Current Monitoring Systems Research Articles

Optimization of sensor model for solar radiation measurement with a pyranometer

Solar energy is electromagnetic energy produced in a thermonuclear process by the Sun from the nuclear fusion of the Sun’s core. This process produces solar radiation. In the lives of living beings on this Earth, solar radiation plays a significant role. As mentioned earlier, the uses are when there is a certain level required for the solar radiation received and vice versa. A more specific measurement of solar radiation is, therefore, needed. Unfortunately, until now, measurement equipment for solar radiation was limited to a few parameters that could be observed. On the other hand, conventional mechanisms and communication media are still used in the current measurement monitoring system, so that the monitoring and analysis process is ineffective. Therefore, this paper provides a solar radiation sensor model that uses only a sensor but can produce four parameters. The system contains a Pyranometer and a realtime controller that can generate all of the solar radiation measurements needed. The proposed model system is hoped that this sensor system will work more accessible and more efficiently.

Design of intelligent invigilator system based on artificial vision

Aiming at the problems of high packet loss rate and low intelligent degree in the current video monitoring system for examination invigilation, an intelligent invigilator system design method based on artificial vision is proposed in this paper. The system design is divided into hardware and software parts, including a / D circuit, clock circuit, video frame cyclic error correction and coding circuit, program loading circuit and output interface circuit. The experimental results show that the system can effectively reduce the video packet loss in the process of invigilation, improve the visual coverage of the invigilator area, and the system is highly integrated and intelligent.

Development of a wind turbine gearbox virtual load sensor using multibody simulation and artificial neural networks

A current development trend in wind energy is characterized by the installation of wind turbines (WT) with increasing rated power output. Higher towers and larger rotor diameters increase rated power leading to an intensification of the load situation on the drive train and the main gearbox. However, current main gearbox condition monitoring systems (CMS) do not record the 6‑degree of freedom (6-DOF) input loads to the transmission as it is too expensive. Therefore, this investigation aims to present an approach to develop and validate a low-cost virtual sensor for measuring the input loads of a WT main gearbox. A prototype of the virtual sensor system was developed in a virtual environment using a multi-body simulation (MBS) model of a WT drivetrain and artificial neural network (ANN) models. Simulated wind fields according to IEC 61400‑1 covering a variety of wind speeds were generated and applied to a MBS model of a Vestas V52 wind turbine. The turbine contains a high-speed drivetrain with 4‑points bearing suspension, a common drivetrain configuration. The simulation was used to generate time-series data of the target and input parameters for the virtual sensor algorithm, an ANN model. After the ANN was trained using the time-series data collected from the MBS, the developed virtual sensor algorithm was tested by comparing the estimated 6‑DOF transmission input loads from the ANN to the simulated 6‑DOF transmission input loads from the MBS. The results show high potential for virtual sensing 6‑DOF wind turbine transmission input loads using the presented method.

Wind, waves, and surface currents in the Southern Ocean: observations from the Antarctic Circumnavigation Expedition

Abstract. The Southern Ocean has a profound impact on the Earth's climate system. Its strong winds, intense currents, and fierce waves are critical components of the air–sea interface and contribute to absorbing, storing, and releasing heat, moisture, gases, and momentum. Owing to its remoteness and harsh environment, this region is significantly undersampled, hampering the validation of prediction models and large-scale observations from satellite sensors. Here, an unprecedented data set of simultaneous observations of winds, surface currents, and ocean waves is presented, to address the scarcity of in situ observations in the region – https://doi.org/10.26179/5ed0a30aaf764 (Alberello et al., 2020c) and https://doi.org/10.26179/5e9d038c396f2 (Derkani et al., 2020). Records were acquired underway during the Antarctic Circumnavigation Expedition (ACE), which went around the Southern Ocean from December 2016 to March 2017 (Austral summer). Observations were obtained with the wave and surface current monitoring system WaMoS-II, which scanned the ocean surface around the vessel using marine radars. Measurements were assessed for quality control and compared against available satellite observations. The data set is the most extensive and comprehensive collection of observations of surface processes for the Southern Ocean and is intended to underpin improvements of wave prediction models around Antarctica and research of air–sea interaction processes, including gas exchange and dynamics of sea spray aerosol particles. The data set has further potentials to support theoretical and numerical research on lower atmosphere, air–sea interface, and upper-ocean processes.

