Performance Monitoring System Research Articles

Structural Health Monitoring of Large-Scale Bridges: A Synopsis of the Padma Bridge

In the recent decade, the concept of "structural health monitoring," or SHM, has gained prominence due to its promise of reflecting the condition of structures and facilitating the monitoring of their behavior. Bangladesh is a country with a long coastline, thus it is unfortunate that the SHM system has not been more widely deployed on the country's many highway bridges across rivers. Saving money on manpower, remote monitoring allows for accurate, up-to-date assessments of a bridge's structural soundness. Recent developments in sensor, communication, and storage technologies have made a worldwide SHM system for infrastructures possible. The primary goal of this investigation is to assess the performance of the structural health monitoring system on the Padma Multipurpose Bridge. Recent developments in SHM's integration with ITS show the usefulness of ITS devices (such as traffic cameras and traffic detectors) in analyzing bridge responses to multimodal traffic with varying loads or during critical events that cause excessive vibration beyond the normal limit, which can be of great assistance in tackling the Padma bridge's serviceability challenge. Integrating information from an ITS device with SHM may increase the reliability and precision of the SHM system. As a consequence of this integration, the SHM system would be less likely to misdiagnose damages (i.e., vibrations caused by big cars on a bridge may be perceived by a SHM sensor as a structural health concern of the bridge), resulting in decreased maintenance costs. This investigative study provided a summary of the SHM systems now in place for major bridges in Bangladesh, such as the spectacular Padma Bridge, and discussed their use and appropriateness in the near and far future.

Performance monitoring and evaluation of water environment treatment PPP projects with multi-source heterogeneous information

Effective measurement and monitoring of the quality of services from the private sector, in the terms of performance in water environment treatment public-private partnership projects (WETPs-PPP), is one of the keys to the success of these projects. Based on the deficiencies of performance monitoring and evaluation theory and the specific characteristics of WETPs-PPP, this study developed a performance monitoring and evaluation model for WETPs-PPP. First, through a literature analysis, a performance monitoring and evaluation index system of WETPs-PPP was constructed from eight dimensions including river embankment, bridges, river water, environment, garden facilities, garden plants, special purpose vehicle, hydraulic structure, and public satisfaction. Second, by combining the adaptive weighted fusion algorithm and Intuitionistic Fuzzy (IF) average operators, multi-source, multi-dimensional, and multi-spatio-temporal data were aggregated. Third, to improve the robustness of the performance monitoring results, the MULTIMOORA evaluation method with a defuzzification procedure under the IF environment was developed to conduct performance monitoring and evaluation for WETPs-PPP. Finally, a water environment treatment and ecological restoration project was used as an example to illustrate the feasibility and effectiveness of the proposed theoretical model.

6.H. Workshop: Towards improved performance measurement and universal health coverage in oral health care

Abstract Oral diseases are increasingly recognized as one of the most prevalent conditions in Europe, affecting nearly half of the European population. They are the third most expensive diseases to treat in the EU and dental expenditures are set to rise substantially. Within EU countries, oral health policy and financing are most often separated from the general health system and vary considerably between countries with different public and private organisation structures providing oral health services, different levels of out-of-pocket payments for patients and a variety of financing models. Oral diseases are a main driver of unmet need and financial hardship in the EU and particularly affect poorer and marginalized groups. However, current provider payment systems prioritize expensive invasive and technology-based methods which drives public expenditure while disserving the healthcare system's central objective of better health outcomes and reducing waste. Moreover, broad and effective oral health promotion policy that spans various care settings and areas of life is not sufficiently implemented. Oral health care systems thus face complex challenges regarding efficiency, quality and integration of care which requires good evidence to steer oral health policy. However, current health information systems only collect few indicators on oral health and oral health care. There is thus need for an improved evidence base for more meaningful assessments and comparisons of oral health systems performance which would allow better informed policy decisions and enable more targeted and effective oral health interventions. In May 2021 the World Health Assembly approved an historic resolution on oral health which urges Member States to include oral health in universal health coverage (UHC) benefit packages and to shift from the traditional curative approach towards a preventive approach. Oral health and the urgent needs for improving the financing of oral health systems have thereby received increased policy attention also in Europe. In this workshop evidence from a cross-country comparison of oral health financing, access and provision in Europe will be presented and the lack of supportive information systems for oral health system performance assessment will be highlighted. Recent research activities will be discussed such as the Horizon Europe project DELIVER (DELiberative ImproVEment of oRal care quality) which aims to create a synergistic problem-solving ecosystem to improve oral health systems. Debates in oral health research and policy in Europe are influenced by global developments such as the WHO resolution. To this end, the recent call for urgent system reform and policy action to address the burden of oral diseases will be set in context and discussed. Key messages • Oral care systems are still dominated by a traditional curative and technology-driven approach which fail to sufficiently encourage prevention and support holistic and integrated oral health care. • Lack of harmonized data reporting on oral health and oral health system indicators impedes oral care systems performance monitoring and evidence-informed policy-making.

