a regional automated field cluster management system for monitoring, operational management and forecasting the nature of real hydrogeological processes and ensuring their stability.

Management Program Implementation of Performance Monitoring and Control Systems Benefits as Quality Control and Teacher Competence in Banyuwangi District

Teachers who get certification are entitled to a professional allowance. The government hopes that with this allowance, teachers can improve their welfare and performance. But unexpectedly, after receiving the professional allowance, teachers are not compensated with good quality and competence. Related to this, the Banyuwangi Regency government made improvements through the Education Office Branch. A Management System for Monitoring and Control of Performance and Allowances (SRITANJUNG) management program was launched to control teacher quality and competency. This study aims to build an implementation model for the Sritanjung Program as a quality control and appropriate teacher competency. Factors that support or inhibit will be sought and try to find a solution. This study uses a descriptive qualitative method by collecting data in the field through interviews and questionnaires to all parties involved. The results showed that 1) the implementation of the program as a quality control and teacher competence in the process there are problems with legality, attitude and character of supervisors and principals, target targets/teachers, and tools. While the supporting factors for program implementation as control are: (a) the existence of implementer intentions and agreements, (b) the existence of a legal umbrella, (c) application support, and (d) the availability of implementor resources that are ready. While the inhibiting factors are (a) policy; assignment legality for school supervisors and principals, (b) tools; teacher's computer equipment, frequent errors, incomplete features, and internet signal, (c) systems and processes; lack of clear information about the program, and (d) from human resources; not all teachers are familiar with applications, honesty of information from teachers, weak mastery of information technology and computers, allocation of allowances and busyness of teachers. Meanwhile, the program implementation model for quality control and teacher competence that has been built and is appropriate is the Co-Han Model, which is presumably the initial solution. The Co-Han model is a combination of the old program implementation model and some elements of the COCO control model. This new model involves elements of attitude and characteristics of implementers and targets. Involving the elements of attitude and character in the form of goals, commitment, and abilities is considered very important. With a good attitude and character, it is hoped that the program can be implemented properly too, so that the goals will be easily achieved. The combination of management as a system, as well as commitment and ability as a character will greatly influence program objectives. This is considered a very effective, necessary and new combination in a program implementation as control.

Modeling crop yield using NDVI-derived VGM metrics across different climatic regions in the USA.

An accurate, cost-efficient, and early crop yield projection is a national and global necessity. This study is aimed to achieve the national demands by proposing crop yield estimation models on the Google Earth Engine (GEE) platform. This study directly used dynamic crop phenology metrics to model soybean crop yield by considering climatic regions in the USA (e.g., Central, East, Northeast, South, Southeast, and West North Central regions). We modeled soybean yields with vegetative growth metrics (VGMs) of NDVI narrated as VGM70 (avg. NDVI of 70days from the emergence), VGM85 (avg. NDVI of 85days from the emergence), VGM98T (total NDVI of 98days from the emergence), VGM120 (avg. NDVI of 120days from the emergence), VGMmean (avg. NDVI of the growth season), VGMmax (maximum NDVI of the growth season), and climatic factors (i.e., daytime surface temperature: DST, night-time surface temperature: NST, and precipitation) from 2000 to 2019. This study further explored individual predictors and a combination of predictors in modeling crop yield for diverse climatic regions. Therefore, we proposed six crop yield linear models for each of the climatic divisions, and these models are then compared with support vector machine (SVM) models. All models showed reliable predictability based on adjusted R-square, normalized root mean square error (NRMSE), normalized mean prediction error (NMPE) parameters, and a p-value of less than 0.001.The impact of the independent predictor in the best crop yield models is discussed based on the regression weights (beta weight: β), and, the VGMmax is identified as the significant predictor in crop yield modeling for different climatic regions. Overall, this study will help the national agricultural management system for better monitoring and forecasting of soybean yield to support and manage soybean production.

Development using the Rapid Application Model of peTrace: Peter’s Poultry Supply Sales and Monitoring Management System

The poultry industry includes other support industries such as feed production and distribution, veterinary and poultry equipment production and distribution, meat and egg processing, marketing and distribution, and so on. Poultry production in the tropics. The poultry supply business is not prevalent in the province of Oriental Mindoro, that has a land area of 588,350 ha that supplies agriculture crops and livestock production, in addition to 286 registered business names, the plurality of which are linked to poultry supply. And one of the towns in Oriental Mindoro is recognized for producing agriculture and aquaculture. Rapid Application Method (RAD) is a software development methodology that emphasizes rapid prototyping through design. This type of testing modifies the software system before it is implemented. And Alpha testing was carried out by the Information Technology Practitioner. The system peTrace was ready for evaluation after several design and functionality issues were resolved. Purposive sampling was applied by the proponents this is to identify the 50 respondents so that the evaluators could have an accurate evaluation result. Information Technology Practitioners, store owners, staff, and clients were among those who responded. Owner, staff utilized the peTrace several times, testing its functionalities and verifying its usability. The proponents adapted the evaluation questionnaire using the ISO 25010 software quality criteria. To modify the five assessment criteria, ISO 25010 quality software standards were used. According to the assessment findings, peTrace is helpful and performs as predicted in terms of functional appropriateness (4.90), performance efficiency (4.85), usability (4.83), security (4.83), and maintainability (4.82). The peTrace system is broad in design, simple to maintain, and adaptable to any portable device independent of operating system, making it suited for any local Feed Store. For future growth, the assessors advise using real-time analysis. A good system will offer continuous monitoring with few, if any delays.