Optimizing the MFlex monitoring system using Mahalanobis-Taguchi system

Methadone Flexi Dispensing Service (MFlex) has been officially re-branded from Methadone 1Malaysia Service (M1M) since 2nd January 2019. Patients under MFlex are frequently taking their methadone according to a plan provided by pharmacist at public clinic. From the dose monitoring taken annually, pharmacists can predict critical patients based on high monthly dose increases. However, the current monitoring system is written documentation with total doses that cannot accurately measure addiction levels and slow down the distribution process to appropriate incentives as provided by the government. The main objective of this work is to develop a new data monitoring system by evaluating all factors contributed to the addiction level. Mahalanobis-Taguchi System (MTS) is a method of predicting and diagnosing system performance using multivariate data in order to make quantitative decisions with the construction of a multivariate measurement scale using an analytical method. The results show that the minimum Mahalanobis Distance (MD) for healthy data is 0.2245 while the maximum is 2.3380. The minimum and maximum MD of unhealthy data is 0.6077 and 24.5719 respectively. Thus, parameters of blood, bilirubin, nitrite, specific gravity, leukocytes are considered as significant parameters by considering positive value signal-to-noise ratio (SNR) gain. Graphical user interface (GUI) has been developed for analyzing the normal and abnormal patients in detail. Meanwhile, mobile application has been developed as a decision-making tool to classify that the patients is either normal or abnormal.

WITHDRAWN: Smart intravenous infusion monitoring and controlling system using Internet of Things

As technology is progressing at a very high pace, it is imperative to occupy with the progress in medical science. The latest shift that is happening in the world as regards our health. In the current saline bottle monitoring system, the intravenous infusion of fluids by gravity flow is a common procedure in medical care facilities. It is of vital importance that the fluid for infusion is replaced with a fresh supply when the fluid bottle is empty. This requires regular inspection by a nurse. In some cases, a pressure difference between a vein of a patient and the saline bottle may cause a reverse flow of the fluid from the patient to the saline bottle, which may prove fatal to the patient. Thus, a need for a system for efficiently and effectively monitoring a fluid level in a saline bottle with minimum human intervention. This paper provides a solution to overcome these problems with the aid of the Internet, sensors can interact with each other via the whole Bio Medical instrument which is placed on the monitoring equipment. This system is easily adaptable for any type of fluid bottle regardless of its initial size and weight.

A Current Monitor System in High-Voltage Applications in a Range from Picoamps to Microamps

In this article, we present a system to measure current in the range of 0 to 10 μA with high-voltage isolation up to 5 kV. This current monitor consists of three ammeters connected in series, to improve the resolution in the measurement. The design features several innovative elements such as using low voltage to provide power to the devices to measure the current and digitize it with a sampling frequency of 1 KHz, it is generated based on a DC-DC converter that produces three voltages, +12 V, −12 V, and 5 V, from a conventional 10 V source. The three voltages are referenced to the same floating ground. The DC-DC converter has a high voltage insulation up to 5 kV and four optocouplers with an insulation up to 20 kV are used to read the digitized data. The introduction of a DC-DC converter contributed to reduce the noise level in the analog part of the circuit which has been resolved implementing shields inside the board. In particle physics, several systems are used to detect particles in high-energy physics experiments such as Gas Electron Multiplier (GEM), micromegas, etc. GEMs suffer small deteriorations due to discharges in constant operation and require monitoring the current consumption at high frequency (1 kHz). In this work, we present the design and operation of a 0 to 10 μA auto scale ammeter. The results obtained by monitoring the current in a 10 × 10 cm2 GEM are shown.

Design of Deployment Strategies to Monitor the Movement of Animals with Passive Electronic Devices.

Current animal monitoring systems have improved our knowledge of quantitative animal ecology. There are many electronic tracking technologies such as VHF/UHF telemetry, light-level geolocation, ARGOS satellite telemetry and GPS tracking. To reach the desired level of information retrieval requires the planning of adequate equipment effort and coverage, which depends on the properties of the system. We propose an equipment arrangement model consisting of a given number of receiver stations in a two-dimensional space in which the animals move according to a central place movement model. The objective is to characterize how the transmission of tracking data depends on the movement of the animals and the design of the equipment deployment: quantity and location of the receiver stations and their associated reception radius. We also implement the model using real trajectories of southern elephant seals and Australian sea lions publicly available online and tracked during the years 2010–2012. We characterize the data transmission based on different equipment configurations and we obtained analogous results to the theoretical model.

