Remote Module Research Articles

The Application of SCADA Systems on Wrapping Machines using PLC and Wonderware InTouch in the Automotive Manufacturing Industry

In this paper, the application of SCADA systems in the automotive product packaging process has been carried out. At an Automotive Manufacturing Industrial Company that produces tires and tubes specifically for two-wheeled vehicles. In making marketable tires, there are various processes that must be gone through, namely: mixing, extrusion, bead wire, calendaring, bias cutting, manufacturing, curing, final inspection, and wrapping. The wrapping process is the process of packaging the outer tire, with the work process of wrapping the outer tire using a predetermined plastic. In the wrapping process there is a process of collecting counter result data manually using a check sheet by the machine operator. The machine operator takes the counter data displayed on the panel of each machine. After that, the data is collected by the foreman at the end of the shift, then the data is recapitulated and entered manually into the recap data for the accomplishment of the wrapping process by the foreman. This process is considered less efficient because it is quite time-consuming, and the level of human error that may occur is quite high. Therefore, we designed a SCADA system for the wrapping machine using the Wonderware Intouch 10.6 application. In this case, we use data communication between a PC (Personal Computer) which contains the Wonderware application program and Microsoft SQL Server with a Mitsubishi Q02H PLC (Programmable Logic Controller) via the QJ71E71-100 ethernet module, and the cc-link module as a remote Input-output module. The machine counter results data is stored in the Microsoft SQL Server database. The process of saving monitoring data from Wonderware Intouch to Microsoft SQL Server is done by creating a table in the Microsoft SQL Server database, adding ODBC (Open Database Connectivity) according to the database that has been created, and creating a bindlist on Wonderware Intouch. This SCADA system was developed for high accuracy, eliminating the manual process of inputting counter data results, and it can monitor production results automatically from a PC both in the interface and data acquisition recorded in Microsoft SQL Server.

Same term, but unequal understanding: differences in digital public health intervention features

Abstract Digital technologies have transformed healthcare delivery and public health, with many countries integrating interventions such as online consultations, electronic health records, and telemedicine to improve population health and healthcare accessibility. Multinational assessments for benchmarking system maturity ask for the degree of implementation of such tools. However, are these interventions as comparable as they claim to be? This talk presents a qualitative analysis of 179 digital public health (DiPH) interventions described in scientific articles. We categorized interventions based on their implementation stages, public health functions, and reported and non-technical features. Telemedicine, health apps, and electronic health record interventions dominated the diverse landscape. While these technology groups already differed greatly in their functions, we identified equally significant differences in the reported intervention characteristics within the groups. For example, telemedicine was not only used in healthcare settings for patients and health professionals but also in primary prevention and research for researchers, policymakers, and healthy individuals. Different interventions reported varying functions, such as remote monitoring, self-monitoring, alarm systems, patient motivation, and user empowerment modules. So, is there one common telemedical intervention? No. Instead, all individual technologies differed to varying degrees. The analysis underscored the diversity of DiPH interventions among and within intervention groups and highlighted the importance of precise terminology for effective planning and evaluation. Instead of using broad classifications like ‘telemedicine,’ interventions should be defined and communicated based on specific technological functions, non-technical characteristics, use cases, and user groups. This approach will promote cross-disciplinary collaboration and foster international comparability across DiPH systems.

Research on the Technology of Improving the Compatibility of DC Measurement Devices Based on the Operation Experience of Siemens Hardware Solutions

The aim of this study was to manufacture alternative Siemens DC measurement system equipment to solve the problems of increased failure rates of foreign DC measurement equipment and the stopped production of key parts. In this paper, the overall structure and common faults of the Siemens DC measurement system are introduced, the difference between TDM signal frame structure and FT3 frame structure is detailed, and the related functional structure, chip type, and function of the Siemens distal module and merging unit (including laser function) are studied. The remote module, merging unit (including laser function), and related hardware design and software design to replace the Siemens DC measurement system were developed, and the test environment and control protection, fault recording wave for communication, and other functional tests were built. The test results show that the domestic remote module, merging unit (laser function), and other technologies communicate normally with the existing Siemens and the domestic mainstream manufacturers, and the accuracy meets the requirements of the 0.2 level.

