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2024 International conference on Smart Electronics and Communication systems, ISENSE 2024

作者： Kumar, Arvind Jaya Krishna, N. Chandra, Mahesh Kumar, Rampravesh Sahoo, Jaya Prakash Poojitha, N. Karan, Biswajit Kishore, Kamlesh Gitam University Department of EECE Bengaluru India School of ECE Reva University Bengaluru India Sandip University Department of EEE Nashik India University of Stellenbosch Department of EEE Stellenbosch South Africa RTC Institute of Technology Department of ECE Bengaluru India

ISBN: (纸本)9798331528126

This paper presents a novel approach for fruit quality detection using a multi-modal system that combines sensor data and image processing techniques with deep learning. In the first stage of our experiment, we employed various sensors to measure temperature, gas levels, and moisture content using DHT 11 and MQ-135 sensors. These sensors provide valuable insights into the environmental conditions surrounding the fruits, which are crucial indicators of their freshness. In the second stage, we utilized image processing algorithms to pre-process fruit images and train a SqueezeNet convolutional neural network (CNN) to classify fruits into two classes: fresh and rotten. By integrating sensor data with image-based classification, our proposed method offers a comprehensive solution for real-time fruit quality assessment. Experimental results demonstrate the effectiveness of our approach in accurately detecting fruit quality, paving the way for advanced applications in food safety and quality control. © 2024 IEEE.

关键词： Convolutional neural networks

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GNSS/IμUWB-Based Train Integrity Monitoring Using Fuzzy Reasoning 4

GNSS/IμUWB-Based Train Integrity Monitoring Using Fuzzy Rea...

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4th IEEE International conference on Power, Electronics and Computer Applications, ICPECA 2024

作者： Zhong, Tianyu Liu, Jiang Cai, Baigen Wang, Jian School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Computer Science and Technology Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350359589

Integrity of a train is a significant characteristic parameter towards a railway train control system in order to guarantee the railway operational safety. The decoupling event between a locomotive and a carriage or two adjacent carriages has become a serious threat for the following train operating along the same track. Conventional train integrity monitoring solutions based on state detection with specific sensors, like the Global Navigation Satellite system (GNSS) receiver and tail wind pressure unit, may not perform effectively and safely under constrained or difficult operation environments. This paper presents a Train Integrity Monitoring system (TIMS) architecture with integration of GNSS, Inertial Measurement Unit (IMU) and Ultra-wide Band (UWB) ranging technique. To realize the effective determination of the train integrity state with multiple detection channels, the fuzzy reasoning theory is adopted for decision-making. By using the simulated Head-of-Train (HoT) and End-of-Train (EoT) platforms, both the normal and decoupling scenarios are investigated through experiments. With the practically collected sensor datasets, the different single-sensor-based methods are compared with the presented fuzzy reasoning-based solution. The comparison results illustrate the advanced performance level under the given experimental conditions, which indicate great potentials of the presented solution in novel train control systems. © 2024 IEEE.

关键词： fuzzy reasoning Global Navigation Satellite system (GNSS) railway transportation sensor integration train integrity monitoring Ultra-wide Band

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Voice controlled Wheelchair system 2

Voice Controlled Wheelchair System

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2nd International conference on Disruptive Technologies, ICDT 2024

作者： Sachdeva, Bhawna Anshuman Jha, Nandni Raj, Akshat Greater Noida Institute of Technology Dept. of Ece Uttar Pradesh India

ISBN: (纸本)9798350371055

The paper presents the design of a voice-controlled wheelchair which aims to improve mobility and independence for individuals with limited physical capabilities. It uses voice recognition technology to interpret voice commands, allowing users to navigate their environment. The voice recognition module in the system is interfaced with an Arduino microcontroller, which functions as the wheelchair's brain. Users can give verbal orders that are processed in real-time, such as stop or direction commands. The wheelchair's motors are managed by the Arduino and the system is equipped with sensors for accurate and obstacle-aware navigation. The system incorporates advanced sensors and motor control mechanisms, ensuring a safe and responsive user experience. © 2024 IEEE.

关键词： Arduino obstacle-aware navigation ultrasonic sensor voice controlled Wheelchair

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Development of Low-Cost Water Level Monitoring and control using PID controller 3

Development of Low-Cost Water Level Monitoring and Control u...

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3rd International conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Kadu, Anil Bhosale, Shreyash Pagare, Ashwini Sable, Pravin Kudtarkar, Raj Bhilare, Abhishek Vishwakarma Institute of Technology Instrumentation and Control Pune India

ISBN: (纸本)9798350343632

This research study presents a multi-process water control loop that utilizes Arduino UNO microcontroller to control and monitor water levels in a tank. The proposed system incorporates two Pneumatic control valves and a water level sensor to regulate the water flow. The Arduino Uno microcontroller is programmed using C and C++ languages in the Arduino IDE. The project aims to maintain optimal water levels within the tank by opening the Pneumatic valve when the tank is empty and closing them when the water reaches the maximum set point. The water level is monitored using a level transmitter sensor. The results demonstrate the successful control and monitoring of the water level. The project demonstrates successful control and monitoring of the water level in the tank. By providing an automated and efficient solution, it contributes to improved water management and process optimization in industrial settings. The results showcase the effectiveness of the implemented system, highlighting its potential for application in various industries where precise control of water levels is essential. The pneumatic control valve adjusts its position based on the control signal received from the Arduino Uno microcontroller. © 2023 IEEE.

