Hardware Components Research Articles

Development of a novel virtual reality-enabled remote monitoring device for maintenance of cathodic protection systems on oil and gas pipelines

Periodic inspections are required for oil and gas pipelines equipped with cathodic protection systems (CPS) to prevent corrosion. This inspection takes time and requires money, mobilisation of specialised staff, and accessibility of pipeline right of way which is often hindered by security issues, and bad terrain. A novel virtual reality-enabled remote monitoring device, developed using the NACE SP0169 standard, which measures the pipe-to-soil potential (PSP) reading, transmits the measured data to an IoT server, and a virtual environment for analysis and feedback while providing an immersive experience to the user, all in real-time, is presented. The hardware and software components are developed using Sensors, Arduino Mega 2560 board, AWS Sumerian 1.2.0 software, ThingSpeak IoT server, Blender modelling software and AutoCAD. When implemented on real test posts of oil and gas facilities and compared with the traditional methodology, the system showed consistency of data measurement and analysis, with real-time feedback to users, and a Spearman rank’s correlation coefficient of 0.998944. The study is significant as it provides the oil industry with an expert, easy-to-understand tool which helps to reduce the rate of oil spillage and losses through corrosion.

Cyberphysical System Modeled with Complex Networks and Hybrid Automata to Diagnose Multiple and Concurrent Faults in Manufacturing Systems

Cyber–physical systems use digital twins to provide advanced monitoring and control functions, including self-diagnosis. The digital twin is often conceptualized as a 3D model, but mathematical models implemented in numerical simulations are required to reproduce the dynamical and functional characteristics of physical systems. In this work, a cyber–physical system scheme is proposed to monitor and diagnose failures. The virtual system, embedded at the supervisory control level, combines concepts from complex networks and hybrid automata to detect failures in the hardware components and in the execution of the sequential logic control. An automated storage and retrieval system is presented as a case study to show the applicability of the proposed scheme. The functional test and the obtained results validate the implemented system that is shown to be capable of fault diagnosis and location in real time. The online execution of the digital twin present several advantages for diagnosing multiple concurrent failures in sensors, actuators, and the control unit. This approach can be incorporate into diverse manufacturing systems.

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

IoT-Based Mushroom Cultivation System with Solar Renewable Energy Integration: Assessing the Sustainable Impact of the Yield and Quality

The conventional method of mushroom cultivation can be labor-intensive and produce limited yields. Due to the humidity and temperature in the summer season, mushroom production is significantly diminished. The growth of each mushroom species depends on the consistency of care, the skill of experienced farmers, and crucial cultivation parameters such as temperature, humidity, irrigation, and exposure to sunlight. This study aims to implement an IoT-enabled cultivation system to control and monitor the environmental parameters of Indian mushroom cultivation within the proposed innovative framework, as compared to conventional methods. The IoT-based cultivation system consists of hardware components, circuit connections, software, and algorithms. This study confirms that consistent control of environmental parameters, such as temperature and relative humidity, by a dynamic climate promotes mushroom growth that is superior to conventional cultivation. Our findings reveal a substantial increase in the yield and quality of mushrooms, demonstrating the tangible advantages of applying an innovative approach. Traditional cultivation yielded an average of 4.118 kg, whereas IoT-based cultivation systems produced an average of 5.306 kg. The t-test statistic comparing yields has highlighted the significance of the observed differences with a p-value of 0.0000. The research contributions are to design and demonstrate the IoT-enabled system innovation with solar renewable energy, illustrating the effect of mushroom production and quality on the economic market analysis of mushroom cultivation in the direction of environmentally sustainable and green agricultural practices. This study’s comprehensive perspective can provide farmers, agricultural professionals, and policymakers with valuable insights regarding the future of mushroom cultivation, particularly the reduction of carbon emissions and energy consumption.

Designing, Optimizing, and Validating a Low-Cost, Multi-Purpose, Automatic System-Based RGB Color Sensor for Sorting Fruits

The use of automatic systems in the agriculture sector enhances product quality and the country’s economy. The method used to sort fruits and vegetables has a remarkable impact on the export market and quality assessment. Although manual sorting and grading can be performed easily, it is inconsistent, time-consuming, expensive, and highly influenced by the surrounding environment. In this regard, this study aimed to design and optimize the performance of a low-cost, multi-purpose, automatic RGB color-based sensor for sorting fruits. The proposed automatic color sorting system consists of hardware components including a machine frame, belt and pulleys, conveyor belt, scanning zone, plastic boxes, electric components (stepper motors, RGB color sensors, Arduino Mega, motor drivers), and software components (Arduino IDE version 2.2.1 and C++). Calibration was performed for the light intensity sensor to measure the light intensity inside the scanning zone, the conveyor speed sensor, and the RGB color sensors by testing the RGB color channels. The sensor, the height, conveyor belt color, and light intensity should be carefully adjusted to ensure a high performance of the color-based sorting system. The results showed that the appropriate sensor height ranged from 15 to 30 mm, the optimum color of the conveyor belt was black, and scanning the objects at a light intensity of 25 lux achieved the best output signals. The RGB color sensors achieved an analytical performance similar to that obtained with manual sorting without requiring the use of computers for image processing like other automatic sorting systems do in order to gather RGB data.