Remote Water Quality Monitoring System In Shrimp Ponds With Photovoltaic (PV)-Based Energy Source

Introduction: Shrimp has great potential to be used as a business field in Indonesia. Especially in Parigi Regency itself, there are now many shrimp ponds that can be found because of the benefits obtained, so people are interested in making shrimp farming a livelihood. One of the main problems of shrimp ponds is pond water quality. There are several factors that affect pond water quality, namely water temperature, water pH, and water salinity, good pond water quality management can maintain quality standards and can increase shrimp yield and productivity Method: To facilitate the shrimp farmers, innovations need to be made in order to help the shrimp farmers manage their shrimp ponds, therefore using a remote water quality monitoring was system in shrimp ponds with photovoltaic (PV) based energy sources is expected to be an innovation in managing shrimp ponds, especially in monitoring water quality in shrimp ponds. The monitoring system designed using the NRF24L01 module as a remote communication module, at the research location the distance from the shrimp pond to the house is approximately 100 meters, so the tools that have been designed can facilitate shrimp farmers to monitor the shrimp pond Results and Disscussion: The results of testing the DS18B20 temperature sensor compared with a digital thermometer measuring instrument get an average error of 0.014%. The test results of the pH sensor compared to the pH meter get an average error of 0.026%. TDS sensor test results compared with the TDS meter get an average error of 0.04%. Conclusion: The temperature, pH, and salinity monitoring system uses transmitter and receiver modules, where the transmitter module reads and sends data to the receiver module wirelessly with NRF24L01. Using DS18B20 temperature, pH, and TDS sensors, as well as energy from photovoltaics, this system helps shrimp farmers monitor pond water quality remotely.

Power-over-fiber-based optical wireless communication systems towards 6G

This paper reports two implementations of power-over-fiber (PoF) solutions applied to radio-over-fiber (RoF) and optical wireless communication (OWC) systems, in the context of an industrial environment. We employ a conventional 62.5-µm multimode fiber (MMF) to deliver optical power to different communication links based on RoF, free-space optics (FSO), and visible light communication (VLC) technologies aiming beyond 5G (B5G) and 6G applications. First, a 3.5-GHz 5G New Radio (5G NR) signal is transmitted throughout a 20-km single-mode optical fiber (SMF) link using RoF technology. Regarding the PoF system, a 5-W optical power is transmitted through a 100-m MMF link. A photovoltaic power converter (PPC) and a DC/DC converter are employed to convert the power from the optical to the electrical domain and adjust the voltage level, respectively, with the purpose of energizing a remote RoF module. The attainable optical and electrical power transmission efficiencies (OPTE and PTE) are 80% and 19%, respectively. Posterior, a second PoF system is implemented to power a hybrid RoF/FSO/VLC B5G system, comprising a 200-m MMF and an additional DC/DC converter. Over 10.5 W of optical power is transmitted to feed an electrical amplifier (EA) and a white LED from the VLC link. In this configuration, we achieve 78% and 18.5% of OPTE and PTE, respectively. Furthermore, a performance investigation based on the root mean square error vector magnitude (EVMRMS) metric is conducted to evaluate the signal using the implemented PoF systems and a conventional electrical power supply. In the first implementation, a throughput of 600 Mbps is achieved with 100-MHz bandwidth without performance degradation, when compared to the conventional-powered RoF system, whereas, in the second implementation, 60-Mbps throughput is achieved when employing the FSO and VLC technologies simultaneously, demonstrating the applicability and potential of the PoF technique for B5G and 6G industrial communications.

