Implementation Of Monitoring System Research Articles

Implementation of Detection and Monitoring System of Illegal Gamble Website

Implementation of Detection and Monitoring System of Illegal Gamble Website

IOT Based Food Minitoring System

Abstract: The Internet of Things (IoT) has emerged as a transformative technology with wide-ranging applications, and one of its promising domains is in the field of food monitoring systems. This abstract introduces an innovative IoT-based Food Monitoring System designed to enhance food quality assurance and reduce waste in the supply chain. The proposed system integrates various IoT components, including sensors, actuators, and communication devices, to create a comprehensive solution for monitoring the entire lifecycle of food products. Key objectives of the system include real-time tracking of food conditions, ensuring compliance with quality standards, and minimizing the environmental impact associated with food waste. The implementation of this IoT-based Food Monitoring System offers several benefits, including improved food quality, reduced waste, increased operational efficiency, and enhanced consumer satisfaction. By leveraging the capabilities of IoT, this system addresses the challenges associated with maintaining food quality and safety while contributing to the overall sustainability of the food industry

Design and Implementation of Water PH Level and Turbidity Monitoring System

Abstract: Building collapses have become a distressing and recurring issue in Nigeria, necessitating urgent action to mitigate their occurrence. This paper introduces an innovative approach to address this challenge by developing an Automated Structural Health Monitoring System (ASHMS) utilizing a mobile app. Focusing on major cities like Lagos and Abuja, the proposed system employs strategically placed sensors to gather data from various structural elements of buildings. The collected information, encompassing seismic activity, vibrations, bending moments, shear forces, and other key parameters, is wirelessly transmitted to the cloud where it can then be accessed and visualized using mobile app. The system offers real-time insights into the structural integrity of buildings and provides early warnings, thereby contributing significantly to reducing the risk of building collapses. Key findings show that when incorporated into an automated Structural Health Monitoring (SHM) system, the user's mobile app offers essential structural insights, capturing values such as a 0.5-unit vibration level, 20 units of shear force, 50 units of bending moment, and an 89-degree vertical wall angle. The app's userfriendly interface improves the effectiveness of monitoring and overseeing structural health, in line with the overarching objective of promoting safety in construction practices

RETRACTION: Reduced self-harm on acute mental health wards following the implementation of a vision-based patient monitoring system: Evidence from five NHS trusts.

M. Kekic, A. Rose, C. Baker, and D. Bayley, 'Reduced self-harm on acute mental health wards following the implementation of a vision-based patient monitoring system: Evidence from five NHS trusts,' Journal of Psychiatric and Mental Health Nursing (Early View), https://doi.org/10.1111/jpm.13036. The above article, published online on 05 March 2024 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor-in-Chief, Hugh McKenna, and John Wiley & Sons Ltd. The retraction has been agreed due to an undisclosed conflict of interest by the authors, which was reported in a complaint by a third party. Following an investigation, it was confirmed that, while the authors reported their employment status with Oxehealth Ltd. in their personal affiliations section, they failed to do so in a conflict of interest statement as required by the journal. Because the journal uses a double-blind peer review process, neither the names of the authors nor their affiliations were visible to the reviewers and editors during evaluation of the manuscript. Had an employment status disclosure been made clear in a conflict-of-interest statement in accordance with the journal's submission guidelines, the Editor-in-Chief and all associate editors would have considered author employment by Oxehealth Ltd., the developer of the technology evaluated by the authors, as a major competing interest and would have rejected the manuscript without peer review. Therefore, the article must be retracted. Dr. Kekic disagrees with the retraction, on behalf of all the authors.

Strain Virtual Sensing Applied to Industrial Presses for Fatigue Monitoring.

The techniques that allow one to estimate measurements at the unsensed points of a system are known as virtual sensing. These techniques are useful for the implementation of condition monitoring systems in industrial equipment subjected to high cyclic loads that can cause fatigue damage, such as industrial presses. In this article, three different virtual sensing algorithms for strain estimation are tested using real measurement data obtained from a scaled bed press prototype: two deterministic algorithms (Direct Strain Observer and Least-Squares Strain Estimation) and one stochastic algorithm (Static Strain Kalman Filter). The prototype is subjected to cyclic loads using a hydraulic fatigue testing machine and is sensorized with strain gauges. Results show that sufficiently accurate strain estimations can be obtained using virtual sensing algorithms and a reduced number of strain gauges as input sensors when the monitored structure is subjected to static and quasi-static loads. Results also show that is possible to estimate the initiation of fatigue cracks at critical points of a structural component using virtual strain sensors.