Design of power monitoring system for new energy grid-connected operation based on LoRa and 4G technology

With the large-scale development and utilization of new energy, in order to achieve rapid collection, monitoring and judgment of grid-connected power quality data, this paper proposes a design scheme of a remote acquisition and monitoring system for power data based on LoRa and 4G communication technology. The system uses high-precision A/D to sample various types of electrical energy information such as current and voltage in real time, uses digital signal processor (DSP) chips to complete power quality data calculation, and combines LoRa, 4G and cloud platform technologies to achieve distributed remote metering and centralized monitoring. Experimental results show that the proposed scheme and the designed system have good tracking capability, and meet the requirements of technical specifications to calculate and analyze the conversion efficiency (>90%) and total harmonic distortion (<5%) of the grid-connected system, which improves the safety and monitoring efficiency of new energy power plants connected to the power grid.

Envisioning the use of in-situ arm movement data in stroke rehabilitation: Stroke survivors' and occupational therapists' perspectives.

BackgroundThe key for successful stroke upper-limb rehabilitation includes the personalization of therapeutic interventions based on patients’ functional ability and performance level. However, therapists often encounter challenges in supporting personalized rehabilitation due to the lack of information about how stroke survivors use their stroke-affected arm outside the clinic. Wearable technologies have been considered as an effective, objective solution to monitor patients’ arm use patterns in their naturalistic environments. However, these technologies have remained a proof of concept and have not been adopted as mainstream therapeutic products, and we lack understanding of how key stakeholders perceive the use of wearable technologies in their practice.ObjectiveWe aim to understand how stroke survivors and therapists perceive and envision the use of wearable sensors and arm activity data in practical settings and how we could design a wearable-based performance monitoring system to better support the needs of the stakeholders.MethodsWe conducted semi-structured interviews with four stroke survivors and 15 occupational therapists (OTs) based on real-world arm use data that we collected for contextualization. To situate our participants, we leveraged a pair of finger-worn accelerometers to collect stroke survivors’ arm use data in real-world settings, which we used to create study probes for stroke survivors and OTs, respectively. The interview data was analyzed using the thematic approach.ResultsOur study unveiled a detailed account of (1) the receptiveness of stroke survivors and OTs for using wearable sensors in clinical practice, (2) OTs’ envisioned strategies to utilize patient-generated sensor data in the light of providing patients with personalized therapy programs, and (3) practical challenges and design considerations to address for the accelerated integration of wearable systems into their practice.ConclusionsThese findings offer promising directions for the design of a wearable solution that supports OTs to develop individually-tailored therapy programs for stroke survivors to improve their affected arm use.

On the dynamic neural network toolbox design for identification, estimation and control

PurposeThere are common problems in the identification of uncertain nonlinear systems, nonparametric approximation, state estimation, and automatic control. Dynamic neural network (DNN) approximation can simplify the development of all the aforementioned problems in either continuous or discrete systems. A DNN is represented by a system of differential or recurrent equations defined in the space of vector activation functions with weights and offsets that are functionally associated with the input data.Design/methodology/approachThis study describes the version of the toolbox, that can be used to identify the dynamics of the black box and restore the laws underlying the system using known inputs and outputs. Depending on the completeness of the information, the toolbox allows users to change the DNN structure to suit specific tasks.FindingsThe toolbox consists of three main components: user layer, network manager, and network instance. The user layer provides high-level control and monitoring of system performance. The network manager serves as an intermediary between the user layer and the network instance, and allows the user layer to start and stop learning, providing an interface to indirectly access the internal data of the DNN.Research limitations/implicationsControl capability is limited to adjusting a small number of numerical parameters and selecting functional parameters from a predefined list.Originality/valueThe key feature of the toolbox is the possibility of developing an algorithmic semi-automatic selection of activation function parameters based on optimization problem solutions.

