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19th ieee Sensors applications symposium (SAS)

作者： Villaverde, Marti Gasulla, Manel Reverter, Ferran Univ Politecn Catalunya BarcelonaTech Dept Elect Engn Castelldefels Barcelona Spain

ISBN: (纸本)9798350369267;9798350369250

In the context of powering indoor sensor nodes from the ambient optical energy, an experimental test of lowarea photovoltaic (PV) cells under real indoor operating conditions for some weeks is proposed and carried out herein. The study involves PV cells of different technology (i.e., monocrystalline, amorphous, organic, and III- V type) and days with different weather (i.e., sunny, partly-cloudy, cloudy, and rainy). The experimental results show that, in a sunny day, the average (per day) power density can be up to 118 mu W/cm(2) for the monocrystalline technology. This corresponds, for an active area of 10 cm(2), to an average power of more than 1 mW, which is an acceptable value for a low-power sensor node. In a cloudy day, the average power density is around 25 mu W/cm(2) for the monocrystalline, provided that the room under test is at the top floors of the building. However, under only the effects of artificial lighting, the average power density is really low, to be precise: less than 2 mu W/cm(2) for the monocrystalline. This value increases up to 13 mu W/cm(2) for the III-V cell, but this is an expensive technology. Therefore, the energetic survival of an indoor low-cost sensor node needs to leverage the natural light.

关键词： artificial lighting autonomous sensor energy harvesting indoor applications PV cell

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Microwave Resonators embedded With Carbon Nanotubes for real-time Gas Sensing

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ieee SENSORS JOURNAL 2024年第4期24卷 4325-4333页

作者： Kao, Hsuan-Ling Tsai, Yun-Chen Chang, Li-Chun Chiu, Hsien-Chin Chang Gung Univ Dept Elect Engn Taoyuan 33302 Taiwan Chang Gung Univ Ctr Reliabil Sci & Technol Taoyuan 33302 Taiwan Chang Gung Mem Hosp Dept Dermatol Taoyuan 33305 Taiwan Ming Chi Univ Technol Dept Mat Engn New Taipei 243303 Taiwan Ming Chi Univ Technol Ctr Plasma & Thin Film Technol New Taipei 243303 Taiwan

This study proposed the application of microwave resonators embedded with carbon nanotube (CNT) sensing films fabricated using inkjet printing technology as gas sensors. The density and uniformity of CNTs dominated resistance, which was related to inkjet printing droplet spacing (DS), layer numbers, and electrode patterns. Although the high-density resistive-type CNT (DS = 20 mu m and 20 layers) sensor with the regular electrode (RE) pattern had a lower response than the low-density CNT (DS = 30 mu m) sensor, its response presented a narrow repeatability distribution. The response of the high-density CNT sensor with interdigital electrode (IDE) pattern can be improved and was even higher than that of the low-density CNT sensor with the RE pattern. Based on the results of resistive-type sensors, the frequency responses of the CNT films with DS = 20 and 30 mu m, 20 layers, and the IDE pattern embedded into transmission-type resonators were studied. During NH3 absorption, the insertion and return losses of the resonator embedded with the sensing film with DS = 20 mu m and 20 layers increased, whereas those of the resonator embedded with the sensing film with DS = 30 mu m and 20 layers decreased. The resonator frequency of both films increased because the CNT resistance increased during NH3 absorption. These results indicated that the frequency response of the microwave sensors was related to the resistance of CNT films. A transmission-type microwave resonator can provide multidimensional frequency responses and high repeatability and has the potential for integration with the IoT and RFID for wireless gas-sensing applications.

关键词： Carbon nanotube (CNT) gas sensor inkjet printing microwave resonant

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A real-time Detection embedded Edge Computing System Based on SNN-ONNX Model Deployment Inference 4

A Real-time Detection Embedded Edge Computing System Based o...

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4th International symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Tan, Binhong Li, Linjing Ma, Mengting Cao, Kaiming Chen, Bo Huo, Jianwen Tan, Liguo Li, Beibei School of Information Engineering Southwest University of Science and Technology Mianyang China School of Cyber Engineering Sichuan University Chengdu China School of Clinical Medicine Tsinghua University Beijing China School of Astronautics Harbin Institute of Technology Harbin China

ISBN: (纸本)9798331541729

With the development of neural network technology, Spiking Neural Networks (SNNs) have shown great potential in edge computing and embedded systems due to their biologically inspired and low-power characteristics. This paper proposes an optimization method based on a custom LIF neuron model to solve the problem of operator conflicts that arise during the conversion of trained SNNs models to ONNX format. By replacing the official LIF neuron model with a custom LIF neuron and achieving cross-framework deployment after model conversion, the method was successfully applied to an embedded system for real-time image classification tasks, meeting the real-time detection requirements in edge computing environments. This method not only completes the hardware implementation of the SNNs model, but also significantly improves its portability and interoperability in embedded systems. © 2024 ieee.

