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An Energy Measurement Framework for 5G RAN Using USRP and real-time Monitoring 18

An Energy Measurement Framework for 5G RAN Using USRP and Re...

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18th ieee International Conference on Advanced Networks and Telecommunications Systems, ANTS 2024

作者： Centofanti, Carlo Venkateswarlu, Gudepu Santos, Jose Tella, Rajashekhar Reddy Marotta, Andrea Graziosi, Fabio Kondepu, Koteswararao University of l'Aquila Disim Department L'Aquila Italy Indian Institute of Technology Dharwad Dharwad India Ghent University - Imec IDLab Department of Information Technology Gent Belgium

ISBN: (纸本)9798350391725

Beyond 5G (B5G) networks, expected to support applications requiring ultra-low latency, high data rates, and dense connectivity, may increase energy consumption, especially in the Radio Access Network (RAN), which accounts for about 75% of total mobile network energy usage. We present an architecture for precise measurement of RAN energy consumption by monitoring the gNB radio interface implemented with Universal Software Radio Peripheral (USRP) and OpenAirInteraface (OAI). real-time measurements from the GW Instek GPM-8213 power meter allowed us to analyze energy consumption patterns during various gNB operation phases. Our results show precise measurement and differentiation of energy usage during user transmission, enabling exact operational cost quantification. This architecture enables energy measurements in other mobile scenarios, paving the way for advanced network management use cases and more energy-efficient B5G operations. © 2024 ieee.

关键词： 5G mobile communication systems

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Towards real-time Analysis of Marine Phytoplankton Images Sampled at High Frame Rate by a YOLOX-based Object Detection Algorithm

Towards Real-time Analysis of Marine Phytoplankton Images Sa...

引用

OCEANS Conference

作者： Wang, Jiacongan Tang, Cheng Li, Jianping Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781665418218

Rapid and quantitative analysis of phytoplankton cells in natural seawater is of great need for marine ecological science research and harmful algae bloom monitoring applications. In this paper, we propose a YOLOX network-based object detection algorithm exclusively for high-throughput real-time analysis of phytoplankton fluorescence images collected by the FluoSieve (R) imaging flow cytometer. Based on an active learning strategy, we first annotate and construct a FluoPhyto dataset of red tide phytoplankton species fluorescence images commonly found in the South and East China Sea, which contains a total of 30,339 images in 32 different categories. Using the dataset, we train the Faster-RCNN, SSD, YOLOv3 and YOLOX networks, and the comparison result shows that the performance of YOLOX network outperforms the other networks, which can reach a mean average precision (mAP) of 90.9%. The trained YOLOX model is then deployed on an embedded GPU module and the inference speed is tested to reach 20 fps with the help of TensorRT optimization, which can hopefully meet the real-time detection requirements of the instrument. In addition, the algorithm is run on the embedded platform for detection of images collected in a red tide event that happened near the Pearl River Estuary, and the key parameters such as abundance and size spectrum of the dominant species, Cochlodinium geminatum, are obtained, which confirms the feasibility and superior performance of the detection algorithm.

关键词： phytoplankton object detection imaging flow cytometry machine vision embedded system

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Hand Gesture Recognition for Traffic Signals Based on Improved Lightweight Convolutional Neural Network 2

Hand Gesture Recognition for Traffic Signals Based on Improv...

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2nd International Conference on Artificial Intelligence and Computer Information technology, AICIT 2023

作者： Dai, Fanzhe Yi, Xianjun Chai, Siyi Wuhan Institute of Technology Dept. School of Electrical Information Wuhan China

ISBN: (纸本)9798350302950

Gesture recognition is a crucial aspect of the development of intelligent transportation systems. In this paper, we propose a novel method for recognizing gestures of artificial traffic signals on embedded devices using a lightweight convolutional neural network (CNN). Our approach adopts GhostNetV2 as the base model and improves it by incorporating the MobileNeXt Hourglass block, resulting in GhostNetV2-A, which effectively reduces the size of the convolutional layers and enhances the device's operational capability under limited conditions. In terms of hardware, we replaced the original SPI flash with a 32GB storage card, used a smaller display screen, and added a user button to address the limitations of OpenMV4 Plus and improve its usability. Finally, we deployed the model on the device, and its performance was evaluated in a self-built experimental environment, achieving an average accuracy of 81.3%. The proposed method achieves an average recognition rate of about 10FPS on improved embedded devices. This method provides a practical and efficient solution for real-time gesture recognition of artificial traffic signals on embedded devices, with potential applications in various traffic scenarios. © 2023 ieee.

