Embedded Computer Systems Research Articles

A new optimal space vector modulation with DTC switching strategy for induction motor control

Efforts to achieve swift and precise dynamic torque control have been central in AC drive research. Recent advancements in embedded computer systems have highlighted direct torque control (DTC) and field-oriented control (FOC) as key methods for enhancing torque dynamics, both utilizing space vector modulation (SVM) to optimize voltage source inverter positioning. This study introduces a novel synthesis by integrating DTC with SVM to address limitations in conventional DTC, which suffers from limited voltage vector availability, leading to undesirable torque behavior and significant current fluctuations. The primary goal is to develop an optimal switching modulator for the fastest torque response through the combined application of DTC and SVM. The proposed strategy optimizes DC bus usage, reduces torque fluctuations, minimizes total harmonic distortion in AC motor current, decreases switching losses, and ensures seamless digital system integration. Simulations using MATLAB/SIMULINK demonstrate significant torque, current, and flux linkage ripple reductions, validating the approach's effectiveness. This integration overcomes established limitations, extending the capabilities of motor control methodologies and offering enhanced performance and operational integrity in induction motor drive systems.

Artificial Intelligence and its Use in the Field of Education

Abstract: The purpose of this study was to assess the impact of Artificial Intelligence (AI) on education. Premised on a narrative and framework for assessing AI identified from a preliminary analysis, the scope of the study was limited to the application and effects of AI in administration, instruction, and learning. A qualitative research approach, leveraging the use of literature review as a research design and approach was used and effectively facilitated the realization of the study purpose. Artificial intelligence is a field of study and the resulting innovations and developments that have culminated in computers, machines, and other artifacts having human-like intelligence characterized by cognitive abilities, learning, adaptability, and decision-making capabilities. The study ascertained that AI has extensively been adopted and used in education, particularly by education institutions, in different forms. AI initially took the form of computer and computer related technologies, transitioning to webbased and online intelligent education systems, and ultimately with the use of embedded computer systems, together with other technologies, the use of humanoid robots and web-based chatbots to perform instructors' duties and functions independently or with instructors. Using these platforms, instructors have been able to perform different administrative functions, such as reviewing and grading students' assignments more effectively and efficiently, and achieve higher quality in their teaching activities. On the other hand, because the systems leverage machine learning and adaptability, curriculum and content has been customized and personalized in line with students' needs, which has fostered uptake and retention, thereby improving learners experience and overall quality of learning.

Intra-class deep learning object detection on embedded computer system

<span lang="EN-US">Implementation of artificial intelligence tends to be portable, mobile and embeds in embedded computer system (EBD). EBD is a special-purpose computer with limited capacity in a small-form size. Deep learning (DL) had known as cutting edges for object recognition. With DL, object feature extraction analysis is omitted. DL requires large computing resources and capacity. Implement DL algorithm on EBD goal to achieves high detection accuracy and high-efficiency resources. Hence, be able to cope with intra-class variations, and image disturbances. By those challenges and limitations, this study reports the performance of EBD to recognize an object which has high variations in their class, through an optimal raw-input dataset. The raw-input dataset performed optimization process with a supervisor. Yield is the proper optimal input dataset in size. The performance results observed begin from training dataset until evaluation stage of DL. The comparison performs in efficiency resources, loss, validation-loss, timesteps, and detection accuracy by multiclass confusion matrix analysis. This study shows through this purpose method efficient resources are highly archived. Shorter timesteps ensure training stage is successful, and detection accuracy is perfectly archived. In addition, this study proves DL method archived great performances in classifying object that has identical structure.</span>

Artificial intelligent based teaching and learning approaches: A comprehensive review

