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检索条件"任意字段=Conference on Advanced Sensor Systems and Applications"

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ECG Monitoring System using IoT for Health Care applications 2

ECG Monitoring System using IoT for Health Care Applications

引用

2nd International conference on Augmented Intelligence and Sustainable systems, ICAISS 2023

作者： Vijaipriya, K. Priya, C. Sivanandan, Siji Krishnaswamy, R. Sri Sai Ranganathan Engineering College Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India Department of Electronics and Communication Engineering Andhra Pradesh Puttur India Meenakshi Sundararajan Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India University College of Engineering Department of Electronics and Communication Tamil Nadu Ariyalur India

ISBN: (纸本)9798350325799

The ECG monitoring system is an innovative method of heart health monitoring that makes use of the Internet of Things for healthcare purposes. With the use of Raspberry Pi, an electrocardiogram (ECG) sensor, and a cloud server, this system can monitor a patient's heart rate in real time and indefinitely, which has several benefits for both the patient and the doctor. Using the IoT, the ECG sensor can communicate to the cloud storage directly. The patient's electrical heart activity is monitored by use of an ECG sensor. After that, the sensor's output data is sent to the cloud server through Raspberry Pi, which operates as a connection between the sensor and the cloud server. Analyzing and evaluating ECG data in real time through cloud servers using advanced methods. The approaches are sensitive and accurate sufficient to detect cardiac irregularities such arrhythmias. When anomalies are detected, the system immediately generates realtime alerts to healthcare professionals. Instant alerts allow for prompt medical treatment, which improves patient outcomes and decreases the potential of catastrophic events. The cloud server provides a store for patient data and will enable doctors to access it from anywhere. In healthcare settings, this system's ability to identify cardiac problems early improves patient care and promotes preventative approaches to controlling heart health. © 2023 IEEE.

关键词： Electrocardiograms

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Speed measurement of solar fed PMDC motor using photovoltaic module and hall effect sensor 8

Speed measurement of solar fed PMDC motor using photovoltaic...

引用

8th International conference on advanced Computing and Communication systems, ICACCS 2022

作者： Sanskriti Choudhary, Sheetal Shivani Yadav, Prem Prakash Electrical Engineering Delhi Technological University New Delhi India

ISBN: (纸本)9781665408165

This paper talks about the use of dc dc converter, namely boost converter in photovoltaic applications and further using the output voltage to run a PMDC motor and find its speed through a hall sensor. The paper starts with the importance of solar energy and then discusses the current energy crisis where we find that in India, the maximum amount of energy is produced through coal which has various disadvantages and is available in limited amounts. Therefore, there is a need to switch to renewable resources. Out of the renewable resources, solar energy is of prime concern. Solar energy can be primarily harnessed through PV arrays and to make it more efficient we incorporate a boost converter in it. This helps in tracking the optimal or the maximum power for the PV array, improves efficiency and allows constant stepped up voltage supply at different loads at the output. © 2022 IEEE.

关键词： Simulink

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Structural health monitoring of belt conveyor based on distributed optical fiber acoustic sensor 12

Structural health monitoring of belt conveyor based on distr...

引用

conference on advanced sensor systems and applications XII

作者： Liu, Qing Pan, Zhen Li, Zhaojie Yan, Binyang Liu, Kang Ai, Bojun Xie, Lang Guizhou Power Grid Co Ltd Power Dispatching Control Ctr Guiyang Peoples R China Univ Elect Sci & Technol China Sch Commun & Informat Engn Key Lab Opt Fiber Sensing & Commun Educ Minist Chengdu 611731 Sichuan Peoples R China

ISBN: (纸本)9781510657090;9781510657083

Distributed optical fiber acoustic sensing (DAS) can serve as an excellent tool for real-time condition monitoring of a variety of industrial and civil infrastructures. This paper presents a belt conveyor roller fault abnormal monitoring method based on DAS, for the low accuracy and efficiency of the existing belt conveyor rollers fault detection. This method uses the Rayleigh Backscatter of coherent pulsed light to detect and reconstruct the fault signal, and proposes a method based on the combination of power spectrum features and peak detection to recognize and locate abnormal signals under intense background noise. The field test verifies the effectiveness of the real-time monitoring scheme of the industrial conveyor belt system, with a detection accuracy rate of over 87% for simulated fault signals, and a location accuracy of +/- 2.5 m. It provides a new passive distributed monitoring method for the all-weather structural health monitoring of the rollers in the industrial belt conveyor systems.

