Hardware Design Research Articles

A single‐channel transmitarray antenna with abilities of super resolution and digital beamforming

AbstractA single‐channel transmitarray antenna with abilities of super resolution and digital beamforming (DBF) is proposed. The amplitude and phase distributions on the array aperture are reconstructed through beam switching with a single channel. By finding and solving relations between distributions and received signals of beams, aperture distributions can be reconstructed. The ill‐conditioned problem caused by limited scanning range and angular interval is solved using the regularization method. The obtained distributions can then be delivered to super‐resolution algorithm to obtain super resolution, or used to produce shaped beams by DBF. On the basis of the proposed theory, a bifocal beam‐reconfigurable transmitarray is designed and tested as a single‐channel DBF antenna without special and additional hardware design. It has the outstanding advantages of low cost, simple structure, low energy consumption, and high working frequency.

Unveiling robust security: Chaotic maps for frequency hopping implementation in FPGA

Frequency hopping is a main technique for wireless communication, avoiding interference and interception. This paper provides novel hardware design for frequency-hopping pseudorandom bit generator (PRBG).PRBG design by chaotic maps on FPGA.Two proposed methods in this work first combine chaotic maps in a cascade manner called fixed point cascade chaotic maps (FPCCM-FHSS), and second, the conjunction of chaotic maps done in an XORed manner called fixed point an XOR chaotic method (FPXORCM-FHSS).The results were the first eight NIST randomness tests.Frequency indicates that all p-values larger than 0.01 are needed to achieve better randomness,Second and third were die-hard tests, many distribution tests with significant p-values (p <0.01) that meet high standards of statistical randomness, making them suitable for channel security.Last were the FPGA results between the proposed methods for speed and hardware resources).The works implemented on XILINX ZC702 achieved 2 Gbps to meet the speed requirements of the change of the carrier frequency.

AI Optimization-Based Heterogeneous Approach for Green Next-Generation Communication Systems.

Traditional heterogeneous networks (HetNets) are constrained by their hardware design and configuration. These HetNets have a limited ability to adapt to variations in network dynamics. Software-defined radio technology has the potential to address this adaptability issue. In this paper, we introduce a software-defined radio (SDR)-based long-term evolution licensed assisted access (LTE-LAA) architecture for next-generation communication networks. We show that with proper design and tuning of the proposed architecture, high-level adaptability in HetNets becomes feasible with a higher throughput and lower power consumption. Firstly, maximizing the throughput and minimizing power consumption are formulated as a constrained optimization problem. Then, the obtained solution, alongside a heuristic solution, is compared against the solutions to existing approaches, showing our proposed strategy is drastically superior in terms of both power efficiency and system throughput. This study is then concluded by employing artificial intelligence techniques in multi-objective optimization, namely random forest regression, particle swarm, and genetic algorithms, to balance out the trade-offs between maximizing the throughput and power efficiency and minimizing energy consumption. These investigations demonstrate the potential of employing the proposed LTE-LAA architecture in addressing the requirements of next-generation HetNets in terms of power, throughput, and green scalability.

Robotic technology in Autism intervention: Design and application of the CARS cat-like robot

This study introduces a novel robotic system designed to aid individuals with Autism Spectrum Disorder (ASD) in enhancing their social communication and interaction skills. Incorporating advanced artificial intelligence, sensors, and image recognition technologies, the robot simulates human social interactions and provides tailored feedback, aiming to improve the quality of life for individuals with ASD. Through a detailed examination of hardware design, software functionalities, and data processing mechanisms, this paper evaluates the system's practical applications and identifies ongoing challenges and potential improvements. The findings suggest that while the robotic system significantly enhances social interaction and learning for autistic individuals, challenges such as technological adaptability, cost, and physical design require further innovation. This research contributes to the field of assistive technologies by offering insights into how robotic systems can be optimized to meet the unique needs of the autism community, thus paving the way for more effective therapeutic tools.