Advances in benchmarking and round robin testing for PEM water electrolysis: Reference protocol and hardware

While the number of publications in the PEM water electrolysis community increases each year, no common ground concerning reference hardware (test cells and test bench) and testing protocols has been yet established. This would, however, be necessary for the comparability of experimental results. First attempts for such reference hardware and procedures have been made in the framework of the Task 30 Electrolysis within the Technology Collaboration Programme on Advanced Fuel Cells (AFC TCP) of the International Energy Agency (IEA). Since then, improvements of both the test hardware (test cell and components) as well as the measurement protocol were identified, and a revised methodology and key results based on a comprehensive measurement series have been obtained. A detailed protocol for testing commercial reference components with a reference laboratory test cell developed in-house by Fraunhofer ISE is presented. For evaluation of the protocol and the hardware, it was tested at three different institutions at the same time. Impedance spectroscopic and polarization data was acquired and analyzed. The obtained differences in performance were calculated to give the community an expectation window to compare own data to. Finally, the importance of a thorough temperature control and the conditioning phase are demonstrated.

Discussion and Suggestions on Future Growth of OPPO

The mobile phone market is always changing. In recent years, fashionable and cheap mobile phones like OPPO have become consumers' preferences, and their market share is also expanding. This research will make predictions about the development of OPPO in the next five to ten years. To make the forecasts reliable and convincing, the SWOT model and data from "Counterpoint" and "The Economic Times" are used. Generally, the international mobile phone market is slowly recovering, but the shortage of hardware components for Chinese brands, such as OPPO and VIVO, and the crisis between Ukraine and Russia made the expected fast recovery fail. For OPPO, its expansion is restricted by China's policy of COVID-19 and it faces serious shortages on making some core hardware components, hence in the future 5 years, OPPO is not expected to occupy much market share. However, in a future decade, it is hard to say. Although the influence of China's COVID policy restriction and the Ukrainian War is expected to disappear, the key restriction for OPPO is the limitation on components. OPPO should develop some core components independently to reduce the impact of the external supply market on the company's expansion. In addition, OPPO pays more attention to offline sales, and its sales have been greatly affected during the COVID-19 period. In the future, OPPO can expand online and other channels and can flexibly switch if similar emergencies happen in the future.

ANALYSIS OF THE POSSIBILITY OF DEVELOPMENT AND IMPLEMENTATION OF A BASIC UNMANNED AIRCRAFT SYSTEM

The term “Basic Unmanned Aircraft System” refers to a comprehensive system encompassing both hardware and software components, forming an integral configuration aimed at unmanned aviation operations.
 The Unmanned Aircraft System, in its fundamental assembly, comprises an intricate interplay of technological components. These components, ranging from cutting-edge hardware to sophisticated software, collaborate harmoniously to execute tasks that were traditionally accomplished by manned aircraft.
 Collaboration between specialized enterprises and research institutions approach holds promise in terms of synergizing the respective expertise of these entities. This symbiotic partnership not only expedites the development process but also introduces the prospect of novel breakthroughs through the fusion of practical experience and theoretical knowledge.
 A paramount consideration is the host of advantages that could potentially be reaped from the realization of the Basic System. One such advantage is the projected increase in production volumes. This, in turn, could significantly bolster the capacity to meet defense orders in a shorter timeframe, thereby enhancing national security endeavors.
 Furthermore, the article delves into the catalytic effect this innovation could have on scientific research, particularly in prioritized domains. The development of the Basic System could potentially serve as a stimulus for intensified scientific inquiry. The complexity of its design necessitates advances in a multitude of scientific fronts, such as materials science, artificial intelligence, and robotics.