Coastal Ecological Environment Monitoring and Protection System Based on Multisource Information Fusion Decision

With the problem of nuclear leakage being concerned by more and more industries, the research of coastal ecological environment monitoring has become more and more important. Therefore, it is necessary to study the current unsystematic coastal ecological environment monitoring and protection system. Aiming at the accuracy of feature fusion and representation of single short environment information, this paper compares the classification effects of the three fusion methods on four classifiers: logistic regression, SVM, random forest, and naive Bayes, to verify the effectiveness of LDA and DS model fusion and determine the consistency vector representation method of short environment information data. This paper collects and analyzes the coastal data in recent years using multisource information fusion decision‐making. In this paper, DS (Dempster Shafer) evidence algorithm is used to collect the data of coastal salinization degree and air relative humidity, and then, the DS feature matching model is introduced to fuse the whole index system. The method in the article completes the standardized and standardized processing of monitoring data digital conversion, quality control, and data classification, forms interrelated four‐dimensional spatiotemporal data, and establishes a distributed, object‐oriented, Internet‐oriented dynamic management real‐time and delayed database. Finally, this paper carries out tree decision processing on the coastal ecological environment monitoring data of multisource information fusion, to achieve the extraction and intuitive analysis of special data, and puts forward targeted protection strategies for the coastal ecological environment according to the data results of the DS algorithm. The research shows that the number of indicators in multisource information fusion in this paper is 16, a total of 3251 data, 2866 meaningful information, and 1869 data including ecological cycle. These data are the results of the collection of multi‐information data. Based on the multilevel nature of the existing marine environment three‐dimensional monitoring system, the study established a comprehensive resource‐guaranteed framework and divided it into four levels according to the level of the marine monitoring system: country, sea area, locality, and data access point. In specific analysis, the guarantee resources involved in each level are introduced. On the basis of in‐depth analysis of the requirements of the marine environment three‐dimensional monitoring system operation guarantee and the guarantee resource structure, the marine environment three‐dimensional monitoring operation comprehensive guarantee system is described from the internal structure and the external connection. The DS algorithm extracts the status information resources of various marine environment three‐dimensional monitoring systems, through the interaction of various subsystems, realizes the operation and maintenance of the monitoring system, and provides various technical supports such as system evaluation and failure analysis. After multisource information fusion and decision‐making, it is obtained that the index equilibrium module in the DS algorithm in this paper is 0.52, the sensitivity is 0.68, and the independence is 0.42. Among them, the range of sensitivity is the largest. In the simulation results, the eco‐economic coefficient can be increased from 12% to 36%. Therefore, using the method of multisource information fusion for quantitative index analysis can provide data support for coastal ecological environment detection, to establish a more perfect protection system.

Data Traffic Analysis on an Electric Current Monitoring System

Change and Innovation continues as the times progress. Especially in the field of technology, one of which is the Internet of Things (IoT). With the existence of this technology, electronic devices can be connected to the internet. This will simplify the process of data transmission and device control. With this aim, the authors do research on the implementation of IoT technology on electronic devices, especially in the field of electricity. Electrical energy monitoring systems are used to detect the use of electrical energy used by the load. In this monitoring system, the measurement of the electric current using the current sensor. The measurement data made by the current sensor will be processed by the microcontroller. The research developed arduino-based monitoring systems and databases aimed at detecting and monitoring the use of electric current. In addition, it also performs analysis of data traffic from arduino devices and databases, to find out data delay, throughput or packet loss by using Wireshark.

Feasibility and Validity of a Framework for Antimicrobial Stewardship in General Practice: Key Stakeholder Interviews.

There is little guidance about developing systems for antimicrobial stewardship (AMS) for general practice. A literature review identified six key components: governance, monitoring of antibiotic prescribing and resistance with feedback to prescribers, consultation support, education of the public and general practitioners, pharmacist and nurse involvement, and research, which were incorporated into a potential framework for the general practice context. Objectives: to determine the feasibility and validity of the proposed AMS framework. A secondary objective was to identify likely bodies responsible for implementation in Australia. We undertook interviews with 12 key stakeholders from government, research, and professional groups. Data were analysed with a thematic approach. The framework was considered valid and feasible. No clear organisation was identified to lead AMS implementation in general practice. The current volume-based antibiotic prescription monitoring system was considered insufficient. AMS education for the public, further development of GP education, and improved consultation support were strongly recommended. The role of community-based pharmacists and nurses is largely unexplored, but their involvement was recommended. A clear leader to drive AMS in general practice is essential for an action framework to gain traction. Monitoring and feedback of antibiotic prescribing require urgent development to include monitoring of prescribing appropriateness and patient outcomes.