<span lang="EN-US">The goal of this study is to investigate the potential effects that Artificial intelligence (AI) could have on education. The narrative and framework for investigating AI that emerged from the preliminary research served as the basis for the study’s emphasis, which was narrowed down to the use of AI and its effects on administration, instruction, and student learning. According to the findings, artificial intelligence has seen widespread adoption and use in education, particularly by educational institutions and in various contexts and applications. The development of AI began with computers and technologies related to computers; it then progressed to web-based and online intelligent education systems; and finally, it applied embedded computer systems in conjunction with other technologies, humanoid robots, and web-based chatbots to execute instructor tasks and functions either independently or in partnership with instructors. By utilizing these platforms, educators have been able to accomplish a variety of administrative tasks. In addition, because the systems rely on machine learning and flexibility, the curriculum and content have been modified to match the needs of students. This has led to improved learning outcomes in the form of higher uptake and retention rates.</span>

Development and Implementation of an Energy-Efficient Test Stand for Railway Car Bogies

The bogies of railway cars are important components of the rolling stock system. The test stand solution that we have developed and proposed is used for testing car bogies under load to inspect and highlight the features that ensure operational safety and energy efficiency. This article presents the development and manufacturing of a prototype test stand for railcar bogies, incorporating specific elements such as hydraulic pressure cylinders, force transducers, displacement transducers, a hydraulic pumping system, a data computation and processing system, as well as a control and command unit. The technical topic of developing the test stand is aimed at testing bogies under a controlled, variable and uniformly distributed load, closely simulating the operational conditions of railcar bogies. The accurate and complete determination of the bogie's parameters assures the railroad operator that they are safely interchangeable—Moreover, decreasing the time spent on testing tasks and increasing the testing process efficiency through process automation is leading to a cutback in energy consumption and better predictability of the time intervals required for the repair of railway cars. The prototype consists of three hydraulic pressure cylinders: a centrally located hydraulic cylinder exerting a maximum pressing force of 20 tons-force and two lateral hydraulic cylinders, each applying a maximum pressing force of 10 tons-force. The hydraulic cylinders operate independently from each other, also supporting asymmetric load distributions that recreate the operating conditions as faithfully as possible. The data processing system monitors the magnitudes of the forces and the displacement of the hydraulic cylinders for reporting the specific characteristics of the bogie. To ensure rapid response in the control of the testing process, a control logic unit was developed, entirely dedicated to the control of this technological process. The graphical user interface of the embedded computer system was designed in the LabVIEW programming environment.

Simulator for Time-Triggered Organic Computing

Nowadays, the complexity of embedded computing systems is increasing due to applications with increasing functional and nonfunctional requirements, e.g., performance, reliability, and energy efficiency. Organic computing has emerged as a research area for handling complex distributed embedded computer systems and is inspired by the organization of biological entities. It provides improved adaptability, robustness and has reduced development efforts. However, organic computing has drawbacks in terms of determinism, composability, and dependability, which are key features for safety-critical applications. Distributed computing systems using time-triggered communication networks have these characteristics and therefore offer distinct advantages for safety-critical systems. By combining organic computing, including artificial DNA and hormone features, with time-triggered communications, we can make these systems more safe, reliable, and suitable for safety-critical applications. Therefore, in this paper, we present a time-triggered organic computing architecture in combination with a simulation tool, in which tasks of an application are executed according to a predefined schedule. Our paper introduces multiple use cases to demonstrate the concepts and the system model. The obtained results from simulation show improved temporal predictability and fault containment of the system.