Implementation of School Management Information Systems at Vocational School State I Tomohon

This research discusses the implementation of the School Management Information System (SIMS) at SMK Negeri 1 Tomohon using the Rapid Application Development (RAD) method. School management, as a process of planning, organizing, directing, and controlling, is carried out by the school principal and his staff to achieve educational goals. The main goal of school management is to create an effective and efficient learning environment. Information systems, as entities with human, hardware, software, procedures, and data components, aim to collect, store, process, manage, and convey relevant information. SMK Negeri 1 Tomohon, as a vocational school in North Sulawesi, faces management challenges due to the use of conventional systems. Processes such as recording grades, registering students, compiling schedules, and collecting data on school fee payments often take time and are difficult. Therefore, this research is focused on implementing a School Management Information System using the programming languages PHP, HTML, CSS, and MySQL, with users consisting of Admin, Teachers, and Students, and using the RAD method. This research identifies problems in data management and school administration which are still manual, resulting in inefficiencies and potential errors. SIMS succeeded in making a positive impact with a structured interface, allowing easy access to information on grades, schedules, and learning activities. SIMS also facilitates systematic monitoring of student and teacher performance. This research concludes that SIMS can be an effective solution to support educational management at SMK Negeri 1 Tomohon with the potential for wider application in other school environments.

GPU propagation and visualisation of particle collisions with accurate model of ALICE detector magnetic field

The ALICE Collaboration at CERN developed a 3D visualisation tool capable of displaying a representation of collected collision data (particle trajectories, clusters and calorimeter towers) called the Event Display. The Event Display is constantly running in the ALICE Run Control Center as part of the Quality Assurance system, providing the monitoring personnel with visual cues about possible problems of both hardware and software components during periods of data gathering. In the software, particle trajectories (which are curved due to the presence of a magnetic field inside the detector) are generated from the physical parameters of detected particles, such as electrical charge and momentum. Previously this process in the Event Display used a uniform, constant magnetic field for these calculations, which differs from the spatial variations of the real magnetic field and does not model one of the two magnets used in the detector. Recently, a detailed model of the ALICE magnetic field was made available as a shader program for execution on the GPU. In this work we attempt to implement the reconstruction algorithm in a shader form as well, allowing us to combine it with the detailed model to create a full solution for rendering trajectories from collision event data directly on the GPU. This approach has several possible advantages, such as better performance and the ability to alter the magnetic field properties in real time. This was not previously done for ALICE and as such could be used in the future to upgrade the Event Display.

An activity-based approach for the early identification and resolution of problems in the development of IoT systems in academic projects

The development of Internet of Things (IoT) systems in university courses encourages students to use multiple skills. Hence, the importance of applying teaching methods like Project Based Learning (PBL) in the development of these kinds of systems for integrating hardware and software components while facing numerous real-life problems. This study presents an activity-based Approach for the Early Identification and Resolution of problems, in a checklist format, to be used by students for preventing them from wasting time in IoT academic projects. The checklist is based on an adapted taxonomy of problems in IoT systems. This study analyzed problems identified in 48 projects carried out by 183 engineering students registered in two courses in 2020 and 2021. For designing the structured checklist, we categorized 14 types of IoT problems, analyzed root causes and solutions, and created and evaluated a taxonomy of problems.

Multi‐Energy X‐Ray Linear‐Array Detector Enabled by the Side‐Illuminated Metal Halide Scintillator

AbstractConventional scintillator‐based X‐ray imaging typically captures the full spectral of X‐ray photons without distinguishing their energy. However, the absence of X‐ray spectral information often results in insufficient image contrast, particularly for substances possessing similar atomic numbers and densities. In this study, an innovative multi‐energy X‐ray linear‐array detector is presented that leverages side‐illuminated X‐ray scintillation using the emerging metal halide Cs3Cu2I5. The negligible self‐absorption characteristic not only improves the scintillation output but is also beneficial for improving the energy resolution for the side‐illuminated scintillation scenarios. By exploiting Beer's law, which governs the absorption of X‐ray photons with different energies, the incident X‐ray spectral can be reconstructed by analyzing the distribution of scintillation intensity when the scintillator is illuminated from the side. The relative error between the reconstructed and measured X‐ray spectral is < 5.63%. This method offers an additional energy‐resolving capability for X‐ray linear‐array detectors commonly used in computed tomography (CT) imaging setups, surpassing the capabilities of conventional energy‐integration approaches, all without requiring extra hardware components. A proof‐of‐concept multi‐energy CT imaging system featuring eight energy channels is successfully implemented. This study presents a simple and efficient strategy for achieving multi‐energy X‐ray detection and CT imaging based on emerging metal halides.