Safety and Protection Measures of Underground Non-Coal Mines with Mining Depth over 800 m: A Case Study in Shandong, China

With the increase in mining depth, the risk of ground pressure disasters in yellow gold mines is becoming more and more serious. This paper carries out a borehole test for the pressure behavior in a non-coal mining area with a mining depth of more than 800 m in the Jiaodong area. The test results show that under a depth of 1050 m, the increase in the vertical principal stress is the same as the increase in the minimum horizontal principal stress, which is about 3 MPa per 100 m. When the depth increases to 1350 m, the vertical principal stress increases by about 3% per 100 m, and the self-weight stress and the maximum horizontal principal stress maintain a steady growth rate of about 3 MPa per 100 m. In addition, based on the test results, the operation of the ground pressure monitoring system in each mine is investigated. The investigation results show that in some of the roadway and stope mines with depths of more than 800 m, varying degrees of rock mass instability have occurred, and a few mines have had sporadic slight rockbursts, accounting for about 5%. There was a stress concentration area in the lower part of the goaf formed in the early stage of mining, and slight rockburst phenomena such as rock mass ejection have occurred; meanwhile, the area stability for normal production and construction was good, and there was no obvious ground pressure. This paper compares the researched mines horizontally as well as to international high-level mines and puts forward some suggestions, including: carrying out ground pressure investigations and improving the level of intelligence, which would provide countermeasures to balance the safety risks of deep mining, reducing all kinds of safety production accidents and providing a solid basis for risk prevention and supervision.

ВНЕДРЕНИЕ И ПЕРСПЕКТИВЫ РАЗВИТИЯ КАРЬЕРНОЙ ЦИФРОВОЙ ПЛАТФОРМЫ В ВЫСШИХ УЧЕБНЫХ ЗАВЕДЕНИЯХ

This article represents the results of an analysis of in-depth interviews conducted with of the Higher School of Economics – St. Petersburg and St. Petersburg State Agrarian University about the existing problems in universities in the field of student career development, tools for solving these problems and expectations from a digital career platform as an example of a solution. The purpose of the research is to identify the causes of pain of students of the previously listed St. Petersburg universities related to career development during their studies, which need to be solved, for example, with the help of a digital career platform. During in-depth interviews, through one-on-one communication in social networks, the needs of students related to their career formation, the necessity of informing about career opportunities and the use of digital tools for career development were identified. The results obtained indicate the need to create a digital career platform in universities aimed at supporting student organizations, career events, publishing internships, vacancies, partner company news and career advice, integration into the performance monitoring system. In addition, the article carries out a market assessment and a financial plan for a digital career platform.

Visual display system of changes in physiological states for patients with chronic disorders and data transmission via optical wireless communication

A visual display system of changes in the physiological state of patients and their data transmission via optical wireless communication is presented. Existing methods such as bedside monitors do not provide the possibility of visual display of information near the object in conditions of high workload of personnel and allow transmitting data via an electric cable or remotely in the radio frequency range. Such disadvantages reduce the responsiveness of personnel and lead to numerous errors in the transmitted data. A remote operational monitoring system is more effective, providing data collection from sensors, display with minimal delay time and data transmission over an interference-free communication channel in the optical range. A simple and visual way of displaying information allows to quickly and accurately recognize critical situations. The proposed system has two channels. The first channel provides a visual representation of changes in the physiological state on the visual display device in the form of a bracelet. The second channel allows transmitting data about the deviation in the patient’s condition via optical wireless communication in the infrared range of the spectrum for detailed display on a computer. The visual representation of changes in the physiological state is based on programmable change in the color of the LED indicators and on change in their operation modes. The block diagram and design of the visual display and data transmission system are presented. As part of the evaluation of the system operability, the heating of the visual display device in the COMSOL Multiphysics was evaluated. It is shown, that the average heating temperature of the indicator part in contact with human skin does not exceed 24 °C and is safe for the patient. The optical scheme of the receiving unit and the transmitting module is presented. The optical model of the module is presented in the Zemax program. It is shown, that the required average optical power of the working spectral region is 235 μW for the four infrared LEDs and four photodiodes located at a distance of 1 meter. A description of the working layout of a visual display and data transmission device is presented, including a digital pulse sensor and blood oxygen level, a color control and data processing unit, a visual display device, and a data transmission unit. The LEDs operation modes and its compliance with the deviation of the controlled parameters were checked by a special microcontroller program of practical significance. The implementation of the developed system is relevant when monitoring the condition of the object of observation in cases where the use of the radio frequency range is limited and the stability of the data transmission channel to electromagnetic interference plays an important role.