Electronic Load Device for Testing DC Power Supply

The project deals with a programmable electronic load device capable of dynamic variations of its load parameters to simulate a myriad of electrical conditions. Hence, one of the objectives of this paper is to implement, in a designed setup, variously heated loads, such as constant current, voltage, resistance, and power modes. That said, the designed system has hardware and software aspects that integrate advanced microcontroller capabilities so that high accuracy is assured through a series of test procedures on the system. The hardware design of the project encompasses choosing various resistors and relays modules (ESP32), selection of the proper power supplies, and microcontrollers. A program is being developed in the Arduino IDE that will program the microcontroller to do dynamic load control.It all began with the circuit design and resistor value choice, taking into consideration their power rating about effective heat dissipation. Dynamic loading control by the ESP32 microcontroller allows variable changes which are automatic in nature. On top of this, relay modules were used for effective switching of load and its adjustments, hence making the system flexible and responsive. The firmware developed in Arduino IDE automates control processes, which enables the smooth running of operations. In this regard, our experiments output results that show the device—a programmable electronic load mimicking load situations and providing performance information. Notably, the automated control system coupled with adjustable load capabilities increased the testing process efficiency and accuracy to a great deal. The overall effect of the programmable electronic load device is that it makes testing more professional by way of automation and provision of precise management for the test settings of the load. Its versatility also provides simulation of a wide scope of scenarios accommodating test conditions. It is designed to cater to heat regulation and power dispersion for the reliability of performance whiles in operation

Design of energy efficient N-bit vedic multiplier for low power hardware architecture

ABSTRACT In this paper, we introduce an advanced design of an N-bit Vedic multiplier using Nikhilam Sutra and Karatsuba algorithms, tailored for low power hardware architectures. Our approach innovatively combines these ancient mathematical techniques to significantly enhance computational efficiency in digital systems. The primary novelty of our method lies in its capability to drastically reduce both power consumption and operational delay. Compared to conventional multipliers, our design demonstrates an average area reduction of 56% and a latency reduction of 45%. Additionally, the integration of the Karatsuba algorithm optimises the structural design of the multiplier, further lowering the requirements for computational units. This dual-sutra approach not only optimises energy efficiency but also enhances overall effectiveness, making it highly suitable for image and signal processing as well as biomedical applications where power efficiency is crucial. By explicitly stating these key advancements, we aim to clearly communicate the significant strides our research has made in the field of energy-efficient hardware design.

Classification of water quality based on dissolved solids and turbidity parameters with the utilization of total dissolved solids sensor and turbidity sensor

Clean water quality is essential for public health, but its scarcity is increasing amid population growth and industrialization. Monitoring turbidity and total dissolved solids (TDS) is essential to determine the quality of clean water. This study addresses the urgent need for accurate and reliable water quality monitoring to test the applicability of TDS and turbidity sensors in taking measurements, aiming to develop efficient monitoring solutions for public health and sustainable water management. The TDS sensor operates according to the principle of electrical conductivity, with a range of 0 to 1000 ppm and an accuracy of ±10%. The turbidity sensor detects water turbidity by determining the level of turbidity particles. The ESP32 microcontroller integrates Wi-Fi and USB capabilities. The hardware and software design ensures accurate sensor readings, which are critical to successful water quality measurement and monitoring. The test results show satisfactory accuracy of the TDS sensor with an average error of 0.09% and good accuracy of the turbidity sensor with an average error of about 1.536%. Concerning the above two parameters, in this study, among 15 water samples, seven were clean, meeting the standard, while eight water samples were dirty, exceeding the limit, making them unsafe for human consumption.