Reconfigurable hybrid micro-grid with standardized power module for high performance energy conversion

This paper proposes a reconfigurable power module system for hybrid micro-grid to reduce the designing cost with standardized software and hardware components. The developed system is composed of three layers including application function layer, interconnection layer and physical layer with the capability to be interfaced with different types of energy resources for the hybrid micro-grid. By implementing the multi-layer power module system, the energy conversion designing procedures for different types of resources can be generalized and automated with less cost on the specified application scenarios. The control functions for different energy resources can be extracted from the application function layer. The desired number of standardized power modules can be integrated from the physical layer to form different power converter topologies. The coordination of the power converter, micro-controller, sampling, high level control is managed by the interconnection layer to construct the complete energy conversion system. The major advantageous results cover three aspects. Firstly, the proposed reconfigurable system generalizes the energy conversion of the hybrid micro-grid with different AC and DC resources. Secondly, the designing procedures of the hybrid micro-grid energy conversion system are simplified with less cost for various interfaced applications. Thirdly, the energy conversion performance and reliability of the micro-grid is improved with standardized power modules and self-restoration capability. The experimental test verified the proposed system.

Enabling the Ocean Internet of Things with Renewable Marine Energy

Marine renewable energy can play an integral role in reducing the cost and complexity of collecting data from the oceans, and enhancing its exploitation. The processing and transmission of data at sea may be modelled as an `internet of things' (IoT) application. The `thing' is any offshore device which can collect and process data in-situ, while the `internet' represents the medium for transmitting data. IoT is differentiated from other internet based communication paradigms by the constraints on the system. These constraints are typically limited energy budgets and computing power, intermittent and low-bandwidth connectivity, and limited physical access. While land based IoT applications are already well served by a wide selection of hardware and software components, the needs of offshore IoT applications are not well served. Utilizing marine energy can advance the adoption of IoT at sea by providing in-situ energy generation, whilst also benefitting from the same technology. The Sustainable Energy Authority of Ireland funded `BlueBox' project aims to overcome barriers to entry for applying IoT technologies to offshore sensing by developing Ocean IoT (OIoT) hardware and software solutions. Features of the BlueBox system include modular offshore focussed hardware, no-code configuration and control of peripherals (such as sensors and actuators), duplex transmission of data using multiple media, serverless cloud server architecture and an edge computing framework. This paper presents an overview of BlueBox, tank tests for system validation of a prototype wave-energy powered ocean-observing platform, and a discussion of future applications of the technology.

Space Communication Network in the New Era: Architecture, Key Technologies, and Challenges

Space communication network (SCN) is a feasible and flexible solution to enable global seamless coverage, as well as service orchestration in a wide range. It's emerged as a promising perspective for the next-generation communication network. However, the design of SCN architecture with both efficiency and security remains an open challenge. In this paper, we propose a new system architecture for SCN, along with new hardware components, such as the collaborative edge gateway, the reconfigurable label-based switch, etc. Meanwhile, three core capabilities of the proposed architecture are elaborated, including structural collaborative security, efficient adaptive communication, and distributed service orchestration. Firstly, as for single node of SCN has weak security capability, the structural collaborative security aims to establish a strengthened security structure among nodes. Through security associations and strategy collaborations, nodes in the structure can cooperate to resist large-scale distributed attacks. Secondly, instead of fixed coverage and limited protocol exchange, the efficient adaptive communication introduces communication resource adaptation to realize on-demand resource scheduling, and introduces transmission protocol adaptation to support more heterogeneous connections. Thirdly, to solve the efficiency problem of centralized orchestration in a wide area, a smart agent with a learning-based Pattern-Matching Library is constructed, namely, a distributed component to execute near real-time service orchestration, which uses decomposing-based orchestration optimization to accomplish a lower service latency. In addition to the key technologies, some future research directions are also provided for enlightening the researchers.

WIRELESS BLACK BOX FOR VEHICLE USING IOT

The project aims to develop a wireless black box system for vehicles using IoT technology. The system will collect data from various sensors installed in the vehicle, such as GPS, accelerometer, gyroscope, and camera, and transmit the data wirelessly to a cloud-based data storage and processing system. The data will be processed and analyzed using advanced data analysis and visualization techniques to provide insights into vehicle performance and driver behavior. The system will also provide driver feedback in real-time, helping to improve driving behavior and reduce the risk of accidents. The project will involve the design and development of hardware and software components, as well as testing and deployment of the system in vehicles. The wireless black box system has the potential to revolutionize the transportation industry by providing real-time data on vehicle performance and driver behavior, which can be used to improve safety, reduce fuel consumption, and optimize fleet management

An effective fault tolerance aware scheduling using hybrid horse herd optimisation‐reptile search optimisation approach for a cloud computing environment