Axial de-scanning using remote focusing in the detection arm of light-sheet microscopy

Rapid, high-resolution volumetric imaging without moving heavy objectives or disturbing delicate samples remains challenging. Pupil-matched remote focusing offers a promising solution for high NA systems, but the fluorescence signal’s incoherent and unpolarized nature complicates its application. Thus, remote focusing is mainly used in the illumination arm with polarized laser light to improve optical coupling. Here, we introduce a novel optical design that can de-scan the axial focus movement in the detection arm of a microscope. Our method splits the fluorescence signal into S and P-polarized light, lets them pass through the remote focusing module separately, and combines them with the camera. This allows us to use only one focusing element to perform aberration-free, multi-color, volumetric imaging without (a) compromising the fluorescent signal and (b) needing to perform sample/detection-objective translation. We demonstrate the capabilities of this scheme by acquiring fast dual-color 4D (3D space + time) image stacks with an axial range of 70 μm and camera-limited acquisition speed. Owing to its general nature, we believe this technique will find its application in many other microscopy techniques that currently use an adjustable Z-stage to carry out volumetric imaging, such as confocal, 2-photon, and light sheet variants.

Development and machine learning-based calibration of low-cost multiparametric stations for the measurement of CO2 and CH4 in air

The pressing issue of atmospheric pollution has prompted the exploration of affordable methods for measuring and monitoring air contaminants as complementary techniques to standard methods, able to produce high-density data in time and space. The main challenge of this low-cost approach regards the in-field accuracy and reliability of the sensors. This study presents the development of low-cost stations for high-time resolution measurements of CO2 and CH4 concentrations calibrated via an in-field machine learning-based method. The calibration models were built based on measurements parallelly performed with the low-cost sensors and a CRDS analyzer for CO2 and CH4 as reference instrument, accounting for air temperature and relative humidity as external variables.To ensure versatility across locations, diversified datasets were collected, consisting of measurements performed in various environments and seasons. The calibration models, trained with 70 % for modeling, 15 % for validation, and 15 % for testing, demonstrated robustness with CO2 and CH4 predictions achieving R2 values from 0.8781 to 0.9827 and 0.7312 to 0.9410, and mean absolute errors ranging from 3.76 to 1.95 ppm and 0.03 to 0.01 ppm, for CO2 and CH4, respectively. These promising results pave the way for extending these stations to monitor additional air contaminants, like PM, NOx, and CO through the same calibration process, integrating them with remote data transmission modules to facilitate real-time access, control, and processing for end-users.

Interactive remote electrical safety laboratory module in biomedical engineering education

To enable interactive remote education on electrical safety in biomedical engineering, a real-life problem-based laboratory module is proposed, implemented and evaluated. The laboratory module was implemented in a freestanding distance course in hospital safety for three consecutive years and was based on electrical safety for medical devices, where standard equipment existing in most hospitals could be used. The course participants were from a total of 42 geographical locations in or near Sweden. To allow a high level of interaction, especially among peer students, a graphical digital platform (Gather Town) was used. The digital platform was additionally used in two group work sessions. The experience of the participants in terms of usefulness and satisfaction was rated on a range of [-2, 2] using a van der Laan 5-point Likert-based acceptance scale questionnaire. The laboratory module overall was scored 4.1/5 by the participants (n = 29) in the final course assessments. The evaluation of the digital platform alone showed that in the first usage instance, the participants (n = 21) found the platform to be useful (0.54 ± 0.67) and satisfactory (0.37 ± 0.60). The participants’ experience of the digital platform improved when comparing two identical group work assignments so that ratings of usefulness and satisfaction were 1.11 ± 0.59 and 1 ± 0.71, respectively, after they had used it in the second group work session (n = 38). This study provides an instance of an interactive remote electrical safety laboratory module that is envisioned to contribute to further implementations of sustainable education in biomedical engineering.

