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

共 4661 条记录，以下是101-110 订阅

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Designing a Machine Learning Based Efficient and Outlier Free Lane Detection System for Autonomous Vehicles

Designing a Machine Learning Based Efficient and Outlier Fre...

引用

2024 International conference on Artificial Intelligence and Quantum Computation-Based sensor applications, ICAIQSA 2024

作者： Singh, Siddharth Sharma, Shruti Singh, Adarsh Dwivedi, Rajendra Kumar Madan Mohan Malaviya University of Technology Department of ITCA Gorakhpur India

ISBN: (纸本)9798331517953

The high growth in the number of automobiles has raised the demand of enhanced driver and passenger safety measures. The goal being effective and efficient application of evolving technology to address the concerns arising with partially or fully autonomous vehicles. Accurate lane positioning and lane change detection is an integral part of advanced Driver Assistance System which helps in safer trajectory planning. The engineering marvel of Light Detection and Ranging sensors corrects global localization error and provides centimeter-level accuracy but finds its use in restricted domain due to its computational complexity and cost implied. Lane detection is a technique for automatically road markers to ensure that cars stay in their assigned lane and do not collide with vehicles in other lanes. As an alternative, machine learning enabled vision-based lane change detection is highly regarded to provide lane-level localization maintaining high level accuracy. The algorithm design provides polynomial fitting with LiDAR data that helps model perform well in bad lighting conditions and help detect curved lane marking. The technology is well adopted based on the real-world testing scenarios which affirms its real time robustness with average of 89% lane change detection accuracy. © 2024 IEEE.

关键词： advanced driver assistance systems

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Open Loop Resonator Loaded Self Complementary Antenna With T-Shaped Dipoles for sensor applications 10

Open Loop Resonator Loaded Self Complementary Antenna With T...

引用

10th International conference on advanced Computing and Communication systems, ICACCS 2024

作者： Rajendran, Jolly Minu, K.H. Keerthana Mohan, U. Ace College of Engineering Department of Electronics and Communication Engineering Thiruvananthapuram India

ISBN: (纸本)9798350384369

This paper proposes a novel antenna, which can be used for detecting electromagnetic field signatures associated with lightning strikes. The proposed printed antenna demonstrates sensitivity to electromagnetic emissions within the frequency range between 330 MHz to 960 MHz. To enhance the antenna's performance, OLRs (Open Loop Resonators) are integrated into a conventional self-complementary antenna (SCA) having T- shaped dipoles. The resulting antenna, the OLR- loaded self- complementary antenna with T-shaped dipoles (OSCTDA) is compact and exhibits a VSWR bandwidth spanning from 330 MHz to 960 MHz, maintaining a Voltage Standing Wave Ratio (VSWR) below 2 throughout the entire frequency spectrum. The antenna's performance is examined through simulations and experiments. The proposed antenna can be used to analyze electromagnetic emissions generated by lightning-induced surge currents. © 2024 IEEE.

关键词： Loop antennas

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Smart sensor-Based Rear Seat Monitoring System to Prevent Pediatric Vehicular Heatstroke 67

Smart Sensor-Based Rear Seat Monitoring System to Prevent Pe...

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67th IEEE International Midwest Symposium on Circuits and systems (MWSCAS)

作者： Sharara, Leila Gillner, Jonas Taylor, Roy Thelen, Klaus Alazzawi, Lubna Ismail, Mohammed Wayne State Univ Elect & Comp Engn Detroit MI 48202 USA Ruhr West Univ Appl Sci Measurement & Sensor Technol Mulheim Germany

ISBN: (纸本)9798350387186;9798350387179

This research presents an innovative solution aimed at preventing in-vehicle pediatric heatstroke incidents through the integration of advanced sensors, connectivity, and intelligent algorithms. The proposed system continuously monitors crucial parameters including occupancy status, temperature, and the child's Respiratory Rate (RR). A hybrid detection approach, combining Force Sensing Resistor (FSR) sensors and motion sensors, is employed to ensure enhanced accuracy. To optimize the system efficiency, the solution utilizes Simplified Frequency Analysis (SFA), offering processing speeds up to 80 times faster than conventional methods, making it ideal for real-time applications. The processed data is seamlessly transmitted via a mobile application, enabling immediate caregiver notification and intervention. Initial testing confirms the solution's high accuracy in occupancy detection and breath monitoring, satisfying automotive standards for temperature resilience and power efficiency. Engineered to withstand extreme environmental conditions ranging from -40 degrees C to +85 degrees C, while maintaining a minimal standby current of 104 mu A, this technology holds immense potential in not only saving lives but also establishing itself as a standard safety feature.

关键词： Force Sensing Resistor FSR sensors Microcontroller DIC CPD Simplified Frequency Analysis SFA RR occupancy Heatstroke

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A Novel Multiple Modes Resonant sensor Featuring Blue Sideband Excitation 38

A Novel Multiple Modes Resonant Sensor Featuring Blue Sideba...