AbstractIT services can be requested via cloud computing, a model based on services as well as the Internet. It includes all computer systems resources from hardware components to software platforms and software applications in a distributed environment. Scheduling is a key step in processing tasks using remote resources. Serious issues have been brought forward, including the ineffective use of resources and task execution failure. The concurrent provision of fault tolerance and resource optimisation is achallenging task. In the context of cloud computing, this research offers a brand‐new job scheduling and fault‐tolerant system. Tasks submitted by users are taken as an input for the proposed method. Several virtual machines (VM) are initially arranged for scheduling work and execution process. Initially, Horse Herd Optimisation is employed here to allocate the job based on key factors such as deadline and user budget. Once the jobs are assigned to each VM, then each job's deadline is confirmed and transferred to VM which has sufficient capacity. Here, the Reptile Search Optimisation technique is applied to identify the VM error. Any VM that does not have enough capacity is the one that has a problem. When a fault is found, a fault‐tolerant process is instantly started. A replication‐based fault‐tolerant mechanism is used in this manuscript. The proposed approach is tested with several metrics which attains better performance like 80 s response time, turnaround time of 32 s, 17% resource utilisation and a success rate of 92%. Thus the designed model is the best choice for fault‐tolerant aware task scheduling.

Remotely controlled water channel system for laboratory education utilizing internet of things and SCADA technologies

This paper was discussed the hardware components of a remotely controlled water channel management system for laboratory education utilizing the internet of things(IoT) and supervisory control and data acquisition systems (SCADAs). The system consists of various sensors and devices included the air pressure sensor (mpx5010dp), water pressure sensor, ultrasonic distance sensor (JSNSR04T) and solenoid water valve plastic. The air pressure sensor (mpx5010dp) was used to detect the water level in the manometer of the pitot tube, a water pressure sensor for detecting the pressure of water, an ultrasonic distance sensor (JSN-SR04T) for detecting the level of water in the channel, a solenoid water valve plastic with relay for protecting the motor when the water level in the tank reduces to 5 cm. These components work together to monitor and control the water channel system remotely, providing users with a more scalable, flexible, and accessible solution for laboratory education. Also, a web page was developed with an IoT and SCADA system for remote control and management of a water channel system that was used for teaching hydraulic and hydrological concepts to students.

Time-Frequency Domain Non-Orthogonal Multiple Access for Power Efficient Communications

We propose a power efficient non-orthogonal multiple access (NOMA) scheme suitable for Internet of Things (IoT) and device-to-device (D2D) communications. OFDM-based power-domain NOMA (PD-NOMA) is one of the promising approaches to achieve simultaneous connections of massive devices. Nevertheless, the problem of high peak-to-average power ratio (PAPR) is a major challenge, since power amplifier (PA) efficiency is a critical factor for IoT and D2D devices consisting of low-cost hardware components. This paper overcomes this problem by introducing time-frequency domain NOMA (TF-NOMA), where OFDM and DFT-spread OFDM (DFT-s-OFDM) are superposed over the time-frequency domain. By utilizing the low PAPR property achieved by DFT-precoding, TF-NOMA can efficiently reduce the PAPR of the downlink signal transmitted by the base station (BS) as well as the uplink signals of the devices located far from BS. As a result, the proposed TF-NOMA can operate with higher PA efficiency than the conventional OFDM-based PD-NOMA. Furthermore, the insertion of DFT-precoding with the aim of PAPR reduction also enhances the error propagation resistance due to the resulting Gaussian mixture signal property. Throughout the mathematical analysis and computer simulations, we demonstrate that TF-NOMA achieves better error rate performance than the conventional PD-NOMA with significant improvement of PA efficiency.

A Unified Approach for Beam-Split Mitigation in Terahertz Wideband Hybrid Beamforming

The sixth generation networks envision the deployment of terahertz (THz) band as one of the key enabling property thanks to its abundant bandwidth. However, the ultra-wide bandwidth in THz causes beam-split phenomenon due to the use of a single analog beamformer (AB). Specifically, beam-split makes different subcarriers to observe distinct directions since the same AB is adopted for all subcarriers. Previous works mostly employ additional hardware components, e.g., time-delayer networks to mitigate beam-split by realizing virtual subcarrier-dependent ABs. This paper introduces an efficient and unified approach, called beam-split-aware (BSA) hybrid beamforming. In particular, instead of virtually generating subcarrier-dependent ABs, a single AB is used and the effect of beam-split is computed and passed into the digital beamformers, which are subcarrier-dependent while maximizing spectral efficiency. Hence, the proposed BSA approach effectively mitigates the impact of beam-split and it can be applied to any hybrid beamforming architecture. Manifold optimization and orthogonal matching pursuit techniques are considered for the evaluation of the proposed approach in multi-user scenario. Numerical simulations show that significant performance improvement can be achieved as compared to the conventional techniques.