关键词： distributed fiber optical sensors acoustic sensing f-OTDR belt conveyor health monitoring

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2023 International Telecommunications conference, ITC-Egypt 2023

2023 International Telecommunications Conference, ITC-Egypt ...

引用

2023 International Telecommunications conference, ITC-Egypt 2023

ISBN: (纸本)9798350326062

The proceedings contain 137 papers. The topics discussed include: a compact petal shaped two-port MIMO antenna for quad-band millimeter wave 5G applications;human footsteps-based energy harvesting using piezoelectric elements;a sequence of circular slotted nonagon shape extended ultrawideband antenna for smart electronic systems using characteristic mode analysis;detecting dependent malicious nodes in multi-state target detection wireless sensor networks;gain enhancement of a miniaturized broadband patch antenna using a metamaterial superstrate for surveillance applications in aircraft;recent advances towards securing smart grids with blockchain;evaluating potential security risks of advanced metering infrastructure using EBIOS risk assessment method;an optimized radar sensors schedule using genetic algorithms;characteristics mode analysis based dual-port sub-6 GHz flexible antenna for surveillance applications;a thermostable frequency selective surface with both a low-pass and a wide shielding band;green computing and security practices for optimizing crawler efficiency;and compact triple-band millimeter wave flexible antenna for wearable applications.

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Enhancing Battery Management systems with Machine Learning and 5G Connectivity beyond Maritime Transport Software Architectures 15

Enhancing Battery Management Systems with Machine Learning a...

引用

15th International conference on Communications, COMM 2024

作者： Paraschiv, Constantin-Laurentiu Tufeanu, Larisa Mihaela Vochin, Marius-Constantin POLITEHNICA Bucharest Faculty of Electronics Department of Telecommunications Bucharest Romania

ISBN: (纸本)9798350355956

The growing advancement in battery technology has revolutionized various domains and services, notably transportation and energy storage. This research focuses on improving battery management systems (BMS) for electric vehicles (EV) and hybrid vehicles (HEV) by leveraging advanced machine learning models and 5G connectivity. This study proposes an integrated software architecture designed for both industrial and road applications, aiming to optimize battery performance and safety by analyzing collected data and predicting the anomaly events by training Random Forest and Gradient Boosting machine learning (ML) models. Throughout the research, key battery performance parameters and their normal operating ranges, such as voltage, current, temperature, charge/discharge rates, internal Resistance and State of Charge (SoC) are analyzed, according to the official regulations and utilized in Python scripting. The Python script implemented simulates battery operations by updating sensor values and logging incidents with factors such as latency, jitter, and encryption time. The script trains and compares machine learning models to determine the most accurate one for anomaly detection. The final part of the script simulates battery performance under different connectivity modes (5G Non-Standalone (NSA) and 5G Standalone (SA)) to assess the impact on data transmission and real-time monitoring. Ultimately, obtained results demonstrate not only advanced, sustainable, mobility solutions by improving the safety and performance of Battery Management systems in electric and hybrid vehicles, but also the importance of leveraging cutting-edge technologies (such as ML) and connectivity (5G). © 2024 IEEE.

关键词： Hybrid vehicles

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Directional bending sensing characteristics of in-line Mach-Zehnder interferometer based on asymmetrical twin-core fiber 12

Directional bending sensing characteristics of in-line Mach-...

引用

conference on advanced sensor systems and applications XII

作者： Yang, Huiping Yan, Binbin Luo, Yanhua Yang, Liwei Wang, Kuiru Yuan, Jinhui Sang, Xinzhu Peng, Gang-ding Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China Shanghai Univ Shanghai Inst Adv Commun & Data Sci Key Lab Specialty Fiber Opt & Opt Access Networks Joint Int Res Lab Specialty Fiber Opt & Adv Commu Shanghai 200444 Peoples R China Univ New South Wales Sch Elect Engn Photon & Opt Commun Sydney NSW 2052 Australia China Agr Univ Coll Informat & Elect Engn Beijing 100083 Peoples R China

ISBN: (纸本)9781510657090;9781510657083

We propose and experimentally demonstrate a simple directional bending sensor based on an in-line Mach-Zehnder interference structure of the single mode fiber (SMF)-multimode fiber (MMF)-asymmetrical twin-core fiber (ATCF)-MMF-SMF. Due to the asymmetric structure in twin-core fiber, this sensor can discriminate different bending directions. The interference spectrum shifts with the change of curvature. Furthermore, the sensor exhibits a linear response with a maximum bending sensitivity of 33.48 and -38.72 nm/m(-1) in the curvature range from 0 to 3.01 m(-1) for bending directions at -x (180 degrees) and +x (0 degrees) directions, respectively. The proposed fiber sensor has great potential in the future Internet of Things (IoT) due to its advantages, such as low cost, compactness, and high bending sensitivity.