A dilute-and-inject liquid-gas chromatography-mass spectrometry method for the analysis of sixteen polycyclic aromatic hydrocarbons in extra-virgin olive oil

BackgroundPolycyclic aromatic hydrocarbons (PAHs) represent a diverse group of organic compounds characterized by the fusion of two or more benzene rings arranged in various structural forms. Due to their harmful effects on human health, it is essential to implement monitoring systems and preventive measures to regulate human exposure. Given the affinity of PAHs for lipids, extensive research has been focused on their presence in vegetable oils. This study aimed to develop an on-line liquid-gas chromatography (LC-GC) method (using tandem mass spectrometry) with minimized solvent consumption for the determination of 16 PAHs in extra-virgin olive oil (EVOO). ResultsA side-by-side comparison of the selected-ion-monitoring and the pseudo multiple-reaction-monitoring (p-MRM) acquisition modes was performed, in terms of specificity and detectability. The results obtained using the p-MRM mode were superior, and for this reason it was selected. The method was linear over the concentration range 1–200 μg kg−1 (except in five cases, over 2–200 and 5–200 μg kg−1 ranges). Accuracy (at the 2 μg kg−1 and 20 μg kg−1 concentration levels) was in the 86.9–109.3 % range, with an RSD <10 %. Intra-day and inter-day precision (at 2 μg kg−1 and 20 μg kg−1 concentration levels) were in the 1.2–9.7 % and 3.2–10.8 % ranges, respectively. For all the PAHs, a negative matrix effect was observed. Three out of sixteen PAHs were detected in three EVOOs (among ten samples), albeit at the low ppb level. Limits of quantification were satisfactory in relation to EU legislation on the presence of PAHs in vegetable oils. SignificanceA dilute-and-inject LC-GC-tandem mass spectrometry method is herein proposed fulfilling EU legislation requirements; sample preparation was very simple, inasmuch that it involved only a dilution step, thus avoiding extraction, clean-up, and thus a high consumption of organic solvents. In fact, considering both oil dilution and the LC mobile phase, less than 8 mL of solvents were used.

Smart Temperature and Humidity Tracker

Smart Temperature and Humidity Tracker

Enhancing deadwood reporting for forest ecosystems: Bridge equations to convert deadwood measured at any diameter threshold to reference diameters

National as well as international requirements have led to an increased need to quantify deadwood stocks in forest ecosystems given their important role not only in terms of carbon storage and regulation of the carbon cycle but also as biodiversity refugia. However, differences in definitions and field monitoring as well as gaps in existing data on deadwood mean that comparisons among countries and retrospective analyses are difficult. In this research, we propose two potential approaches to solve the most common gaps in forest deadwood monitoring. First, we develop bridging functions capable of converting deadwood measurements with a specific reference diameter to 7.5 cm (minimum diameter value in Spain) and 10.0 cm (the most common minimum value for international statistics) diameters for the main forest types while also addressing the effect of raising the minimum measurable size on the quantification of deadwood. Furthermore, we aim to calculate the ratios between the amount of standing deadwood, the most common indicator monitored in National Forest Inventories, and the entire deadwood pool as a proxy for estimating complete deadwood stocks when data are not available. For this objective, we use information obtained from the Spanish National Forest Inventory, linear models and 10-fold cross-validation. We estimate the percentage of deadwood omitted when the minimum deadwood size is increased for the main eight forest types in Spain as well as for the entire country, using two different approaches. The ratio between the amount of standing deadwood and the entire deadwood pool ranged between 0.14 and 0.45 depending on the forest type. The lowest values of this ratio were found in Open woodlands and the largest in Mediterranean conifers. The validation statistics (R2 ranging from 0.82 in Evergreen broadleaves to 0.97 in Macaronesian broadleaves) indicate that the bridging functions we propose are robust and accurate. However, the ratios between the amount of standing deadwood and the entire deadwood pool performed poorer (R2 ranging from 0.26 in Macaronesian conifers to 0.65 in Macaronesian broadleaves) and led to an overestimation of the total stocks. Our results are of value not only for the purposes of comparison and harmonization but also for the implementation of new forest monitoring systems.