FPGA-Based battery management system for real-time monitoring and instantaneous SOC prediction

Battery management systems (BMS) are becoming essential for all types of electric vehicles using battery packs. Various factors, such as battery temperature and balance, directly affect the life, safety, and efficiency of batteries used in vehicles. For security and robustness, these factors should be monitored and adjusted instantly. Today, battery management systems are constantly being developed using different production methods and algorithms. In the studies, calculations are made by measuring parameters such as temperature, current, current balance, load status, and health status of the battery cells, and the control of the battery group is provided with these calculations. Instant and continuous measurement and processing of all these data and the creation of a control algorithm according to the calculation result are possible with the use of powerful processors. FPGA is a processor that can provide the speed and functionality required for BMS. In the battery management system, the FPGA is responsible for receiving and processing all signals from the battery cells and producing results. It instantly processes the data from temperature, current, and voltage sensors and applies the control stage required for balancing. In addition, the charge and discharge capacity of the battery is calculated by instantly measuring the state of charge (SOC). SOC is of great importance in the battery management system to ensure the safety of the battery pack. Therefore, the SOC needs to be estimated accurately and in real-time. Thanks to its parallel processing capability, the FPGA can simultaneously read data from the sensors and perform related calculations. In this study, a versatile system design with real-time, high computational speed for BMS was carried out on FPGA. The voltage and current of an experimental battery based on the embedded system were monitored in real time in a simulation environment. Experimental results show that the instantaneous SOC estimation is successful, and the system returns instant results to the incoming sensor data. The use of FPGA as a management unit will provide significant advantages in BMS with its high operating speed, real-time monitoring, low power consumption, and re-programmability.

Sports health monitoring management system based on artificial intelligence algorithm

With the improvement of people's material living standards, more and more people start to pay attention to health issues. This paper takes the health field as the main research object, and discusses the current development and status quo of the health field. Through literature review, it is found that the current health field mainly focuses on the single monitoring of a certain organ or body function, and there are limitations in systematic health monitoring research, and most of the research stays at the stage of human body monitoring. Therefore, this paper intends to design a sports health monitoring and management system based on artificial intelligence. The system is mainly divided into a body temperature monitoring module, a blood pressure monitoring module and an exercise monitoring module, through which the user's health data is monitored. In order to ensure the practicability of the system, this paper selects three common life states in daily life for experimental testing, namely exercise state, rest state and sick state. The experimental test results show that each monitoring module can operate correctly and normally under three different states. The lowest temperature was 36.5° and the highest temperature was 37.1° under the exercise state. The lowest blood pressure is 70 in the resting state, and the highest blood pressure is 80. In the sick state, the maximum value of motor threshold is 0.2, the minimum value is 0.1, and the threshold difference is 0.1. Each module reads and backs up relevant data, and sends it to the platform for intelligent analysis. The platform will analyze and compare the data of different modules at the same time, judge the health status of the user at that time, choose whether to issue a health alert for the user, and finally complete the entire system process of the health monitoring management system. This proves that the sports health monitoring management system based on artificial intelligence algorithm designed in this paper is effective and feasible.

Construction project management monitoring system using s-curve

Every construction project generally has a specific implementation plan and implementation schedule: when to start the implementation of the project, when to complete the project, how to do the project, and how to provide resources. Making a plan for a construction project always refers to the estimates that exist when the scheduled development plan is made. Therefore, problems can arise if there is a mismatch between the plan that has been made and its implementation. With the limited resources in the company, thorough and good planning is needed as a guide in carrying out the project to use resources efficiently and organize work to be completed according to the time specified in the contract. To achieve this goal, the manager controls the project with an s-curve by comparing the actual curve graph with the plan curve graph. The method to be used in monitoring the progress of construction projects is the s-curve. The use of the s-curve method is very supportive because it is suitable for monitoring project progress in terms of performance, cost, and timeliness of project work. The results of this study show that the construction project management monitoring website using the s-curve can create a cost budget plan that follows the contract document, a schedule plan, a weekly project report, and a project report recapitulation. The output results are displayed in the form of a Gantt Chart, and S-curves are completed with plan curve lines and realization curve lines. This project management monitoring website has a multi-user feature so that more than one user can use it.