Assessing a soil-removed semi-empirical model for estimating leaf chlorophyll content

Leaf chlorophyll content (LCC) is an important indicator of foliar nitrogen status and photosynthetic capacity. Compared to physical models, the generality of empirical models based on vegetation indices is often questioned when they are used to estimate LCC due to the influence from canopy structure, such as leaf area index (LAI). A recent study developed the LAI-insensitive chlorophyll index (LICI) and established a semi-empirical LICI-based LCC quantification model, which inherits both the robustness of physical models and the simplicity of empirical models. However, it is unclear whether such a simple model is as accurate and generic as physical models. Here, we adopted an innovative approach to disentangle the confounding effects of LAI and LCC on LICI and found that LICI was strongly correlated to LCC but only marginally sensitive to LAI. Moreover, we also found that LICI was sensitive to the soil background and thus proposed a spectral separation of soil and vegetation (3SV) algorithm, which is automatic and does not require prior information of soil background. After implementing the 3SV algorithm to remove the contributed reflectance of soil, we then obtained the contributed reflectance of vegetation (CRv). Model simulations showed that the soil background effect on the CRv-derived LICI was largely eliminated and hence this index was viewed to be soil-removed. As a result, the accuracy and generality of the soil-removed LICI-based model for LCC estimation was evaluated using comprehensive datasets from multiple vegetation types, years, sites, and observation platforms and compared to that of a MatrixVI-based physical model and a MERIS terrestrial chlorophyll index (MTCI)-based semi-empirical model. The root-mean-square error (RMSE) for LCC estimated by the soil-removed LICI-based model was 6.22–6.87 μg/cm2 for the crop datasets and 10.68 μg/cm2 for the multi-ecosystem dataset when the equivalent wet soil fraction was <0.7. Although further efforts are required to mitigate the effects of soil on the LICI-based model over sparse vegetation, this research is highly beneficial for extending its potential applications to the globe and advancing the development of an operational LCC monitoring system in the emerging satellite hyperspectral era.

Developing progress monitoring measures: Parallel test construction from the item-up

Progress monitoring is a process of collecting ongoing samples of student work and tracking performance of individual students over time. Progress monitoring involves administering parallel sets of items to the same student on a regular basis (at least monthly) that are sensitive to changes in the student’s understanding based on instruction. The sets of items administered over time should be parallel in difficulty so that differences in performance can be attributed to differences in the student’s understanding as opposed to variability in item difficulty across sets. In this manuscript, we describe an approach to designing items that controls item-level variability by constraining the item features that may elicit different cognitive processing. This approach adapts the principles of Automated Item Generation (AIG) and includes carefully designing test specifications, isolating specific components of the content that will be assessed, creating item models to serve as templates, duplicating the templates to create parallel item clones, and verifying that the duplicated item clones align with the original item model. An example from an operational progress monitoring system for mathematics in Kindergarten through Grade 6 is used to illustrate the process. We also propose future studies to empirically evaluate the assertion of parallel form difficulty.