Predicting the milk yield curve of dairy cows in the subsequent lactation period using deep learning

Existing lactation models predict milk yields based on a fixed amount of observed milk production in early lactation. In contrast, this study proposes a model to predict the entire lactation curve of dairy cows by leveraging historical milk yield information observed in the preceding cycle. More specifically, we present a deep learning framework to encode the model inputs, predict the latent representation of the milk yield sequences and generate the corresponding lactation curves. Results show that the proposed framework outperforms the baseline models and that during the first 26 days of lactation, the model’s predictions are more accurate than those of a state-of-the-art lactation model which is able to leverage the observed milk yields. As a result, the framework presented in this study allows farmers to increase their forecast horizon with respect to predicting its herd’s total production and hence facilitates optimal herd management. Additionally, the model can be used to compare a cow’s actual and expected milk yield over the entire course of the lactation cycle. This in turn can help to accelerate disease detection and enhance current animal monitoring systems. Finally, as the model incorporates the impact of health and reproduction events as well as herd management on the cow’s productivity, future earnings and costs can be estimated more accurately.

Assimilation of SMAP and ASCAT soil moisture retrievals into the JULES land surface model using the Local Ensemble Transform Kalman Filter

A land data assimilation system is developed to merge satellite soil moisture retrievals into the Joint U.K. Land Environment Simulator (JULES) land surface model (LSM) using the Local Ensemble Transform Kalman Filter (LETKF). The system assimilates microwave soil moisture retrievals from the Soil Moisture Active Passive (SMAP) radiometer and the Advanced Scatterometer (ASCAT) after bias correction based on cumulative distribution function fitting. The soil moisture assimilation estimates are evaluated with ground-based soil moisture measurements over the continental U.S. for five consecutive warm seasons (May–September of 2015–2019). The result shows that both SMAP and ASCAT retrievals improve the accuracy of soil moisture estimates. Especially, the SMAP single-sensor assimilation experiment shows the best performance with the increase of temporal anomaly correlation by ΔR ~ 0.05 for surface soil moisture and ΔR ~ 0.03 for root-zone soil moisture compared with the LSM simulation without satellite data assimilation. SMAP assimilation is more skillful than ASCAT assimilation primarily because of the greater skill of the assimilated SMAP retrievals compared to the ASCAT retrievals. The skill improvement also depends significantly on the region; the higher skill improvement in the western U.S. compared to the eastern U.S. is explained by the Kalman gain in the two experiments. Additionally, the regional skill differences in the single-sensor assimilation experiments are attributed to the number of assimilated observations. Finally, the soil moisture assimilation estimates provide more realistic land surface information than model-only simulations for the 2015 and the 2016 western U.S. droughts, suggesting the advantage of using satellite soil moisture retrievals in the current drought monitoring system.

Return to Work in Post COVID Phase in India: Media Reports Compilations

Summary: Ministry of Health & Family Welfare, Government of India (MOHFW, GOI) has publishedguidelines on preventive measures to contain spread of COVID-19 in workplace settings to respond in atimely and effective manner for detection and control of COVID-19 cases. It was first published on 17thMarch with subsequent revision on 15thApril; 18thMay and in June 2020. Despite timely and efficientimplementation of the guidelines; there was a steep rise in COVID cases. This article attempts to reviewthose guidelines holistically; to identify the gaps in them and the challenges in their implementation.This study will address shortcomings in the guidelines and what can be done to rectify these shortcomings.There is a need for strengthening of current monitoring and evaluation system/ mechanism along with theprovision of public health insurance.

Stray Current Protection and Monitoring Systems: Characteristic Quantities, Assessment of Performance and Verification.

Electrified transportation systems (ETSs) are affected by stray current problems impacting within and outside the right of way on reinforcement, buried metal structures and foundations. Stray current protection systems have recently been integrated in the track structure. Track electrical quantities are, thus, usually measured to assess track insulation and protection efficiency but should be backed up by additional measurements at the affected structures and installations, in order to assess their exposure and risk of corrosion. Ideally, a stray current monitoring system proceeds from the measurement of these quantities, to data collection and archival, to data presentation, analysis and prediction. Feasible sensors and probes, the impact of environmental conditions and uncertainty are considered for the measurement at the physical level. Data analysis is critically reviewed considering the variability of operating conditions and the effectiveness of each quantity as indicator of track insulation and protection efficiency. Given the normal spread of values, for data presentation and interpretation, suitable techniques are considered based on averaging, curve similarity and feature extraction, and also for the task of assessing compliance to limits or reference values and establishing a trend that may drive informed maintenance decision.