Control of multi-energy drying system: Optimal weighted combination prediction of moisture content and fuzzy compensation of wind speed

In order to monitor the moisture content accurately and improve the drying uniformity of the same batch of materials, an online moisture monitoring approach based on optimal weighted combination model (OWCM) was developed, and a fuzzy control strategy of wind speed compensation was established for multi-field coexistence. The Human Machine Interface (HMI) and remote monitoring modules are designed, which can automatically obtain, view and store environmental parameters on site and mobile devices. The system was loaded into a kelp drying equipment, and moisture content prediction and drying uniformity verification tests were conducted respectively. The results showed that Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of the OWCM are 0.022 and 0.019, the prediction accuracy was better than that of single model and average weighted combined model (AWCM). The drying time difference between the front and back of the same batch of kelp was shortened from 1 ∼ 1.5 h to 0 ∼ 0.5 h. This study provides theoretical and technical support for the synergistic utilization of multiple energies and the research and development of aquatic products processing equipment.

Vision-inertial collaborative localization of multi-agents with remote interaction

In collaborative missions, it is crucial for each agent to have a clear understanding of the status among others. Therefore, various related works have been conducted, including virtual reality interactions and real-life swarm jobs. However, these types of collaborations still face certain limitations: (i) Limited distance: In virtual reality, users interact with others over a network within a predefined area and are unable to move over longer distances. (ii) Weak/non-GPS signals: Swarm jobs, which rely solely on localization information like GPS, often suffer from drift or interruptions. Moreover, significant location devices are rarely deployed in consumer-grade products. To address these challenges, we propose a multi-agent collaborative localization framework based on Camera, IMU (Inertial Measurement Unit), and a remote interaction module. This framework not only achieves globally consistent localization but also overcomes the distance limitations of WIFI or Bluetooth. Additionally, we tackle the issue of scale ambiguity in visual-inertial collaborative localization. Simulations and physical experiments validate the effectiveness of our proposed multi-agent collaboration with remote interaction. Unlike traditional applications that depend on external devices like Motion Capture Devices or GPS, our system achieves globally consistent localization internally.

Development of IoT-Based Remote Monitoring Module for Greenhouse Environment to Facilitate Crop Growth Data Analysis

Development of IoT-Based Remote Monitoring Module for Greenhouse Environment to Facilitate Crop Growth Data Analysis

EXPLORING MISSING LEARNING PHENOMENON IN PRESCHOOL SETTINGS DURING COVID-19 PANDEMIC: TEACHERS’ PERSPECTIVES

Purpose –This study aims to explore the missing learning phenomenon due to school closures during the COVID-19 pandemic in preschool settings from teachers’ perspectives in Selangor, Malaysia. Related studies have shown that missing learning phenomena from different settings leads to delayed literacy development and raises the risk of dropping out among children. There is a lack of in-depth documentation on the missing learning phenomenon among preschoolers exploring the socioecology of preschool settings in a local context. Methodology –This research employed a case study approach. In-depth interviews were conducted with six preschool teachers from Selangor, Malaysia, using an inductive approach for a holistic understanding of the missing learning phenomenon during the COVID-19 pandemic. The data were analyzed using Computer Assisted Qualitative Data Analysis Software (CAQDAS), NVivo version 12 software, which mapped the findings to understand further the ecosystem behind the preschoolers’ absence of learning during the COVID-19 pandemic. Findings – Three major themes were revealed from the data: the missing learning demographic, socioecological factors, and mitigation plans. Several sub-themes (the compensative learning solutions, the demographic of impacted people, the delayed progress, teachers’ readiness to facilitate online learning, engagement towards online learning, revised syllabus, personalized learning, and parental involvement) are classified under the respective major themes. Several main categories also emerged from the themes: lack of experiences and technology-pedagogical knowledge, unavailable online modules, low readiness to utilize online learning, unsupportive family climate, and accessibility. Learning intervention and online engagement with pupils during the pandemic are crucial in ensuring a successful continuous education. Significance – There is also a need for comprehensive remote instructional modules that consider socioecological actors – parentsand home climate; in the future and the enhanced instructional technology competency among preschool teachers.