Implementation of an Effective Course Registration Credit Unit Monitoring System

Automation of course registration is a major breakthrough with the advancement in information technology. Registration processes that take longer time most times eating deep into the semester and with laborious inputs from registration officers have evolved into a seamless and easy process due to the development of robust information systems. An information system requires accurate data for it to give a reliable output, so it is of the essence to be able to input accurate credit units of courses to the course registration system. Computing the credit units of courses by students and course registration officers is mostly manual, in this research, automation of this vital pre-process is implemented. The system is built using java programming language which makes it robust, simple and easy to use. It is a credit unit calculator that does not require being online before it can either be deployed or used. The system prompts the user to enter level, the semester, maximum credit load for the semester and their corresponding credit units. At each execution of the system the courses, corresponding credit units, total credit load for the semester is displayed provided the total credit units entered is not greater than the credit load for the semester, otherwise a prompt displays the excess credit units. Subsequent research can enhance the system to be able to send the output of the pre-registration document from the student directly to the registration officer, and also there should be a module embedded to the system that will enable the registration officer to perform the pre-registration document verification. A module to check double registration and determination if a given course is either first or second semester can also be added.

Implementation of an Effective Course Registration Credit Unit Monitoring System

Automation of course registration is a major breakthrough with the advancement in information technology. Registration processes that take longer time most times eating deep into the semester and with laborious inputs from registration officers have evolved into a seamless and easy process due to the development of robust information systems. An information system requires accurate data for it to give a reliable output, so it is of the essence to be able to input accurate credit units of courses to the course registration system. Computing the credit units of courses by students and course registration officers is mostly manual, in this research, automation of this vital pre-process is implemented. The system is built using java programming language which makes it robust, simple and easy to use. It is a credit unit calculator that does not require being online before it can either be deployed or used. The system prompts the user to enter level, the semester, maximum credit load for the semester and their corresponding credit units. At each execution of the system the courses, corresponding credit units, total credit load for the semester is displayed provided the total credit units entered is not greater than the credit load for the semester, otherwise a prompt displays the excess credit units. Subsequent research can enhance the system to be able to send the output of the pre-registration document from the student directly to the registration officer, and also there should be a module embedded to the system that will enable the registration officer to perform the pre-registration document verification. A module to check double registration and determination if a given course is either first or second semester can also be added

Post-discharge surgical site infection surveillance using patient smartphones: a single-centre experience in cardiac surgery

Background/Aims Surgical site infections following cardiac surgery pose significant risks and financial burdens to both patients and healthcare systems. This study aimed to explore the implementation and outcomes of a novel surgical wound monitoring system using patient smartphones for post-discharge surveillance. Methods The study was conducted at a London-based cardiothoracic tertiary referral centre, where 1358 patients undergoing cardiac surgery between January 2021 and March 2023 were enrolled onto the surgical wound monitoring system. Data were collected from the National Cardiac Audit Programme dataset, the monitoring system and Hospital Episode Statistics data. Comparisons between patients who did or did not respond to surveillance requests were performed. A nested confirmatory analysis assessed antibiotics reported by patients through the digital route compared with antibiotics given by GPs or in outpatients. Results The overall response rate for surgical wound monitoring using patient smartphones was 86.6%. Patients who were female, from areas of higher deprivation and lived closer to the hospital were less likely to engage with surgical wound monitoring. Although not statistically significant, the current study suggests that patients with surgical site infections who used smartphones for surgical wound monitoring were less likely to be re-admitted or have further surgery and had shorter readmission stays. The accuracy of antibiotic use for surgical site infections using the surgical wound monitoring system was 96.5%. Conclusions This study underscores the potential of digital technologies, particularly smartphones, in efficient and accurate post-surgical monitoring. The findings suggest that the use of digital monitoring systems may improve patient outcomes, with potential for wider system-level benefits.

Breaking Barriers: An Innovative Tool to Assess the National and City-Level Physical Activity Policy Development to Practice Disconnect.