关键词： Convolution

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Development of Automated real-time Water Quality Monitoring and Controlling System in Aquarium 12

Development of Automated Real-Time Water Quality Monitoring ...

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12th ieee symposium on Computer applications and Industrial Electronics, ISCAIE 2022

作者： Yasruddin, Muhammad Luqman Amir Hakim Ismail, Muhammad Husin, Zulkifli Tan, Wei Keong University Malaysia Perlis Faculty of Electronic Engineering Technology Perlis Malaysia

ISBN: (纸本)9781665487030

The aquaculture industry significantly impacts food and the world economy, especially in countries that depend on marine and river resources. Fish farming in large tanks is getting more attention as this can be done anywhere without searching for sea, river and pond areas. However, the water quality in the rearing tank must be monitored and controlled continuously, which causes problems because maintaining the water quality requires expertise and is time-consuming. This paper proposes an automated water quality control system consisting of various sensors, microcontrollers, servers and mobile applications that continuously monitor and control water quality. Water quality parameters are measured using sensors, and data is sent to the microcontroller. The microcontroller processes the received data simultaneously, sends it to the server, and activates the actuator based on the situation. Data on the server can be monitored and controlled by a mobile application. The system achieves an excellent real-time performance and high practicability in the future to encourage technological advancement in the aquaculture industry. © 2022 ieee.

关键词： Water quality

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Q-eBall: A Hybrid Physical Electronic Game for the Next Generation of Bubble Soccer 6

Q-eBall: A Hybrid Physical Electronic Game for the Next Gene...

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6th International symposium on Advanced Electrical and Communication Technologies, ISAECT 2024

作者： Aklah, Zeyad Al-Safi, Amean Hassan, Hussein T. Aljabery, Khalid University of Thi-Qar Department of Information Technology Thi-Qar Iraq University of Thi-Qar Department of Electrical and Electronics Engineering Thi-Qar Iraq Missouri University of Science and Technology Applied Computational Intelligence Lab RollaMO United States

ISBN: (纸本)9798331529987

The widespread of electronic games has increased screen time, causing negative consequences such as autism, social isolation, vision problems, and back pain. This underscores the need for new games that blend physical activity with digital engagement. Consequently, the field of physically interactive electronic games has emerged, driven by advancements in sensor technology. In response, we present a novel hybrid physical electronic game, named Q-eBall. It builds upon the traditional bubble soccer game by replacing the real physical ball, which was causing a level of mundanity in the game, with a visual ball. This visual electronic ball is a group of integrated Light-Emitting Diodes (LEDs) in the players' plastic bumper bubbles. The game incorporates an embedded electronic circuit, a keypad for precise visual ball transfers, and sensors for detecting player falls and scoring. A centralized game server manages communication, monitors player status, and ensures smooth gameplay progression. The electronic integration in Q-eBall adds a new dimension of complexity, opening up possibilities for unique gameplay strategies and tactical choices. This paper describes the concept of Q-eBall game, along with a prototype and offers a labeled dataset collected from accelerometer, gyroscope, and pressure sensor during gameplay. The dataset comprises 173 falls and 206 non-fall events across 15 gameplay sessions, making it a valuable resource for researchers interested in analyzing and evaluating fall detection algorithms. © 2024 ieee.

关键词： Accelerometers

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Development of a universal diagnostic system for stator winding faults of induction motor and PMSM based on transfer learning 14

Development of a universal diagnostic system for stator wind...