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38th IEEE International conference on Micro Electro Mechanical systems, MEMS 2025

作者： Xu, Jiao Zheng, Zhuoyue Xi, Jingqian Zhang, Ziqian Liu, Huafeng Zhang, Pan Chen, Jianlin Wang, Chen Kraft, Michael Wang, Yuan Martins, R.P. Mak, Pui-In Huazhong University of Science and Technology Moe Key Laboratory of Fundamental Physical Quantities Measurement Pgmf School of Physics Wuhan430074 China University of Macau Institute of Microelectronics State Key Laboratory of Analog and Mixed-Signal Vlsi 999078 China Peking University National Key Laboratory of Advanced Micro and Nano Manufacture Technology School of Integrated Circuits 100871 China Shanghai University School of Microelectronics 200444 China Ku Leuven Department of Electrical Engineering-MNS Leuven3000 Belgium

ISBN: (纸本)9798331508890

This paper reports a novel MEMS resonant structure functioning as a baseline resonant electrostatic force/temperature sensor, highlighting its substantial potential in sensing applications. The resonator, characterized by a dual-cosine structure, is capable of simultaneous multiple resonant modes actuation within the 300 kHz range, through a sole-source drive approach using the recent emerging Blue Sideband Excitation (BSE) technique. This method enables a distinctive multi-modal response, essential for multi-parameter measurements. The research focuses on the sensor's temperature characteristics, electrostatic perturbation sensitivity, and noise floor. Notably, the study reveals intriguing temperature responses across different modes, where certain modes exhibit a significant frequency rise with increasing temperature, this is counter-intuitive with common MEMS resonator devices, prompting further investigation into the underlying mechanisms. The analysis of electrostatic perturbation sensitivity and noise background further unfolds the resonator's performance under various excitation conditions, laying a foundation for advancing sensor functionality, and providing solid evidence on the viability of the subject. To sum up, this study highlights the resonator's potential as a high-precision sensor, opening new opportunities for MEMS sensor design and multi-parameter measurement applications. © 2025 IEEE.

关键词： Microchannels

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Beyond the Blink: IoT's Next-Gen Drowsiness Detection System for Drivers 3

Beyond the Blink: IoT's Next-Gen Drowsiness Detection System...

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3rd IEEE International conference on Industrial Electronics: Developments and applications, ICIDeA 2025

作者： Routray, Sidheswar Patel, Nachiket Patel, Dhruv Srivastava, Jyoti Dash, Rudra Narayan Pandit Deendayal Energy University Dept. of Computer Science & Engg. Gandhinagar India Indrashil University Dept. of Computer Science & Engg. Mehsana India Ganpat University Dept. of Computer Engineering Mehsana India School of Electrical Engineering KIIT University Bhubaneswar India

ISBN: (纸本)9798331533205

Drowsiness during driving includes high risks for the driver, the co-passengers, and the other people on the road. Advance Driver Assistance systems (ADAS) have been proposed to reduce these risks. This work introduces a new Internet of Things (IoT) seizure detection system to improve driver safety using Raspberry Pi, which is equipped with various sensors and utilizes machine learning for real-time monitoring and analysis. Using sensor fusion technology, including monitoring yawning and eye-closing patterns, the system aims to detect early signs of driver sleepiness. Being a low-cost, versatile, and tiny device, it becomes an ideal core processor for integration into an in-car environment. Additionally, the simplicity enables seamless communication with various sensors and facilitates effective data collection. Extensive tests and simulations were conducted to evaluate the effectiveness and reliability of the proposed system for real-world driving situations. The result outcomes prove the system's accuracy and efficiency in detecting early signs of driver fatigue to enhance driver safety. The integration of Raspberry Pi and sensor fusion technology makes it economical as well as scalable approaches supporting multiple platforms. © 2025 IEEE.

关键词： advanced driver assistance systems

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Solving the Two-Criteria Maximum Coverage Location Problem of Continuous Area Monitored by sensor Network 12

Solving the Two-Criteria Maximum Coverage Location Problem o...