关键词： Arduino UNO microcontroller Pneumatic control valves Real-time monitoring interface Water multi-process control

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W-band On-chip Vital Sign Radar sensor using GaAs MMIC Super-Regenerative Oscillator 31

W-band On-chip Vital Sign Radar Sensor using GaAs MMIC Super...

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31st Asia-Pacific Microwave conference (APMC) - Microwave Linking the World

作者： Gao, Donglin Li, Shuping Wu, Chung-Tse Michael Rutgers State Univ Dept Elect & Comp Engn Piscataway NJ 08854 USA

ISBN: (纸本)9781665494182

This paper introduces a low-power, highly sensitive W-band (75-110 GHz) super-regenerative oscillator (SRO)-based vital sign radar sensor with a SIW monopole antenna integrated. The proposed radar sensor is implemented using the 0.1-mu m GaAs pHEMT technology. Operating at the center frequency of 85.283 GHz, the proposed super-regenerative oscillator leverages 100 Hz and 20 kHz sinusoidal quench signals for control during the target detection. Experimental results validate the effectiveness of the proposed sensor in identifying the displacement frequency of an actuator along with human target vital signs. The achieved results show good agreement with the ground truth. Moreover, compared to the self-injection-locked (SIL) detection scheme, the proposed SRO radar sensor demonstrates superior characteristics, such as lower power consumption, higher sensitivity, and low system complexity.

关键词： GaAs pHEMT super-regenerative oscillator (SRO) substrate-integrated-waveguide (SIW) vital sign detection W-band

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Adaptive-optical 3D microscopy for microfluidic multiphase flows

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Light(advanced Manufacturing) 2024年第3期5卷 105-119页

作者： Clemens Bilsing Erik Nützenadel Sebastian Burgmann Jürgen Czarske Lars Büttner Laboratory of Measurement and Sensor System Techniques TUD Dresden University of Technology01069 DresdenGermany Chair of Fluid Mechanics Bergische Universitát Wuppertal42119 WuppertalGermany BIOLAS Laboratory of Measurement and Sensor System Techniques01069 DresdenGermany

Measurements based on optical microscopy can be severely impaired if the access exhibits variations of the refractive *** the case of fluctuating liquid-gas boundaries,refraction introduces dynamical aberrations that increase the measurement *** is prevalent at multiphase flows(***,film flows)that occur in many technical applications as for example in coating and cleaning processes and the water management in fuel *** this paper,we present a novel approach based on adaptive optics for correcting the dynamical aberrations in real time and thus reducing the measurement *** shape of the fluctuating water-air interface is sampled with a reflecting light beam(Fresnel Guide Star)and a Hartmann-Shack sensor which makes it possible to correct its influence with a deformable mirror in a closed ***-dimensional flow measurements are achieved by using a double-helix point spread *** measure the flow inside a sessile,oscillating 50-μl droplet on an opaque gas diffusion layer for fuel cells and show that the temporally varying refraction at the droplet surface causes a systematic underestimation of the flow field magnitude corresponding to the first droplet eigenmode which plays a major role in their detachment *** demonstrate that the adaptive optics correction is able to reduce this systematic ***,the adaptive optics system can pave the way to a deeper understanding of water droplet formation and detachment which can help to improve the efficiency of fuels cells.

关键词： Double-Helix point spread function Adaptive optics Particle tracking velocimetry Aberration correction Depth-resolving microscopy Closed-loop control

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Application Overview of Fiber Bragg Grating sensors in Structural Health Monitoring 6

Application Overview of Fiber Bragg Grating Sensors in Struc...

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6th IEEE advanced Information Technology, Electronic and Automation control conference (IEEE IAEAC)

作者： Wang, Limin Xiao, Chuncheng Ding, Wenqi Wu, Jiayi Shi, Chunlin Beijing Inst Strength & Environm Engn Beijing Peoples R China Beijing Inst Astronaut Syst Engn Beijing Peoples R China

ISBN: (数字)9781665458641

ISBN: (纸本)9781665458641

This paper introduces the composition and basic principles of the structural health monitoring system and the development history of fiber Bragg grating sensing technology. The advantages are described in detail. At the same time, the application of FBG sensor in the field of structural health monitoring at home and abroad is introduced, and the existing problems in the application and the future research direction are discussed.

关键词： structural health monitoring optical fiber sensing technology fiber Bragg grating (FBG) sensor development application

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Real Time Monitoring and Configuration interface for Smart Home Device Management Using Streamlit and Pygame

Real Time Monitoring and Configuration Interface for Smart H...