Sentinel-2 estimation of CNC and LAI in rice cropping system through hybrid approach modelling

ABSTRACT Earth observation techniques represent a reliable and faster alternative to in-situ measurements by providing spatio-temporal information on crop status. In this framework, a study was conducted to assess the performance of hybrid approaches, either standard (HYB) or exploiting an active learning optimisation strategy (HYB-AL), to estimate leaf area index (LAI) and canopy nitrogen content (CNC) from Sentinel–2 (S2) data, in rice crops. To achieve this, the PROSAIL-PRO Radiative Transfer Model (RTM) was tested. Results demonstrate that a wide range of rice spectra, simulated according to realistic crop parameters, are reliable when appropriate field background conditions are considered. Simulations were used to train a Gaussian Process Regression (GPR) algorithm. Both cross-validation and validation results showed that HYB-AL approach resulted the best performing retrieval schema. LAI estimation achieved good performance (R2=0.86; RMSE=0.54) and resulted very promising for model application in operational monitoring systems. CNC estimations showed moderate performance (R2=0.63; RMSE=0.89) due to a saturation behaviour limiting the retrieval accuracy for moderate/high CNC values, approximately above 4 [g m−2]. S2 maps of LAI and CNC provided spatio-temporal information in agreement with crop growth, nutritional status and agro-practices applied to the study area, resulting in an important contribution to precision farming applications.

Using airborne and DESIS imaging spectroscopy to map plant diversity across the largest contiguous tract of tallgrass prairie on earth

Grassland ecosystems are under threat globally, primarily due to land-use and land-cover changes that have adversely affected their biodiversity. Given the negative ecological impacts of biodiversity loss in grasslands, there is an urgent need for developing an operational biodiversity monitoring system that functions in these ecosystems. In this paper, we assessed the capability of airborne and spaceborne imaging spectroscopy (also known as hyperspectral imaging) to capture plant α-diversity in a large naturally-assembled grassland while considering the impact of common management practices, specifically prescribed fire. We collected a robust in-situ plant diversity data set, including species composition and percent cover from 2500 sampling points with different burn ages, from recently-burned to transitional and pre-prescribed fire at the Joseph H. Williams Tallgrass Prairie Preserve in Oklahoma, USA. We expressed in-situ plant α-diversity using the first three Hill numbers, including species richness (number of observed species in a plant community), exponential Shannon entropy index (hereafter Shannon diversity; effective number of common species, where species are weighed proportional to their percent cover), and inverse Simpson concentration index (hereafter Simpson diversity; effective number of dominant species, where more weight is given to dominant species) at four different plot sizes, including 60 m × 60 m, 120 m × 120 m, 180 m × 180 m, and 240 m × 240 m. We collected full-range airborne hyperspectral data with fine spatial resolution (1 m) and visible and near-infrared spaceborne hyperspectral data from DESIS sensor with coarse spatial resolution (30 m), and used the spectral diversity hypothesis—i.e., that the variability in spectral data is largely driven by plant diversity—to estimate α-diversity remotely. In recently-burned plots and those at the transitional stage, both airborne and spaceborne data were capable of capturing Simpson diversity—a metric that calculates the effective number of dominant species by emphasizing abundant species and discounting rare species—but not species richness or Shannon diversity. Further, neither airborne nor spaceborne hyperspectral data sets were capable of capturing plant α-diversity of 60 m × 60 m or 120 m × 120 m plots. Based on these results, three main findings emerged: (1) management practices influence grassland biodiversity patterns that can be remotely detected, (2) both fine- and coarse-resolution remotely-sensed data can detect the effective number of dominant species (e.g., Simpson diversity), and (3) attention should be given to site-specific plant diversity field data collection to appropriately interpret remote sensing results. Findings of this study indicate the feasibility of estimating Simpson diversity in naturally-assembled grasslands using forthcoming spaceborne imagers such as National Aeronautics and Space Administration's Surface Biology and Geology mission.

A Study on Zakat Education Assistance for Poor Asnaf Student in Sabah

Zakat has been acknowledged for its role in establishing social justice and security among the Muslim community to avoid economic inequalities and unfavorable consequences. This study examines the role of zakat education assistance in growing human capital and balanced wealth distribution. Furthermore, educational assistantship such as scholarships, educational institution development, and education enhancement through training, workshops, seminars, and motivation for the poor asnaf student in Sabah has been discussed. Finally, a highlight on the managerial challenges and recommendations for zakat education assistance. Hence, this article will analyze the previous related article to gain an in-depth understanding of the current knowledge and information on the effort of zakat institution in empowering the education among poor asnaf students. The findings show that the zakat institution creates numerous efforts where it creates opportunities for the poor asnaf student to pursue their education in higher education and reduce the wealth gaps among poor Muslim society. The practical implication of this study will enhance the education performance monitoring system for poor asnaf students.