Improving University Students' Critical Thinking and Problem-Solving Skills: How Problem-Based Learning Works during COVID-19 Pandemic?

With the COVID-19 pandemic spreading all around the world, higher learning institutions were forced to shut down or limit the people in contact to control the spread of diseases. Under this circumstance, remote learning that emphasized learning via online setting was embraced in higher education to replace the physical classroom during the pandemic time. This study designed a single Problem-Based Learning (PBL) module using remote learning to examine the students' experience in PBL, and to what extent the PBL module helps students improve their critical thinking and problem-solving skills. The remote learning PBL module was conducted using the reflection method to assess the students' experiences in PBL learning. On the other hand, a set of survey questionnaires was distributed to 34 undergraduate students to gather the responses for the assessment of critical thinking and problem-solving skills. This study employed both quantitative and qualitative analysis to investigate the students’ critical thinking, problem-solving skills and their experience in remote learning PBL. Using paired sample t-test to test the difference between pre- and post- remote learning PBL class, results indicated that there was a significant improvement in students’ critical thinking and problem-solving skills after remote learning PBL class. On the other hand, thematic analysis of students’ feedback on remote learning PBL class- first, second, and third meetings, indicated that students gradually improved their critical thinking and problem-solving skills. Although students implied positive feedback on the class, however, some of them were facing difficulties in understanding the module or physical disruptions that distracted their learning. The findings gave insights for the lecturers to design a suitable learning course during the pandemic time. Moreover, the findings highlighted challenges that gave insights for the lecturers to look at the students’ feedback from time to time to improve the learning mechanisms and to create a better learning environment.

Enhancing IoT Network Reliability: Evaluating LoRa Module Susceptibility to Interference

The Internet of Things (IoT) is gaining popularity, leading to the widespread use of remote communication modules (LoRa), known for their energy efficiency and wide coverage range. However, as the number of LoRa modules used in IoT networks grows, the possibility of interference from third-party devices operating at the same frequency becomes a concern. This study aimed to examine the vulnerability of LoRa modules to electromagnetic interference (EMI) when transmitting text messages and images. Radiation emission conditions were measured in the test area for evaluating LoRa module performance, and susceptibility to interference was assessed under non-line-of-sight (NLOS) conditions. The study's outcomes reveal that interference with LoRa transmitters has no noticeable effect on the range within a distance of up to 50 meters. In contrast, the interference power required to disrupt the LoRa receiver decreases with increasing distance. Additionally, interference from frequencies outside the designated LoRa working frequency (915 MHz) has no discernible impact on module performance. Introducing a delivery delay check demonstrates consistent performance even in interference. These findings deepen our understanding of the susceptibility of LoRa modules to tampering, emphasizing the importance of implementing effective disruption management strategies in IoT deployments. By considering the potential impact of electromagnetic interference (EMI) on LoRa modules, developers can design more robust IoT networks, ensuring reliable communication and improved system performance. Overall, the research focuses on the interference characteristics of LoRa modules, providing insights for developing resilient and interference-resistant IoT solutions. It underscores the necessity of addressing interference issues to ensure the reliable operation of IoT devices across diverse environments.

Automatic flaw detection of carbon fiber prepreg using a CFP-SSD model during preparation

As an intermediate material for carbon fiber composites, surface flaws inevitably occur during carbon fiber prepreg preparation, which will seriously affect the quality of carbon fiber composite products. The current approaches for identifying flaws on carbon fiber prepreg have the drawbacks of being labor-intensive and inefficient. This research puts forward a novel model for identifying surface flaws on carbon fiber prepregs using an improved single-shot multibox detector (SSD), called CFP-SSD model. A machine vision-based platform for surface flaws identification on carbon fiber prepreg is created. Additionally, the modified-Resnet50 backbone employed in the proposed CFP-SSD model can enhance the effectiveness of network feature extraction. Then, the multi-scale fusion remote context feature extraction module is designed to efficiently fuse the information from the shallow and deep layers. The findings of performance comparison experiments and ablation experiments indicate that the proposed CFP-SSD model achieves 86.63% mean average precision and a detection speed of 47 frames per second, which is sufficient for real-time automatic identification of carbon fiber prepreg surface flaws.