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14th ieee International symposium on Diagnostics for Electrical Machines, Power Electronics and Drives, SDEMPED 2023

作者： Skowron, MacIej Wroclaw University of Science and Technology Drives and Measurements Department of Electrical Machine Wroclaw Poland

ISBN: (纸本)9798350320770

This paper deals with the possibility of using transfer learning (TL) of a deep convolutional network (CNN) to develop a universal stator winding fault diagnostic system for the induction motor (IM) and the permanent magnet synchronous motor (PMSM). The proposed diagnostic system uses direct processing of phase current signals to detect and evaluate the degree of stator damage. The TL idea was based on using the CNN structure pre-trained for the IM diagnostic system in a diagnostic application dedicated to IM and PMSM. Experimental verification carried out on real objects confirmed very high precision of steady-state and transient damage detection and classification for both IM and PMSM. Furthermore, the detection time shown in the study for both types of machines did not exceed 0.07 seconds. © 2023 ieee.

关键词： Induction motors

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FORCE: Optimal Resource Utilization Framework for Fog-enabled Green Communication in IoMT 18

FORCE: Optimal Resource Utilization Framework for Fog-enable...

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18th ieee International Conference on Advanced Networks and Telecommunications Systems, ANTS 2024

作者： Patel, Kaju Kanjia, Angel Kumhar, Malaram Bhatia, Jitendra Jadav, Nilesh Kumar Guptall, Rajesh Tanwar, Sudeep Gupta, Ankur Gujarat Technological University Ahmedabad382424 India Institute of Technology Nirma University Department of Computer Science and Engineering Ahmedabad India Model Institute of Engineering & Technology J&k Department of Computer Science & Engineering India

ISBN: (纸本)9798350391725

The Internet of Medical Things (IoMT) has revolutionized healthcare by integrating smart devices to monitor, analyze, and optimize patient care. Various healthcare devices generate a large volume of data daily, which uses a lot of storage and bandwidth. Fog computing is a promising paradigm that extends cloud computing capabilities near the network edge, allowing for real-time processing of healthcare data. In a fog-enabled IoMT environment, effective load balancing is essential to maximize resource utilization and guarantee timely and reliable healthcare services. This paper presents a load-balancing framework, i.e., FORCE, especially for fog-enabled IoMT environments. The FORCE focuses on challenges present in healthcare applications, such as meeting low latency requirements and dynamic workloads, and thus accelerates the idea of faster communication between the end devices, or IoT wearables, and fog nodes. To provide low-latency processing, the framework considers the fog computing architecture and brings computation close to healthcare devices. The FORCE delivers healthcare services with reduced latency and energy consumption. For the scenario wherein the region attribute is used to determine the optimal node result, the time to compute that was obtained is 14.82 seconds. In contrast, the computation time in later scenarios without considering region attributes is {7 6. 8 9} seconds. Hence, the FORCE efficiently reduces the searching time for finding the optimal node. Based on the simulation results, it can be concluded that the FORCE effectively optimizes both latency and energy consumption. © 2024 ieee.

关键词： Fog computing

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Wireless Edge Controller for Robot Education Using MQTT on Dobot Magician Lite 1

Wireless Edge Controller for Robot Education Using MQTT on D...

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1st ieee International symposium on Consumer technology, ISCT 2024

作者： Prayudi, Agus Arief, Muhammad Fauzan Zainuddin, Muhammad Agus Sukaridhoto, Sritrusta Rante, Hestiasari Politeknik Elektronika Negeri Surabaya Department of Electrical Engineering Surabaya Indonesia Politeknik Elektronika Negeri Surabaya Department of Creative Multimedia Technology Surabaya Indonesia Politeknik Elektronika Negeri Surabaya Department of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350365191