Intelligent Optimization Approaches for a Secured Dynamic Partial Reconfigurable Architecture-Based Health Monitoring System

In this work, an intelligent multi-objective optimization technique is proposed to optimize various parameters such as power consumption ([Formula: see text]), computation time ([Formula: see text]) and area ([Formula: see text]) for a health monitoring system designed using the Secured Dynamic Partial Reconfiguration (SDPR) architecture. The cost-efficient Dynamic Partial Reconfiguration (DPR)-based field-programmable gate array (FPGA) is very useful for analyzing many applications such as automation and data processing. The novelty of this paper is to design a new intelligent SDPR (i-SDPR) module in order to achieve better performance in a health monitoring system by considering various performance parameters. The SDPR architecture is incorporated with two reconfigurable modules such as Encrypt and Authenticate, which results in an increase in the core power consumption ([Formula: see text]), computation time ([Formula: see text]) and area ([Formula: see text]). So, to improve the performance of the SDPR-based health monitoring system, there is a necessity to optimize the performance parameters and it is achieved through intelligent multi-objective evolutionary (MOEA) techniques. The intelligent multi-objective evolutionary techniques such as Niched-Pareto Genetic Algorithm (NPGA), Pareto Archived Evolution Strategy (PAES) and Pareto Envelope-based Selection Algorithm (PESA) have been considered for better optimization in the performance parameters. For the study, the free-to-use MIMIC-III dataset is taken, which contains critically admitted various intensive care unit patient data. The dataset is processed through any one of the multi-objective evolutionary operators till satisfying the conditions and then forwarded to implementation. The proposed architecture has been implemented and tested using Cyclone[Formula: see text] V SX SoC Development Kit. The comparative analysis of various performance parameters was done for the proposed i-SDPR with the existing techniques such as the DPR and SDPR approach to show the improvement. The results declare that the proposed techniques obtain better performance compared to the existing techniques.

Level of Funding and Performance of Monitoring and Evaluation System of Human Immuno-Deficiency Virus Programme in Msambweni Sub- County, Kwale County

Purpose: The study sought to determine influence of funding on performance of Monitoring and Evaluation system of Human Immuno-Deficiency Virus Programme in Msambweni Sub- County, Kwale County&#x0D; Methodology: A descriptive survey design was used. A total of 36 staff working in the HIV Programme were targeted because they are familiar with the M&amp;E activities of the programme. All thirty-six staff working in the programme were used in this study as respondents. The researcher used Census survey in each facility because the number of subjects was manageable. Data was collected from the respondents using semi- structured questionnaires. The data was sorted, assessed for completeness and edited for errors, coded, and then entered into the Statistical Packages for Social Sciences (SPSS) version 25 where it was analysed using descriptive statistics. Descriptive statistics that were used include percentages and frequencies. Data presentation was done using tables, charts and graphs.&#x0D; Findings: Results revealed that the budget allocated for most of the respondents is minimal and does not favour the monitoring and evaluation system. The study concluded that lack of sufficient budget allocation has a negative impact on the performance of the monitoring and evaluation system.&#x0D; Unique contribution to Theory, Practice and Policy: The study recommends for more money to be generated in to the budget allocated to favour the monitoring and evaluation system. Lastly but not least the study recommends that training should be encouraged on services delivery to the programme since it have got a very high impact on monitoring and evaluation system.

Animal Migration Studies with the Use of ICARUS Scientific Equipment in the URAGAN Space Experiment aboard the Russian Segment of the ISS

The major challenges of space research are monitoring and exploration of our planet, which are carried out through the use of remote sensing satellites (RSS) operating in near-Earth orbits. They provide invaluable information for assessing the environmental, epidemiological and other situations on our planet, including animal migration data. The ICARUS project (International Cooperation for Animal Research Using Space) implemented on the International Space Station (ISS) is an ideal laboratory for in-orbit testing of instrumentation and various space technologies aimed to refine methods for tracking movements of mammals and birds. The paper analyzes the experience in the operation of the animal migration monitoring system installed in the Russian segment (RS) of the ISS (ISS RS). The system has incorporated the latest accomplishments in space science, satellite navigation, control technology, and microelectronics. The scientific results on the study of animal and bird migrations obtained within the Russian research program are briefly discussed.