Hardware design and the fairness of a neural network

Hardware design and the fairness of a neural network

Implementasi Smart Brankas Berbasis Internet Of Things Pada PT. Umbi Teknologi Indonesia

The IoT-based smart safe represents a cutting-edge innovation in secure valuables storage. The aim of this research is to develop, implement and evaluate an intelligent and secure system connected to the Internet of Things (IoT). The development method involves the integration of hardware and software design with sensor technology and network connectivity. Implementation is achieved by deploying the smart safe within home or office environments connected to the internet. System evaluation is conducted through a series of tests focusing on security, functionality, and reliability. The research findings demonstrate that IoT-based smart safes offer enhanced security access, real-time monitoring, and user convenience through mobile applications. These findings have significant implications for improving secure storage across various contexts, from households to businesses

Design of a Real-Time Monitoring System for Electroencephalogram and Electromyography Signals in Cerebral Palsy Rehabilitation via Wearable Devices

Cerebral palsy is a disorder of central motor and postural development, resulting in limited mobility. Cerebral palsy is often accompanied by cognitive impairment and abnormal behavior, significantly impacting individuals and society. Time, energy, and economic investment in the rehabilitation process is substantial, yet the rehabilitation outcomes often remain unsatisfactory. Additionally, some patients have limited sensory perception during rehabilitation training, making it challenging to effectively regulate exercise intensity. Traditional evaluation methods are mostly based on recovery performance, lack guidance at the neurophysiological level, and have an unequal distribution of medical rehabilitation resources, which pose great challenges to the rehabilitation of patients. Based on the issues mentioned above, this paper proposes a real-time cerebral signal monitoring system based on wearable devices. This system can monitor and store blood oxygen, heart rate, myoelectric, and EEG signals during cerebral palsy rehabilitation, and it can track and monitor signals during the rehabilitation treatment process. The system includes two parts: hardware design and software design. The hardware design includes a data signal acquisition module, a main control chip (ESP32), a muscle electrical sensor module, a brain electrical sensor module, a blood/heart rate acquisition module, etc. It is primarily for real-time signal data acquisition, processing, and uploading to the cloud server. The software design includes functions such as data receiving, data processing, data storage, network configuration, and remote communication and enables the visual monitoring of data signals. The system can achieve real-time monitoring of electromyography, electroencephalography, and blood oxygen levels, as well as the heart rate of patients with cerebral palsy, and adjust rehabilitation training in real-time during the rehabilitation process. At the same time, based on the real-time storage of the original electromyography and electroencephalography data, it can provide auxiliary guidance for later rehabilitation evaluation and effective data support for the entire rehabilitation treatment process.

A Systematic Translation Validation Framework for MLIR-Based Compilers

This paper introduces an innovative translation validation framework designed for MLIR-based compilers, which has garnered considerable prominence in fields such as machine learning, high-performance computing and hardware design. Despite rigorous testing, compilers based on MLIR might still induce incorrect results and undefined behaviors, necessitating verification work. Our framework first takes a pair of MLIR programs as inputs and check their function signature’s compatibility before encoding them into SMT expressions. Then it uses the Z3 SMT solver to check whether the target program refines the source program. Our framework transcends the dialect limitations of past solutions, thereby providing validation support to a wider range of MLIR-based compilers. We demonstrate its effectiveness through evaluations on prominent open-source MLIR-based compilers, where we identified bugs and undefined behaviors. We further demonstrate the capability of this framework by validating two practical deep-learning accelerator designs.

Improved DOA estimation of MEMS vector hydrophone combined with CEEMDAN and wavelet transform for noise reduction