关键词： Neural network models

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Optimizing Deep Learning on Sustainable embedded Systems: A Study of Handwritten Digit Recognition with CNN and OpenCV

Optimizing Deep Learning on Sustainable Embedded Systems: A ...

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2024 ieee Region 10 Conference, TENCON 2024

作者： Kok, Chiang Liang Ho, Chee Kit Vicknesh, R. Lee, Charles Koh, Yit Yan College of Engineering The University of Newcastle Australia Singapore Institute of Technology Singapore

ISBN: (纸本)9798350350821

This senior thesis develops a real-time handwritten digit identification system using a Raspberry Pi 3B+ with a camera module, leveraging a lightweight CNN optimized with MNIST. The project highlights the effective implementation of deep learning on edge computing devices through seamless integration of CNN, TensorFlow Lite, and OpenCV's real-time image processing. The system is both cost-effective and precise, enabling real-time digit recognition tasks. This proposed work illustrates the potential of AI applications in education, industry, and commerce, setting the stage for future advancements in embedded AI systems. © 2024 ieee.

关键词： Convolutional neural networks

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Towards Mutation Testing of embedded Software: A Framework and Case Study 35

Towards Mutation Testing of Embedded Software: A Framework a...

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35th ieee International symposium on Software Reliability Engineering Workshops, ISSREW 2024

作者： Jiang, Wei Dong, Sijin Zhang, Jiaming Tang, Jin Zhang, Zichao Sun, Chang-Ai Zhang, Xiaoyi China Electronics Technology Group Corporation Information Science Academy Beijing China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing China

ISBN: (纸本)9798350367041

embedded software commonly executes safety-critical tasks and thus is expected to be highly reliable, which calls for stronger quality assurance techniques. As a fault-based testing technique, mutation testing is widely recognized to have stronger fault detection capability than those coverage or function-based testing techniques. However, some unique features of embedded software, such as limited hardware resources, real-time requirements, and differences between development and execution environments, pose challenging issues for the application of mutation testing. In this study, we explore the application of mutation testing to embedded software. As a result, we propose a mutation testing framework for embedded software, and evaluate the simulation capability of mutation operators for real-life faults in embedded software. A case study was conducted on a realistic open-source embedded software to evaluate the effectiveness and efficiency of the proposed technique. The experimental results demonstrate that mutation testing is able to detect various faults of embedded software, thus delivering a promising supplement for embedded software testing. © 2024 ieee.

关键词： Case Study embedded software Mutation Operators Mutation testing Software testing

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Development of Dynamic Platform with MEMS Microphones Array embedded for UAV Detection and Tracking 11

Development of Dynamic Platform with MEMS Microphones Array ...

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11th ieee International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan) - Empower of Innovative Consumer technology

作者： Cheng, Chin-Yi Saputra, Ilham Lin, Chih-Wei En, Shi-Chen Natl Yunlin Univ Sci & Technol Dept Mech Engn Touliu Yunlin Taiwan

ISBN: (纸本)9798350386851;9798350386844

This study introduces a dynamic platform with a micro-electromechanical system (MEMS) microphone array for robust unmanned aerial vehicle (UAV) detection and tracking. Leveraging the compactness of MEMS technology, the platform integrates microphones to capture UAV acoustic signatures using Direction of Arrival (DOA) and Beamforming technologies. Its adaptability optimizes surveillance coverage, surpassing the limitations of visual tracking in adverse conditions. This research details the design, calibration, and integration processes, validated through rigorous testing. This innovation improves real-time situational awareness, offering a promising solution for security and defense applications.

关键词： real-time Surveillance Direction of Arrival UAV Detection MEMS Microphone Array

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Employing an embedded Renderer as Recognition Tool for Odometry, Map-Building, Navigation, and Localization on Active Sensing Robotics

IEEE Journal on Indoor and Seamless Positioning and Navigati...

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ieee Journal on Indoor and Seamless Positioning and Navigation 2024年 2卷 275-291页

作者： Kunbum, Park Takeshi, Tsuchiya The University of Tokyo Department of Aeronautics and Astronautics Bunkyo-ku113-8654 Japan

This study proposes a method that employs a renderer as a tool for environmental recognition. In the proposed system, features are extracted from sensors and cameras;the renderer represents scenes in a 3-D space to suit the purpose of the applications, and the applications resample the scenes to achieve their purpose after manipulating the renderer. As an example, this study presents implementation mechanisms of environmental recognition - odometry, map-building, navigation, and localization of automotive indoor robots. This method has a higher computational cost than typical feature-based methods;however, the algorithms are considerably intuitive. Although commercial rendering engines cannot be used as they are, a lightweight rendering engine dedicated to recognition can operate in embedded systems to enable real-time recognition. In addition, this study presents an experiment that corresponds to the simulation of moving robots indoors. In conclusion, this study proposes a change from the perspective of adopting a renderer-a well-established software technology that has been thoroughly investigated and can manipulate space-as an essential tool in the recognition framework. © 2023 CCBY.