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2024 International conference on Advances in Data Engineering and Intelligent Computing systems, ADICS 2024

作者： Mani, G. Suma Krishna, G. Venkata Praveena, M.D. Anto Asha, P. Selvan, Mercy Paul Sathyabama Institute Of Science And Technology Dept. Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

One of the helpful tool for measuring and managing home power consumption is one of the clever and creative tool for tracking the usage of Home Power Management system. The Goal of this system is to lower the power bills, also promote energy efficiency, and provide the users active control over how much energy they use. Smart meters, an intuitive and user-friendly smartphone app, and real-time energy monitoring sensors are some of the system's essential parts and these are the key parts of the system. Installing smart meters makes it possible to accurately track the power usage and provide data to the system. Users can be able to see their energy usage instantly and make smart decisions when real-time energy monitoring equipment is included. Further, the system uses advanced smart technology, analytics and machine learning algorithms to provide clients customized suggestions on how to save energy consumption. Homes may save a lot of money on electricity bills, help the environment, and have more control over how much energy they use by using our Smart Home Power Management system. © 2024 IEEE.

关键词： Smart meters

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DECOUPLING AND PREPARATION OF FLEXIBLE HAPTIC THREE-DIMENSIONAL FORCE sensor 10

DECOUPLING AND PREPARATION OF FLEXIBLE HAPTIC THREE-DIMENSIO...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Fu, Minghui Gao, Guowei Wang, Chao Li, Yansheng Hu, Jingfang Beijing Key Laboratory of Sensor Beijing Information Science and Technology University Beijing100101 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9781837242672

An asymmetric capacitive haptic sensor structure with three-dimensional force detection capability has been designed. The sensor unit comprises a upper public electrode, three under electrode plates and fork finger electrodes. Developed a visualization interface for this system by PyQt5. A series of tests were conducted on the sensor, including tensile and flex fatigue tests, single and dynamic pressure performance tests, tangential force performance tests and three-dimensional force tests. The response time of the sensor was found to be 3.5 seconds, while the recovery time was 5.5 seconds. The sensitivity of the Z-axis was 0.081 Kpa-1 in the range of 0 to 4.22 Kpa and 0.014 Kpa-1 in the range of 4.22 to 29.31 Kpa, the sensitivities in the positive and negative directions of the X-axis was 0.223 pF/N and -0.248 pF/N, while the sensitivities in the positive and negative directions of the Y-axis was 0.242 pF/N and -0.243 pF/N. The tests demonstrates that the sensor exhibited satisfactory flexibility, repeatability, and a linearity of 0.16%, thereby ensuring reliable measurement outcomes. © The Institution of Engineering & Technology 2024.

关键词： Tensile testing

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Real-Time Monitoring and control systems Using IoT-Integrated Wireless sensor Networks-Leveraging Machine Learning Algorithms for Enhanced Performance and Efficiency

Real-Time Monitoring and Control Systems Using IoT-Integrate...

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2024 International conference on Cybernation and Computation, CYBERCOM 2024

作者： Swaminathan, Subbiah Poongavanam, N. Arun, M. Pushparani, S. Muthukrishnan, A. Johri, Prashant Rajalakshmi Engineering College Department of Information Technology Tamil Nadu Chennai India Saveetha University Department of Computer Science and Engineering Chennai602105 India Panimalar Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Meenakshi College of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai600 078 India Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Avadi Chennai India School of Computer Application and Technology Galgotias University India

ISBN: (纸本)9798331542344

This paper introduces a developed real-Time monitoring and control system using Internet of Things (IoT) incorporated Wireless sensor Networks (WSNs) supported by machines learning algorithms. The system focuses at meeting core issues and questions in terms of productivity, reliability and timeliness within evolving settings. The current paper contributes to the ongoing research and development in the area of IoT and WSN to enable, always-on real-Time data gathering from a variety of discrete sensors which is invaluable for various applications including industrial, environmental and smart city applications. The heart of the system is based on the idea of utilising machine learning methods to acquire and elaborate sensor signals. More specifically, the deep learning models that are used include Long Short-Term Memory (LSTM) networks as well as Reinforcement Learning (RL) algorithms for predictive analytics, as well as anomaly detection. The work also entails a comparison of the system performance based on energy consumption and other factors such as latency, packet delivery ratio and even the accuracy of the predictions made by the system. The findings suggest improved utilisation within substantial ranges;decreased energy use by 30 per cent or more. 7%, latency decrease by 33. Although achieving this was accompanied by an increased data packet loss rate to 3%, the overall packet delivery ratio was boosted to 98%. Additionally, the system established overall accuracy rate of 95% with negligible error percentage. In conclusion, this research proves the applicability of incorporating the IoT and the advanced machine learning methods in the real-Time monitoring and control systems development to overcome cases of low efficiency and reduced performance in numerous real-world applications. © 2024 IEEE.

关键词： Predictive analytics

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