PurposeCiliated microelectromechanical system (MEMS) vector hydrophones pick up sound signals through Wheatstone bridge in cross beam-ciliated microstructures to achieve information transmission. This paper aims to overcome the complexity and variability of the marine environment and achieve accurate location of targets. In this paper, a new method for ocean noise denoising based on improved complete ensemble empirical mode decomposition with adaptive noise combined with wavelet threshold processing method (CEEMDAN-WT) is proposed.Design/methodology/approachBased on the CEEMDAN-WT method, the signal is decomposed into different intrinsic mode functions (IMFs), and relevant parameters are selected to obtain IMF denoised signals through WT method for the noisy mode components with low sample entropy. The final pure signal is obtained by reconstructing the unprocessed mode components and the denoising component, effectively separating the signal from the wave interference.FindingsThe three methods of empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD) and CEEMDAN are compared and analyzed by simulation. The simulation results show that the CEEMDAN method has higher signal-to-noise ratio and smaller reconstruction error than EMD and EEMD. The feasibility and practicability of the combined denoising method are verified by indoor and outdoor experiments, and the underwater acoustic experiment data after processing are combined beams. The problem of blurry left and right sides is solved, and the high precision orientation of the target is realized.Originality/valueThis algorithm provides a theoretical basis for MEMS hydrophones to achieve accurate target positioning in the ocean, and can be applied to the hardware design of sonobuoys, which is widely used in various underwater acoustic work.

Time-Aware Spectrum-Based Bug Localization for Hardware Design Code with Data Purification

Time-Aware Spectrum-Based Bug Localization for Hardware Design Code with Data Purification

Phasor-based analysis of a neuromorphic architecture for microwave sensing

This article presents a design procedure for implementing artificial neural networks (ANNs) using conventional microwave components at the hardware level with potential applications in radar and remote sensing. The main objective is to develop structured hardware design methods for implementing artificial neurons, utilizing microwave devices to create neuromorphic devices compatible with high-frequency electromagnetic waves. The research aims to address the challenge of encoding and modulating information in electromagnetic waves into a format suitable for the neuromorphic device by using frequency-modulated information instead of intensity-modulated information. It also proposes a method for integrating principal component analysis as a dimensionality reduction technique with the implementation of ANNs on a single hardware. As a dummy task, the process outlined here is used to implement an artificial neural network at the hardware level, with a specific emphasis on creating hardware that is capable of performing matrix multiplications in the form of dot products while also being able to extract the resulting data in an interpretable manner. The proposed implementation involves the use of directional couplers to implement weights and sample the resulting signal at specific intervals to obtain the multiplication result.

Design and implementation of embedded hardware in furniture control based on DSP

The continuous progress of embedded technology and Internet of Things technology has accelerated the arrival of the era of home intelligence. By designing a smart home control system based on embedded DSP technology, it can detect temperature, humidity, flammable gas leakage, smoke, fire, and other indicators in the home environment, and carry out intelligent control of the detected security risks. The core of the system is the smart home management terminal, which is responsible for the network interconnection inside and outside the home. Terminal hardware includes a high-speed DSP chip, various interface modules, and so on. The software adopts the C/OS-II operating system to realize multi-task processing. This paper briefly summarizes DSP technology and embedded technology, and proposes the composition of intelligent home control system based on embedded DSP technology, as well as the hardware and software design and implementation of the system. Through the smart home system, users can control home conditions and obtain public service information anytime and anywhere, which is highly practical.

Визначення оптимальних норм надійності космічного апарата з урахуванням економічних показників

The goal of this paper is to develop a method for determining the values of system failure rates optimal in terms of net profit maximization with account for spacecraft mass limitations. It is adopted that the spacecraft systems are independent in terms of reliability, each of them can be only in two states (a functioning state or a failure state), and each equipment type of the special complex makes an independent contribution to the overall effect. The paper considers the case where the spacecraft system failure time obeys the exponential law. Use is made of the Lagrange multiplier method and numerical optimization methods. The problem is solved using the mass ? failure rate and cost ? failure rate relationships of the spacecraft systems. For the supporting complex, the dimension of the mathematical simulation problem is reduced to two: a formula is derived to find the optimal failure rates of all the systems of the supporting complex using the optimal failure rates of two systems of it. The variables for the special complex and the supporting complex are separated. Due to the fact that each special complex system makes an independent contribution to the overall effect, the problem for the whole spacecraft is reduced to a system of two equations for the special complex and the supporting complex and ncn equations in one variable for the special complex with two coupling variables between the supporting complex and the special complex where ncn is the number of the special complex systems. The paper presents a numerical-and-analytical method for spacecraft system failure rate optimization where the initial guess is specified indirectly: by specifying the supporting complex mass and probability of no-failure operation. The method may be used in the development of a space hardware design methodology accounting for economic factors. From the optimal values of the spacecraft system failure rates found using the mass ? failure rate and cost ? failure rate relationships, one can find the masses and costs of the spacecraft systems to be used in optimizing the parameters and development cost of the systems. The method is expected to increase the profitability and competitiveness of spacecraft under development.