Design of Dual-tiltable Ducted-Fan Aircraft Based on Cross-coupling Network Control

In recent years, with the rapid development of drone technology, unmanned aerial systems have been widely applied in various fields. Although the flight control and airframe structure of traditional multirotor aircraft are fairly mature, they still face challenges such as low aerodynamic efficiency, low safety, and complex structure. In order to solve these issues, a dual-tiltable-ducted-fan aircraft system is designed. The system is equipped with an STM32F407 processor as the main controller, which receives motion control information from the remote control module. By employing cross-coupling network control methods, it coordinates the output values and tilt angles of the two channeling fans to achieve stable control of the aircraft's flight attitude.

Development of a low-power remote monitoring module for set-net fish school based on WCDMA

Development of a low-power remote monitoring module for set-net fish school based on WCDMA

Field Test Method and Equivalence Analysis of Delay Characteristics of DC Electronic Current Transformer

DC electronic current transformer is the data source of the system control and protection device, so its measurement delay has always been concerned. In this paper, the DC current transformer is modelled equivalently and the key factors affecting the delay of shunt and the remote module are analyzed. A field test method for the delay characteristics of the DC electronic current transformer is proposed. Moreover, a complex multi-state large current generator and integrated test system are developed. On the basis of the IEC 60044-8 standard transmission protocol, the accuracy of standard signal acquisition with the shunt is better than 0.2%. The maximum output current of the established testing system is 600 A. Based on the field test in an actual HVDC project, transient step and various frequency signal components are applied for analyzing.

Performance Evaluation of a Quadcopter by an Optimized Proportional–Integral–Derivative Controller

This paper presents an analysis of a quadcopter’s stability and its sensors’ data reading using an IMU (inertial measurement unit). Firstly, the angular velocity and acceleration data are read by an Stm® development board embedded with an Stm32f401ccu6 microcontroller. The altitude of the measurement instrument platform was determined using an MS5611 barometric pressure sensor combined with a temperature sensor. The quadcopter’s control was achieved by connecting a brushless DC motor to the Stm® board, which received four PWM (pulse-width modulation) signals via the output port. An electronic governor was utilized to control the brushless DC motor, while a pre-existing remote control was designated as the transmitter. The quadcopter receiver received a 2.4 GHz signal from the transmitter using the BLE (Bluetooth low-energy) protocol, which was used to ensure the simultaneous operation of the four brushless DC motors. Finally, a PID (proportional–integral–derivative) controller was employed for parameter adjustment. The collected PID parameter program was developed in the Simulink software as a simulation platform, allowing for the execution of the Simulink model on the Stm® MCU. The Stm® module facilitates monitoring of the performance of the UAV (unmanned aerial vehicle) and enables immediate parameter adjustments to ensure flight stability. This research aims to reduce calculation errors in sensor and controller usage and improve the efficacy of the remote machine module for future industrial applications.

Optical coherence tomography-based design for a real-time motion corrected scanning microscope.

While two-photon fluorescence microscopy is a powerful platform for the study of functional dynamics in living cells and tissues, the bulk motion inherent to these applications causes distortions. We have designed a motion tracking module based on spectral domain optical coherence tomography which compliments a laser scanning two-photon microscope with real-time corrective feedback. The module can be added to fluorescent imaging microscopes using a single dichroic and without additional contrast agents. We demonstrate that the system can track lateral displacements as large as 10 μm at 5 Hz with latency under 14 ms and propose a scheme to extend the system to 3D correction with the addition of a remote focusing module. We also propose several ways to improve the module's performance by reducing the feedback latency. We anticipate that this design can be adapted to other imaging modalities, enabling the study of samples subject to motion artifacts at higher resolution.