DEVISING ARCHITECTURE FOR REMOTE EDUCATION ORGANIZATION BASED ON A SINGLE-BOARD COMPUTER

The presented paper sets the goal of providing computer engineering courses based on a single-board computers (SBC) with the organization of the remote education process. The devised approach relies on the connection to the local area network (wired or wireless) of the university, making the board accessible to the internal users, and creation of a network tunnel between the remote user and connected parts. These actions are accompanied by assignments of necessary permissions to the users of the system. First, the requirements of each involved actor were considered and as a result of that further understanding of the network communication process, network management and administration, software requirements, etc. was acquired. According to these results, analysis of the capabilities of SBC in terms of its connectivity was performed and, finally, the architecture was realized on the available hardware with regard to the peculiarities of the specific subject. The article establishes all the necessary details on the implementation of the proposed architecture and discusses results of the testing performed as a part of the specific course. During the testing stage, the deployed system based on FriendlyARM Nano Pi allowed us to organize the course on Real-Time Embedded Computer Systems and successfully finish all related activities under circumstances of remote education. It was demonstrated that the proposed organization is reliable as demonstrates conceivable performance even under condition of multiple simultaneous connections to the target board. From the administrative point of view, the solution is highly configurable which is a huge advantage for the lecturer and for the administrator. The devised architecture has a potential in terms of improvement and scalability because it consumes relatively low network capacity and is easy to deploy under any circumstances.

Quadrotor Real-Time Simulation: A Temporary Computational Complexity-Based Approach

The interaction of digital systems with dynamic systems requires synchrony and the accomplishment of time constrains, so the simulation of physical processes needs an implementation by means of real-time systems (RTS). However, as it can be expected, every simulation and/or implementation might demand too many computational resources, surpassing the capacity of the processor used by computational systems. This is the reason for the need to perform a temporary computational complexity analysis based on the study of the behavior of the execution times of the implemented simulation. In this regard, the Real-Time Operating Systems (RTOS) feature time managing tools, which allow their precise measurement and the establishment of scheduling criteria in process execution. Therefore, this research proposes accomplishing a temporary computational complexity analysis of the real-time simulation by an embedded system (ES) of an unmanned aerial vehicle (UAV) propelled by four rotors. Derived from this analysis, formal definitions are elaborated and proposed, which establish a close relationship between the temporary computational complexity and typical real-time temporary constraints. To the best of the author’s knowledge, the definitions presented in this article have not been reported in the literature. Furthermore, to perform the temporary computational complexity analysis of the UAV, the mathematical modeling based on the Euler–Lagrange approach is presented in detail. Finally, simulations were performed using a real-time system implemented on the Embedded Computer System (ECS) Raspberry Pi 2 Model B+, in order to validate the suggested definitions.

Development and application of an embedded computer system for CubeSats exemplified by the OPS-SAT space mission

The space industry is one of today’s major growth markets and a very interesting business sector for innovation, science, and technology. In the last century, the space industry has dramatically changed and undergone strong commercialization referred to as “New Space”. In addition to the commercialization, the concept of CubeSats has become well established in the market during the last decade. The European Space Agency (ESA) has acknowledged this trend and uses CubeSat nanosatellites for projects like the OPS-SAT mission. OPS-SAT uses state-of-the-art embedded systems for various tasks. These embedded systems are the key for the great mission success of OPS-SAT and provide outstanding computational power for various experiments conducted with the OPS-SAT flying laboratory. This paper describes the fundamental design of these embedded systems and discusses some of the related achievements during the OPS-SAT mission.

Digital medical instrument based on embedded computer system

Digital medical instrument based on embedded computer system

Digital medical instrument based on embedded computer system

Digital medical instrument based on embedded computer system

Optimizing the convolutional neural networks for resource-constraint hardwares

Convolutional neural networks (CNNs) play an important role in many computer vision applications such as object classification and recognition. To achieve high recognition rate, these neural networks are usually implemented on high-performance computing platforms with high processing speed and large memory. This is a big obstacle for deploying these models on devices with limited hardware resources such as embedded computers. For convolution layers, it requires a lot of multiply-accumulation operations to extract useful features from input images. Furthermore, multiplication of floating-point numbers has long latency and demands a big hardware overhead. In this paper, we analyze and identify the causes that limit the performance of CNNs. Then a method for implementing convolutional networks on hardware with limited resources is presented. Performance evaluation in terms of power, execution time as well as recognition rate is presented in detail. Experimental results on both the FPGA hardware platform and the ARM Cortex-A embedded processor indicate that CNNs using the XNOR-popcount approach can be optimized to achieve a 1000-fold increase in computational performance and approximately a 24-fold reduction in power consumption compared to the tranditional implementation of CNNs on common embedded computer systems.