Study on Integrated Systems for Enhanced Forest Fire Prevention: An Embedded Intelligent Video Analysis and Collaborative IoT–Fog–Cloud Framework Approach

Introduction:: Forest fires have been a major hazard to forest management, needing sophisticated monitoring and management techniques. By creating an embedded intelligent video analysis system, this research proposed a complete strategy for addressing this difficulty. Method:: The system's hardware architecture was explained, and the operating system software was detailed, using a software and hardware design based on the ZynqSoC. At the same time, an emphasis on forest fire prevention applications was maintained. Furthermore, the study investigated a unique technique for forest fire detection using Arduino as a field data collector and a fuzzy logic algorithm to improve accuracy. Results:: The proposed IoT-Fog-Cloud collaboration infrastructure offered a patented contribution to real-time wildfire monitoring, prediction, and forecasting. The framework achieved excellent accuracy in determining wildfire proneness levels and real-time alert production by utilizing fuzzy K-nearest-neighbor classification and Holt-Winter's forecasting model. Conclusion:: The findings demonstrated the integrated system's ability to reduce the impact of wildfires, serving as a significant reference for future forest fire prevention scenarios.

Design and implementation of deep learning-based object detection and tracking system

Many human tracking methods by deep learning rely on powerful computing resources. For embedded platforms with limited resources, efficient use of resources is a priority. In this paper, we design an object detection and tracking system based on deep learning methods. We propose an efficient system with software and hardware design. We apply the framework of Vitis AI and its Deep Learning Processing Unit using a hardware/software co-design approach. This approach capitalizes on a higher-level acceleration design framework, where the convolutional models can be updated more flexibly and rapidly. This design approach not only provides a fast design flow but also has good performance in terms of throughput. We facilitate the design and accelerate the object detection model YOLO v3 to achieve higher throughput and energy efficiency. Our tracking method achieves a 1.27x improvement in processing speed with the addition of a single-object tracker. Our proposed human tracking methods can achieve better performance than the others in precision with the same test sequences.

Hardware circuit design of intelligent fast charger control system

Hardware circuit design of intelligent fast charger control system

The monitoring system of running state data of converter station equipment based on sensor information and 3D positioning algorithm

Abstract The stable operation of multiple equipment in the converter station can ensure the safety of the DC transmission system. Once the fault occurs, it will pose a threat to the safety and stability of the power grid. It is necessary to monitor the running state of all kinds of equipment, and study the monitoring system of the running state data of the converter station equipment based on sensor information and a three-dimensional positioning algorithm. In terms of hardware design, TCP and IP communication protocols are used to connect the sensors, and the sensors are arranged according to the vibration conduction standard, constituting a three-layer monitoring architecture of monitoring center, sensor, and equipment. The sensor module is connected by interface, and the structure of the connecting control board for sensor data transmission is set to increase the flexibility of sensor nodes. In software design, the basic information of converter station equipment is corresponding to sensor technology, and the database of operating equipment is established. A three-dimensional positioning algorithm is used to determine the data output form, detect the running state data of the converter station equipment, and complete the system design. The experiment takes various types of running data as the test object. Under the system application in this paper, different running data can be correctly classified and data monitoring under various states can be realized, which has application value.