Population-level physical activity increases are improbable without intersectoral collaboration across government levels and sectors to develop and implement physical activity promotion policies. This study aims to provide information about the development of the Interaction between National and Local Government Levels in Development and Implementation of Physical Activity Policies Tool (INTEGRATE PA-Pol). A framework was created to examine the development and implementation of national and subnational physical activity policies and the (mis)alignment between government levels. The work was conducted in 3 phases: (1)a scoping review was carried out to identify local government physical activity promotion policies and instruments for assessing them, (2)an expert group designed 6 questionnaires, and (3)cognitive response testing was employed for validity testing and item modification with a panel of research and policy experts. The INTEGRATE PA-Pol Tool consists of 6 questionnaires assessing how national and subnational governments collaborate to develop and implement physical activity promotion policies. This tool can assist in better understanding the development and implementation of a public policy monitoring system that will allow for benchmarking and priority setting to comprehend how physical activity promotion policies are designed and executed.

5G SMART DIABETES TOWARDS PERSONALIZED DIABETES DIAGNOSIS WITH HEALTH CARE BIGDATA CLOUD

Recent advances in wireless networking and big data technologies, such as 5G networks, medical big data analytics, and the Internet of Things, along with recent developments in wearable computing and artificial intelligence, are enabling the development and implementation of innovative diabetes monitoring systems and applications. Due to the life-long and systematic harm suffered by diabetes patients, it is critical to design effective methods for the diagnosis and treatment of diabetes. Based on our comprehensive investigation, this article classifies those methods into Diabetes 1.0 and Diabetes 2.0, which exhibit deficiencies in terms of networking and intelligence. Thus, our goal is to design a sustainable, cost-effective, and intelligent diabetes diagnosis solution with personalized treatment. In this article, we first propose the 5G-Smart Diabetes system, which combines the state-of-the-art technologies such as wearable 2.0, machine learning, and big data to generate comprehensive sensing and analysis for patients suffering from diabetes. Then we present the data sharing mechanism and personalized data analysis model for 5G-Smart Diabetes. Finally, we build a 5G-Smart Diabetes testbed that includes smart clothing, smartphone, and big data clouds. The experimental results show that our system can effectively provide personalized diagnosis and treatment suggestions to patients. Key Words: Monitoring, Diabetes, Wearable, Big Data, Smart Systems, Machine Learning

Design and Implementation of NFC-based Staff Attendance Monitoring System

Design and Implementation of NFC-based Staff Attendance Monitoring System

An ultrathin wideband linear-to-circular polarization conversion metasurface for X-band applications

A specialized ultrathin metasurface has been developed to transform a linearly polarized incident wave into a reflected wave with circular polarization across a wide range of frequencies. The unit cell consists of two modified L-shaped structures that convert the incident linearly polarized wave to a circularly polarized wave. The axial ratio bandwidth of the reflected wave ranges from 8.19 to 11.08 GHz, exhibiting a fractional bandwidth of 30%. The dimensions of the unit cell are 7 × 7 ×1.6mm3 (0.225λ×0.225λ×0.051λ) where λ represents the center frequency within the operational frequency band. The proposed design not only provides a wide bandwidth but also is ultrathin as the dimensions are much less than λ/12. Finally, the proposed metasurface is fabricated and tested. The results obtained are in significant concurrence with the simulated results. Hence, it can be used in various applications, including implementation in multi-beam antennas, beam-scanning antennas, wireless systems, weather monitoring, radar tracking, and navigation systems.

Intervention diversity predicts social rehabilitation indicators at discharge in Therapeutic Communities

IntroductionThe Therapeutic Community Model narrows the gap in substance use disorder's network of assistance in Brazil by offering residential treatment to socially vulnerable populations. Due to a historical lack of evidence-based approaches, the government has established treatment guidelines and has been trying to implement training and monitoring methods. MethodThis study analysed real-world data from the monitoring system implemented in the largest network of institutions receiving public funds in the State of Sao Paulo. Data came from 8109 records of individuals admitted between 2014 and 2016 in 48 institutions. ResultsResults showed that less than half of the sample was exposed to at least one therapeutic activity from each of the recreational, spiritual, educational and selfcare intervention domains, as proposed by the national guidelines. Social rehabilitation outcome (SRO) defined by housing and self-support at discharge was reported by 21 % of the sample, who stayed in residential treatment for 82.6 days in average. More than half completed the therapeutic programme while 27.3 % dropout. Treatment duration and the diversity of the interventions offered were significantly associated with SRO when mutually adjusted. Chances of SRO increased nearly 5 times when residents were offered the full range of intervention domains, even when controlling for treatment duration. Treatment duration increased chances of SRO in a dose-response manner with a threefold increase for stays up to 90 days and over 9 times for stays longer than 90 days. ConclusionOur findings offer evidence to promote treatment guidelines compliance and to pave the way for the implementation of monitoring systems for this modality of treatment in Brazil and abroad.