The integration of wireless controllers in robot education has emerged as a pivotal area to enhance the learning experience and practical understanding of robotics concepts. This paper presents the implementation of a wireless controller for educational purposes using MQTT (Message Queuing Telemetry Transport) on the Dobot Magician Lite robotic platform. MQTT, a lightweight messaging protocol, facilitates efficient communication between the controller and the robot, enabling seamless interaction and control over the robot's movements and functionalities. The implementation focuses on providing a user-friendly interface and intuitive controls, allowing students and educators to easily operate the robot while exploring various educational scenarios. Leveraging MQTT's flexibility, the system offers real-time control and monitoring capabilities, fostering interactive learning experiences in robotics education. The proposed wireless controller demonstrates the feasibility and effectiveness of employing MQTT in robot education, paving the way for enhanced learning opportunities and practical applications in the field of robotics. The examination of MQTT performance across various bandwidths provides important insights into our system's abilities. At 8 Mbps, our system achieved its highest transaction speed, averaging 1.61 transactions per second with a quick average transaction time of 0.62 seconds. Transaction speeds decreased as bandwidth decreased, with 1 Mbps showing the slowest average TPS of 1.24. Importantly, data retention stayed at 100% for all bandwidths, demonstrating consistent reliability. © 2024 ieee.

关键词： Educational robots

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A Machine Learning Enabled mmWave RFID for Rotational Sensing in Human Gesture Recognition and Motion Capture applications

A Machine Learning Enabled mmWave RFID for Rotational Sensin...

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ieee/MTT-S International Microwave symposium (IMS)

作者： Adeyeye, Ajibayo Lynch, Charles Hester, Jimmy Tentzeris, Manos Georgia Inst Technol ATHENA Lab Atlanta GA 30332 USA Atheraxon Atlanta GA USA

ISBN: (数字)9781665496131

ISBN: (纸本)9781665496131

In the coming years, augmented reality (AR) and virtual reality (VR) based applications will become common place. The proliferation of radar technology and the strong performance of millimeter wave backscatter have presented a unique opportunity to develop low-cost and low-power solutions to support the advent of AR/VR. In this effort, the authors present a first of its kind millimeter wave backscatter RFID for rotational sensing. The novel RFID tag design employed takes advantage of the polarization mismatch of linearly polarized antennas as the angle between the pair is varied. A supervised learning algorithm is used to achieve extremely high accuracy <1 degrees over an unambiguous range of +/- 90 degrees thus opening the door for potential use in a wide variety of real-time applications.

关键词： AR/VR FMCW millimeter-Wave radar RFID

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Implementation of a Robust Chirplet Signal Decomposition Algorithm on FPGA-SoC Platform for Ultrasonic Flaw Detection

Implementation of a Robust Chirplet Signal Decomposition Alg...

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ieee International symposium on applications of Ferroelectrics (ISAF)

作者： Tianyang Fang Austin Fite Jafar Saniie Department of Electrical and Computer Engineering Embedded Computing and Signal Processing (ECASP) Research Laboratory Illinois Institute of Technology Chicago IL U.S.A.

ISBN: (数字)9798350371901

ISBN: (纸本)9798350371918

This research presents a robust chirplet decomposition algorithm designed for hardware implementation, specifically aimed at enhancing ultrasonic nondestructive testing and imaging. The study focuses on developing an algorithm and an FPGA hardware module that enable real-time chirplet decomposition, emphasizing increased processing speed while maintaining echo accuracy. A novel Maximum Likelihood Estimation (MLE)-based parameter estimation algorithm was developed to improve chirplet parameter estimation, enhancing both accuracy and convergence speed. This high-performance platform enables real-time ultrasonic imaging for flaw detection in steel specimens, demonstrating significant improvements in defect detection and characterization. The resultant platform has been tested against four alternative platforms to evaluate its effectiveness in enhancing execution times. Remarkably, when compared to similar embedded platforms, this speed-optimized platform achieves a 150-fold increase in processing speed, surpassing the next fastest embedded platform, the Teensy 4.0, which includes a Cortex-M7 processor operating at 600MHz. Additionally, when compared to an AMD Ryzen 7 3700X, this platform operates 6.6 times faster.

关键词： Parameter estimation Accuracy Ultrasonic imaging Chirp Signal processing algorithms Transforms Hardware Acoustics real-time systems Steel

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