RETRACTED ARTICLE: An energy-efficient reconfigurable accelerators in multi-core systems using PULP-NN

Emerging developments in embedded computer systems and applications demand low energy consumption and high performance. Owing to increased demand for low-voltage computing and lowered technology returns, academia and industry are interested primarily in energy-efficient accelerators. Hardware accelerators have the greatest disadvantage that they are not programmable. It can also be misused for a particular task. The number of accelerators in a device can cause scalability problems. Flexibility and scalability issues are present in programmable accelerators. Coarse-grained reconfigurable architecture (CGRA) design, implementation, computer systems integration and compilation for CGRA are the key contributions in this proposed design. First of all in parallel ultra-low-power processing system (PULP), the CGRA-based integrated programmable array (IPA) is implemented. Second, PULP-NN is a coding library that has been developed for the RISC-V cluster with parallel, high–low storage. The key development in PULP-NN is that the latest move towards aggressive quantization of deep neural network inferences which is a collection of kernels which use bytes and sub-byte information types up to INT-1. The library in the proposed procedure utilizes advanced sign handling expansions in the RISC-V PULP processors and in bunch matches, to accomplish ideal energy effectiveness of estimation execution.

Research on the Design of Intelligent Data Acquisition Platform for Wireless Monitoring of Rotating Machinery Based on Arm

Rotating machinery is the most extensive type of machinery in the industry, which is the key equipment in many industries. Therefore, once the rotating machinery fails, it will cause huge economic losses, which requires us to monitor and diagnose the equipment status. Therefore, the rotating mechanical equipment must have an intelligent data acquisition system, which can collect the state of mechanical operation. Through real-time information collection, the rotating machinery can be monitored and diagnosed in real time, which will reduce the accident shutdown rate and maintenance costs. Therefore, the rotating machinery can reduce the production cost, which will avoid rabbit accidents and ensure the safety of production. Arm is an embedded computer system, which can be used for intelligent data collection flexibly. Firstly, this paper analyzes the application of embedded system in the rotating machinery monitoring system. Then, the hardware scheme and software of the system are designed.

Protecting COVID-19 Vaccine Transportation and Storage from Analog Cybersecurity Threats

Protecting COVID-19 Vaccine Transportation and Storage from Analog Cybersecurity Threats

ColMap: A memory-efficient occupancy grid mapping framework

In order to possess a significant degree of autonomy, a robot must be able to perceive its environment and store a representation of that environment for use in tasks such as localisation, navigation, collision avoidance, and higher decision making. It must do this subject to constraints on memory and processing power typical of the embedded computer systems commonly found on small robotic devices. These constraints are particularly important for flying robots (i.e. unmanned aerial vehicles), for which weight must be minimised. The challenge of storing a detailed map of a large area on a small embedded computer has led to the development of many algorithms that exploit the sparsity of typical maps to create a more memory-efficient representation. In this paper, we demonstrate that the verticality of both natural and man-made structures can be exploited to create a framework that can store occupancy grid maps efficiently, without causing additional computational burden. The new framework achieves an order-of-magnitude reduction in memory footprint relative to widely-used occupancy grid mapping software, while also achieving a slight speed-up in map insertion and access times. We also make available LIDAR scans taken from a hexacopter of an indoor flight arena that can be used to assist in evaluating future mapping and SLAM developments.

RETRACTED: Embedded computer system in hospital and atomized intelligent monitoring of children's respiratory diseases

Single-compartment model described in the alveolar partial pressure of carbon dioxide in exhaled breath, since the recording time based on the scene design. Respiratory parameters, use this model to estimate, then the clinical status and obstructive pulmonary disease in a patient. Methods: consider appropriate assumptions, a derive the analytical solution of the model, described in the section for children breath. The proposed framework integrates three new technical contribution: active shape model using a weighted allocation, using the graph cut segmentation Asymmetry unexpected objects removed, and the use of heterogeneous information theory measures the severity of a medical system quantization lung segmentation. A simple mechanical model allows estimation of respiratory parameters from the subject children, and may be applied to the measurement of these variables and the diagnosis and monitoring of chronic reversible obstructive lung disease suction size, then through the same qualitative trend study night. The results showed that the derivative and tidal volume the size of the measure is to attract an agent on behalf of the original waveform breathing. Relative sizes of the tidal volume suction maturation degree by changing the sleep state may be maintained potentially be used for quantitative pathology, or respiratory control.