Gendered gaps to tuberculosis prevention and care in Kenya: a political economy analysis study

BackgroundTuberculosis (TB) remains a public health concern in Kenya despite the massive global efforts towards ending TB. The impediments to TB prevention and care efforts include poor health systems, resource...

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.

IoT based weather monitoring system for temperature, humidity, rainfall and seismic detection in real time

This paper presents the design and implementation of an IoT-based weather monitoring system enhanced with seismic detection capabilities, employing Node MCU microcontroller and the Blynk mobile application platform. The system incorporates various sensors including a rain sensor, Light light-dependent resistor (LDR), a DHT11 sensor for temperature and humidity measurement, and an accelerometer (MPU6050) for earthquake detection. The hardware components are interconnected with the Node MCU microcontroller, facilitating real-time data acquisition from the sensors. Programming of the Node MCU is conducted using the Arduino IDE, enabling data transmission to the Blynk app via Wi-Fi connectivity. The Blynk app serves as the user interface, allowing seamless visualization and monitoring of weather parameters and seismic activity on smartphones. Key functionalities of the system include periodic data collection from sensors, transmission of sensor data to the Blynk server, and updating of graphical representations in the Blynk app interface. The accelerometer sensor is utilized to detect changes in acceleration, indicative of seismic disturbances. Threshold values are defined to trigger alerts within the Blynk app in the event of potential seismic activity. The implementation undergoes rigorous testing to ensure accuracy, reliability, and responsiveness under diverse environmental conditions. Considerations such as network stability, power efficiency, and data security are addressed to enhance system performance and longevity. The system demonstrates promising capabilities for real-time weather monitoring and seismic event detection, offering valuable insights for disaster preparedness and environmental analysis. IoT-based weather monitoring system integrated with seismic detection provides an effective solution for comprehensive environmental monitoring, leveraging the power of IoT technology and mobile applications for enhanced data accessibility and analysis. Further advancements and optimizations can be explored to extend the functionality and scalability of the system for broader applications in environmental science and disaster management.

Current problems and prospects of poultry industry: innovative vector

Poultry farming in Kazakhstan is one of the most progressive and dynamically developing areas of agriculture, which is profitable and quickly pays off. The goal is to study the economic indicators of poultry farming industry, develop directions for its development, and analyze government support measures. Methods – statistical analysis, comparison and generalization, observation with subsequent conclusions. Results - the authors show the state of poultry farms, identify problems and factors that negatively affect the growth of production volumes, and consider issues of subsidizing producers. It is noted that poultry production, including chickens and eggs, has increased, which is important to meet the growing demand for these food products. Efforts are being made to develop the domestic poultry sector through various initiatives, including investment in infrastructure, improvement of technological processes, and government assistance. These measures are aimed at reducing dependence on imported poultry meat and increasing self-sufficiency in poultry products. Vaccination programs are being implemented and biosafety protocols and monitoring systems are being improved. The republic's poultry farmers are introducing modern production methods and technologies to optimize labor efficiency and productivity. This is, first of all, the use of innovations in genetics, integrated diets, and more advanced housing and management systems. Conclusions - based on the experience of developed countries, it is proposed to raise the level of poultry farming in Kazakhstan through investment in research and development, introduction of advanced technologies, efficient production methods, wide access to markets and compliance with high quality standards. However, achieving results in poultry farming depends on specific geographical, economic and cultural factors. The stable development and expansion of poultry farming sector provides a number of undeniable advantages: a new level of small and mediumsized businesses; additional jobs; providing the population of the republic with high-quality products of domestic production; a real opportunity to refuse similar imported products; quite a large flow of investment.