关键词： Robots

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On Tiny Feature Engineering: towards an embedded EMG-based hand gesture recognition model 9

On Tiny Feature Engineering: towards an embedded EMG-based h...

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9th symposium on Edge Computing

作者： Gomez-Bautista, Andres D. Mendez, Diego Alvarado-Rojas, Catalina Mondragon, Ivan F. Colorado, Julian D. Pontificia Univ Javeriana Sch Engn Bogota 110231 Colombia Pontificia Univ Javeriana Sch Engn iOMICAS Bogota 110231 Colombia Pontificia Univ Javeriana Sch Engn iOMICAS Cali 760031 Colombia

ISBN: (纸本)9798350378290;9798350378283

Robotic-based therapy is becoming a very popular treatment for the rehabilitation of hand function impairment as a consequence of strokes, due to the high-dimensional and less interpretable nature of superficial electromyography (sEMG) signals. In this context, feature engineering becomes particularly important to estimate the intention of upper limb movements by utilizing machine learning models, specially when a hardware embedded on-board implementation is expected, due to the strong computational, energy and latency constraints. Our work compares the performance achieved by implementing four state-of-the-art feature techniques (random forest, minimum redundancy maximum relevance (MRMR), Davies-Bouldin index, and t-tests), when these are evaluated on a sEMG dataset intended for training hand gesture classifiers. The results of three different machine learning algorithms (neuronal networks, k-nearest neighbors and bagged forest) are used as a reference to validate the analysis. This ongoing research has revealed valuable information on the potential and constraints of these 4 feature generation methods for real gesture recognition embedded applications.

关键词： EMG feature engineering gesture recognition hand movement rehabilitation machine learning

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real-time Reduced Model of Active Distribution Networks for Grid Support applications

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ieee TRANSACTIONS ON POWER DELIVERY 2023年第5期38卷 3531-3540页

作者： Prasad, Manorath Rather, Zakir Hussain Razzaghi, Reza Doolla, Suryanarayana IITB Monash Res Acad Mumbai 400076 India Indian Inst Technol Dept Energy Sci & Engn Mumbai 400076 India Monash Univ Dept Elect & Comp Syst Engn Melbourne Vic 3800 Australia

Seeking to reduce the computational effort to model the intrinsically complex active distribution networks (ADNs), this article proposes a new realistic approach to develop a real-time reduced steady-state model of an ADN using synchrophasor measurements. Such models facilitate much needed co-simulation of the bulk power system (BPS) and multiple ADNs for grid support applications. With the advent of distribution-level phasor measurement units (D-PMUs), the synchrophasor data are employed to derive the reduced model parameters in real-time and track the time-varying ADN operating point. The proposed approach develops a general three-phase four-wire reduced model which can replace any arbitrary feeder configuration confined within D-PMUs. The explicit modelling of neutral-wire under different neutral-grounding conditions results in accurate representation of any unbalanced and complex feeder segment, containing transformers, distributed generators, loads and n-phase laterals. Further, the reduced model is modified to account for embedded distributed generation, which is useful for effective estimation of grid support capability at the transmission-distribution interface. The proposed reduced model has been extensively validated on the highly unbalanced ieee-13 bus feeder system for various test cases, including high penetration of locally-controlled photovoltaic inverters. DIgSILENT PowerFactory MATLAB co-simulation has been used as the platform to establish the model accuracy.

关键词： Active distribution network (ADN) bulk power system (BPS) distribution-level phasor measurement unit (D-PMU) grid support network reduction transmission-distribution co-simulation TSO-DSO coordination

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embedded System for Efficient Brain Stroke Prediction using CSML on PYNQ-Z2 1

Embedded System for Efficient Brain Stroke Prediction using ...

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1st ieee International Conference on Advances in Signal Processing, Power, Communication, and Computing, ASPCC 2024

作者： Dwibedi, Sudhansu Ranjan Biswal, Pradyut Kumar International Institute of Information Technology Electronics and Telecommunication Engineering Bhubaneswar India

ISBN: (纸本)9798350355093

This paper proposes an embedded system for efficient, real-time brain stroke prediction. While many machine learning techniques achieve high accuracy, their implementation on embedded platforms remains challenging. The solution utilizes a Correlated Supervised Machine Learning (CSML) method implemented on PYNQ-Z2 board, optimized through the PYNQ framework. Various classifiers are evaluated, with performance measured by F1 Score, Accuracy, Precision, Recall, and AUC-ROC. Additionally, power consumption and resource utilization are analyzed, demonstrating the system's suitability for real-time healthcare applications with low computational overhead. © 2024 ieee.

关键词： embedded systems

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