Design and Realization of Seeding Quality Monitoring System for Air-Suction Vibrating Disc Type Seed Meter

To improve the seeding qualification rate and stability of the air-suction vibrating disc type seed meter on the rice seedling raising line, in this paper, an improved wireless sensor network node layout optimization algorithm was proposed, and the operation monitoring system of the seed meter was designed using the Internet of Things and configuration software. In the system, the upper computer software adopted the Kingview software, the lower computer took the STM32F429IGT and CC2530 as the core controllers, and ZigBee was selected for data transmission to build the wireless sensor network. The acquisition of field status information and the sending of control instructions were realized through the sensor nodes constructed by the CC2530 core controller. The data was sent to the coordinator node in real-time through the wireless sensor network. The coordinator node realized the bidirectional transmission of data with Kingview and the upper computer control instructions forwarding using the ASCII protocol The host computer monitoring and management software was developed based on configuration software to realize real-time data monitoring, access database storage, fault alarm, control command sending and other functions. The experimental results showed that the detection accuracy of the system for the seeding amount and missed seeding amount was 94.3% and 95.6%, respectively, which could realize the monitoring of the primary working status of the seed meter. The system realized effective data transmission and data remote wireless transmission function, which provided sufficient theoretical and data support for the performance optimization of the seed meter, and laid a good foundation for the visualization and intelligence of information data.

The first phase of research and manufacturing of bridge deformation monitoring equipment using position sensor: case study in Vietnam

This paper is the first result of an experimental study of manufacturing deformation monitoring equipment using a position sensor, an efficient solution for contractors in bridge monitoring during either process of construction or operation in the context of the increasing number of large bridges. The object of the research is bridgework. And the work is aimed at achieving two tasks, which include meeting the need of the surveyors in real-time monitoring and warning during the construction process with a suitable price and reducing the reliance on manufacturers in supplying and operating monitoring systems. The study used a KTR position sensor, a Linear Variable Differential Transformer, and an Arduino board for embedded coding. Data from the KTR sensor are acquired, processed, and controlled by a program written in Python. The results of the study are compared to the true observations from a Mitutoyo Palmer which has 0.01 mm accuracy in a laboratory. The initial results from the laboratory show prospects for applications in reality, and accuracy is suitable for technical measurements. This is also a good choice for surveyors in acquiring continuously monitoring data at high accuracy for bridge monitoring in general and structure in particular. The study is fundamental to expanding the number of channels from 1 to 8 or 16 for monitoring a full cross-section. At the same time, cable connection mode will be developed to Wi-Fi or Bluetooth mode for online observation. The results of the study confirm the scientificity, and feasibility of the solution. This solution can be applied for either bridge monitoring or other monitoring fields and can be produced by contractors. The cost of monitoring projects will be significantly reduced and there will be no more disruption of monitoring projects after suppliers leave as a new system will be quickly added or replaced.

Rancang Bangun Monitoring Solar Home System Berbasis Internet of Thing Pada Komplek Peternakan Kambing PE Marsudi Luhur

The PE Goat Farm Complex, with an area of about 600 m2 located in Mertosutan Hamlet, Sidoluhur Village, Godean District, Sleman Regency, Yogyakarta Special Region Province, has a lighting system from a hybrid solar home panel system with solar panels as the main source and PLN as a backup source. The system for switching resources from solar panels to PLN sources or vice versa is carried out automatically with an ATS (Automatic Transfer Switch) circuit so that no human resources are needed for its operations. The performance of the solar home system is the most important element in the supply system, so it needs to be monitored regularly. This program aims to design a solar home system performance monitoring system based on the Internet of Things (IoT). The method applied in this program is Design Improvement. The design of the system is made by adding a series of electrical components that are applied to the solar home system at the location. The power, current, voltage, and light intensity generated by the solar home system are sent to the application via the internet in real-time. The results of testing the implementation of an IoT-based monitoring system design can work optimally with a 100% success rate. The implication is that the use of a solar home system at the Marsudi Luhur Goat Farm Complex can be maintained for stability and sustainable performance through an IoT-based monitoring system that has been implemented.