Design and Implementation of an Automated Lighting System

A programmable logic controller is a digitally operated system used in an industrial environment that uses a programmable memory to implement specific functions to control through digital or analogue inputs and outputs of various types of machines. This report used a typical application for PLC's lighting control in a building for an office environment. The proposed design must define an appropriate office with various areas or rooms needing lighting with multiple control signals, the lighting controlled by a Siemens LOGO PLC (type 6ED1 052-1MD00-0BA5). The design has four relay outputs and eight digital inputs configured as analogue inputs. The scheme designed must be unique to meet the minimum requirements, including a provision for emergency evacuation if the radiation levels exceed a critical threshold. The system must use both analogue inputs but used for different purposes, and the analogue input level ranges must be significantly different. The relay logic has controlled by rules derived from an original relay logic using an embedded computer system. It optimises the control tasks to perform rugged designs to withstand vibrations, temperature, humidity, and electrical noise designs that allow a vast expansion. This circuit will be developed and simulated using the LOGO comfort software and then implemented on the PLC hardware. It includes diagrams and a description that clearly describes how the system should operate.

RETRACTED: Clinical monitoring and misoprostol for early embryo abortion based on embedded computer system

Abstract Abortion, under certain circumstances, is legal in India. It can be done for a variety of reasons for up to 20 weeks of gestation. In exceptional cases, the court, there is a possibility to end after 24 weeks. At the time of 2017, safety, there is a binary classification of unsafe Abortion. India has a law of liberal Abortion. The World Health Organization (WHO), in the death of 76,000 women with complications and treatment of unprocessed, mainly developing countries, has been estimated to be incomplete Abortion every year. Care of post-abortion, all reproductive health and international, and general terms used in the walk of life associated with implementing a particular service, all-natural and artificial Abortion, refer to the experienced woman. The maternal mortality rate must be the provision of health services to increase after Abortion. Misoprostol, women, must easily access women to carry out post-abortion health management is not access otherwise. Adequately trained, as long as safety is a nurse, supported, including the outpatient clinic, it can provide post-abortion care services in the first row. Tablets of contraception and safe abortion services misoprostol, to prevent unsafe Abortion, are connected to reduce the need for abortion aftercare. The health of the woman is the better treatment method to solve the complications.

Control and data acquisition software of the high‐energy particle detector on board the China Seismo‐Electromagnetic Satellite space mission

AbstractThe China Seismo‐Electromagnetic Satellite (CSES) space mission—also known as Limadou in Italian—is a scientific collaboration between China and Italy that aims to investigate the structure and dynamics of the iono/magnetosphere, and in particular to study the possible correlation of perturbations to the occurrence of high‐magnitude seismic events. The Chinese satellite houses the Italian high‐energy particle detector (HEPD), an apparatus composed of a silicon tracker and a calorimeter system, which detects electrons and protons in the energy ranges 3–100 and 30–200 MeV, respectively. The satellite was launched on February 2, 2018; after a commissioning phase dedicated to the setting of an optimal configuration, HEPD is fully operational since July 28, 2018. After a general overview of the CSES‐Limadou mission, this article presents the structure of the HEPD apparatus and describes the design and implementation of the software for the embedded computer system that is responsible for HEPD management. The onboard software runs on the digital signal processors of two electronic boards (CPU and data acquisition), monitors system status, handles instrument data acquisition, performs periodic calibration of the subdetectors, performs data compression, and communicates with the satellite. An overview of HEPD in‐flight operations and performance is given in the last section.