Development of a three-dimensional virtual monitoring system for a workshop

Aiming at the problems of poor applicability and development efficiency of the current manufacturing workshop monitoring system, a workshop monitoring system using the industrial Internet of Things platform as the system service platform is proposed. This article takes a seal automated production line as an example to illustrate the development process of a workshop monitoring system, including virtual scene construction, data acquisition and real-time model driving based on the industrial Internet of Things platform. The results show that the 3D virtual monitoring system has good real-time performance and realizes multi-level and visual monitoring. It has certain reference value for the development of the workshop 3D virtual monitoring system.

CHALLENGING QUESTIONS IN ENVIRONMENTAL MONITORING OF GROUNDWATER QUALITY IN RURAL AREAS OF KYIV’S REGION

Water resources protection is the prioritized target all over the world. Of course, it is Ukraine’s aim too. Environmental crisis grows stronger because of global warming. Monitoring of groundwater quality and water resources assessment requires immediate improvement and a framework for monitoring should be launched as soon as possible. After all, the delays observed 10-15 years ago have shown that humanity is unable to postpone the issue of environmental crisis until the emergence of slow solutions, either the availability of funds, or any other favorable moment. Environmental crisis has already begun on a large scale. So, regions of Ukraine, which were fully provided with water, have started to suffer from drought and hurricanes. Water wells in rural areas are running dry and in some places the water disappeared completely. Kyiv’s region is not an exception. Also, it is one of the most populated regions in Ukraine.Eco-friendly water supply to Ukrainian cities is permanently much talked-of topic in public settings. At the same time, matter of villages survival is suppressed. Taking into account disproportionate distribution of water resources between rural community and citizens, financial component becomes considerably important. Forasmuch as water is supplied for more financially reliable big-city residents for tens or even hundreds of kilometers from the location of a city. Therefore, the area that would have used these resources (most commonly it is rural area) is losing them. Approaches to solution of this problem should be overviewed and water monitoring should be actively started. Also causes of pollution of existing drinking water should be identified and removed. It is imperative to act in a goal-directed manner and to found a group of researchers and advance into action. Underground water massif should be examined as complex system (supersystem) of drinking water supply of population with the goal of improvement of current monitoring system. At the legal level there are all opportunities for implementation of the research of this system and first steps of state monitoring implementation has been done. Although it is not enough. As mathematically sound calculations show, value of this work operation and involvement of human resources could not be higher than service fee of safe environment and investments into health of rural population.

A Control Circuit Design for Automatic Aperture

In view of the fact that automatic aperture technique is applied as a method of regulating light in the current industrial monitoring and control systems more and more, an automatic aperture control circuit is designed according to automatic aperture control principle. The circuit has the characteristics of the simple structure, low cost and high reliability and etc. It has been proved by experiments that the circuit can adjust the size of aperture automatically according to the change of the external illumination, which ensures proper luminous flux entering the lens, and avoids the loss of image gray levels in bright space, and solves the image flicker caused by the change of light intensity, ensures the CCD get used to brightness changes of scenery outside and obtain the best image.

Мониторинг физического здоровья китайских студентов в рамках государственного проекта "Здоровый Китай - 2030"

This article presents the results of a study aimed at identifying problematic aspects of monitoring the physical health of Chinese students and establishing strategic directions for its improvement within the framework of the state project "Healthy China - 2030". In the course of the study, the reasons for the low effectiveness of the current monitoring system were considered in detail, which allowed us to identify strategic directions for its modernization, taking into account the prevailing socio-economic conditions in the field of education, physical culture and China as a whole. The significance of this research lies in the established strategic directions, according to which it is possible to implement a number of measures that will significantly improve the quality of monitoring the physical development and fitness of Chinese students and improve the management process in the field of physical education.

Cattle Diseases Prediction u sing IOT a nd ML A Review

Due to the everchanging environment, the cattle’s are in risk of getting affected by diseases and this in turn affects the economy. There will low productivity, less yield . It is still hard to forestall farm animals sicknesses using current monitoring systems that tune cattle activity and consequently the environmental situations of cattle .In this paper, we design a cattle health monitoring system using IOT and ML to a prevent livestock diseases, like anthrax disease, using dedicated sensors. We collect information using various. With the assistance of machine learning algorithm, we will predict the disease and send notification to the respective cattle owner and also the doctor in charge.