关键词： Asymmetric twin-core fiber Optical fiber sensor Mach-Zehnder interferometer Directional bending sensing

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UKF-Based Multi-sensor Data Processing Algorithm for SLAM 9

UKF-Based Multi-sensor Data Processing Algorithm for SLAM

引用

9th International conference on Control Science and systems Engineering, ICCSSE 2023

作者： Xu, Kun Zhang, Boheng Li, Jiangang Wang, Guizhong Sun, Mingjian School of Information Science and Engineering Harbin Institute of Technology Weihai China Harbin Institute of Technology Department of Control Science and Engineering Harbin China Co. Ltd. Shenzhen China Hebei Key Laboratory of Grid Advanced Measurement Monitor Jinyanhagong Industrial Technology Research Institute Zhangjiakou China

ISBN: (纸本)9798350339055

Simultaneous localization and mapping (SLAM) algorithm is widely used in unmanned and robotic applications. SLAM usually uses sensor data, which are from the LiDAR, the inertial measurement unit (IMU) and the wheeled odometry, to build maps of the surrounding environment. However, the motion distortion of LiDAR data and the error accumulation of wheeled odometry can affect the accuracy of the front-end odometry of the SLAM algorithm, which can lead to serious errors in the maps created. Therefore, in order to solve the problem of poor map construction results of SLAM algorithm due to various types of sensor errors. we propose the traceless Kalman filtering based (UKF-based) multi-sensor data processing algorithm. Firstly, the proposed algorithm uses the UKF to fuse IMU and wheeled odometry data to reduce the cumulative error of wheeled odometry. And then the algorithm uses IMU and corrected wheeled odometry data and combines with the motion states of the robot to solve the motion distortion problem of LiDAR data. Finally, we verified the effectiveness of the proposed algorithm for wheeled odometry data correction in Gazebo simulation environment and real environment experiments, and compared the mapping effectiveness of SLAM by using the original data and the data processed by our algorithm. The experimental results show that the map construction effect of SLAM algorithm is significantly improved when using the sensor data processed by the algorithm. Experimental validation on the robot shows that the proposed algorithm has universal applicability and good compatibility. © 2023 IEEE.

关键词： sensor data fusion

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Deterministic Multi-sensor Measurement-adaptive Birth using Labeled Random Finite Sets 26

Deterministic Multi-sensor Measurement-adaptive Birth using ...

引用

26th International conference on Information Fusion, FUSION 2023

作者： Bondarchuk, Jennifer Trezza, Anthony Bucci, Donald J. Advanced Technology Laboratories Lockheed Martin Cherry HillNJ United States

ISBN: (纸本)9798890344854

Measurement-adaptive track initiation remains a critical design requirement of many practical multi-target tracking systems. For labeled random finite sets multi-object filters, prior work has been established to construct a labeled multi-object birth density using measurements from multiple sensors. A truncation procedure has also been provided that leverages a stochastic Gibbs sampler to truncate the birth density for scalability. In this work, we introduce a deterministic herded Gibbs sampling truncation solution for efficient multi-sensor adaptive track initialization. Removing the stochastic behavior of the track initialization procedure without impacting average tracking performance enables a more robust tracking solution more suitable for safety-critical applications. Simulation results for linear sensing scenarios are provided to verify performance. © 2023 International Society of Information Fusion.

关键词： Target tracking

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Tactile Image Processing and Shape Detection Method of Array Tactile sensor for Surgical Robot Based on Deep Learning 17th

Tactile Image Processing and Shape Detection Method of Array...

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17th International conference on Intelligent Robotics and applications, ICIRA 2024

作者： Niu, Xinyao Ju, Feng Nanjing University of Aeronautics and Astronautics Nanjing210016 China

ISBN: (纸本)9789819607761

The rapid evolution of modern medical technology has propelled surgical robots to the forefront of surgical innovation. These robots offer unprecedented accuracy and safety in procedures, empowering surgeons with advanced technical capabilities to tackle complex medical challenges. In tumor treatment, surgical robots excel in precise tumor tissue resection, minimizing damage to healthy tissue and reducing surgical risks. However, accurately identifying tumor boundaries and depth remains challenging due to limitations of traditional palpation methods. This study aims to develop a deep learning model for real-time tumor boundary detection within surgical robot systems. By processing array tactile sensor image data, this model will enable precise boundary and depth detection, enhancing surgical robot recognition and operational capabilities. This advancement promises improved surgical success rates, patient survival rates, and reduced risks of complications, ultimately enhancing patient treatment outcomes and quality of life. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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A Simplified Open-loop Control Strategy for Integrated Shading and Lighting systems Using Machine Learning 17

A Simplified Open-loop Control Strategy for Integrated Shadi...

引用

17th conference of International-Building-Performance-Simulation-Association (IBPSA)

作者： Xie, Jiarong Sawyer, Azadeh Omidfar Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781775052029

Conventional integrated shading and lighting systems are usually sensor-dependent, which could entail excessive cost and labor associated with sensor installation, calibration, and maintenance. advanced systems use daylight modeling to eliminate the use of physical sensors. However, real-time daylight simulation can be computation-heavy, leading to a slow response of the system. This paper proposed a data-driven method for integrated shading and lighting control, employing machine learning models developed from pre-simulated data to predict real-time daylighting and control the blind and lighting accordingly. Verification using climate-based daylight simulation with a case study showed that the method prevented 94.7% of annual glare and reduced lighting use by 64%. The study will contribute to the development of effective daylight-linked control systems for industrial applications.

关键词： Machine learning

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