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12th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems: Technology and applications, IDAACS 2023

作者： Yakovlev, Sergiy Wojciechowski, Adam Podzeha, Dmytro Illiashenko, Oleg Yakovleva, Iryna National Aerospace University 'KhAI' Kharkiv61070 Ukraine Lodz University of Technology Lodz90-924 Poland Institute of Information Science and Technologies 'Alessandro Faedo' - Isti Cnr Software Engineering & Dependable Computing Laboratory Pisa56124 Italy National University of Urban Economy in Kharkiv Kharkiv61002 Ukraine

ISBN: (纸本)9798350358056

The paper investigates the problem of optimizing a sensor network for monitoring a continuous area, considering the bounded coverage areas of sensors. This task is formulated in terms of the maximum coverage location problem. A mathematical model is proposed as a two-criteria optimization problem. The objective functions are the maximum area of the covered part of the region and the minimum total overlapping of sensor coverage areas. This model is transformed into an elastic (quasi-physical quasi-human) model, which differs from the known one in forming the extrusion potential energy function. To solve the problem, an original approach was implemented, combining local and global optimization stages. At the stage of local optimization, the Broyden-Fletcher-Goldfarb-Shanno method was used, in which the gradients were calculated analytically or from first-order differences depending on the shape of sensor coverage areas. At the stage of local optimization, the multistart method was used. The implementation of the approach has been tested for the polygonal shape of the region and elliptical shapes of the sensor coverage areas. © 2023 IEEE.

关键词： elastic model mathematical model maximum coverage location problem optimization sensor network testing

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advanced Frost sensor for HVAC applications

Advanced Frost Sensor for HVAC Applications

引用

2024 ASHRAE Winter conference

作者： Gao, Zhiming Brechtl, Jamieson Nawaz, Kashif Fricke, Brian Gluesenkamp, Kyle Lavrik, Nickolay Boudreaux, Philip Li, Kai Oak Ridge National Laboratory United States The Center for Nanophase Materials Sciences Oak Ridge National Laboratory United States Oak Ridge National Laboratory United States Oak Ridge National Laboratory United States

ISBN: (纸本)9781955516822

Frost is a common problem in heating, ventilation, and air conditioning (HVAC) systems that can degrade their efficiencies, leading to excessive electricity consumption. Appropriate defrosting is therefore essential for heat pumps and refrigeration systems. However, these systems typically run the defrost cycle based on a predetermined time interval, a method that does not accurately identify the amount of frost and thus consume excessive electricity. This paper describes development of a smart sensor that can substantially improve defrosting initiation and termination and is based on a capacitive sensing technique that can quantify frost accumulation and distinguish the difference between frost, ice, and water. The reported sensor employs interdigitated comb electrodes and can be updated to a potential multifunctional sensor array for enhanced identification of frost, ice, and water via the integrated measurement of surface temperature, frost capacitance, and resistance. The proposed frost sensor is expected to have widespread applications in HVAC systems, including heat pumps, refrigerators, and commercial refrigeration systems. © 2024 U.S. Government.

关键词： Defrosting

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Increasing Order of Digital Filters of the Same Type in Robotic systems 12

Increasing Order of Digital Filters of the Same Type in Robo...

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12th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems: Technology and applications, IDAACS 2023

作者： Sytnikov, Tykhon Sytnikov, Valerii Streltsov, Oleh Stupen, Pavlo Odessa Polytechnic National University Odessa65044 Ukraine

ISBN: (纸本)9798350358056

Considering the issues of the filter order in a signal processing channel with sensors, through the serial link of the same type filters with low order. New approach to define cutoff frequency of such link was obtained. This solution allows quickly change the order and bandwidth of bandpass filters in robotic mobile platforms with limited computing resources. Proposed using a preliminary calculation of such frequencies, depending on the number of serial links of the same type of filters. This allows quickly rebuild the sensor signal processing channel. © 2023 IEEE.

关键词： AFC bandpass filters cutoff frequencies frequency-dependent components Industry 4.0-5.0 robotic systems serial link of components

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Intelligent Fruit Quality Monitoring System using sensor Networks and Deep Learning

Intelligent Fruit Quality Monitoring System using Sensor Net...

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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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advanced Camouflage Robot for Military Spying applications using sensor Fusion and Machine Learning 3

Advanced Camouflage Robot for Military Spying Applications u...

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3rd IEEE International conference on Blockchain and Distributed systems Security, ICBDS 2024

作者： Kulkarni, Neeraj P Khan, Subim N. Rathod, Rahul Ramkishan Choure, Ajay Raosaheb Chinchole, Mahesh Gokul Jspm Rajarshi Shahu College of Engineering Tathawade Pune India Soet D Y Patil University Ambi Pune India Bhivarabai Sawant Institute Of Technology And Research E&tc Department Wagholi Pune India Nutan Maharashtra Institute of Engineering and Technology E&tc Department Pune India

ISBN: (纸本)9798350354348

The current defense application scenario. the ability to blend into the environment is crucial for reducing detection and enhancing operational efficiency. This paper presents the development of an advanced camouflage robot to dynamically adapt its color to match its surroundings. The proposed system utilizes a combination of machine learning, computer vision, and sensor fusion to achieve camouflaging using the RGB LED panels mounted on the robot to adapt to the color of the surroundings. The robot is equipped with a video camera system that captures real-time video feed of the environment. The captured video is then processed by a trained machine learning model, which analyzes the color distribution in the surroundings. Simultaneously, the robot uses RGB color sensors to accurately detect the colors present in its immediate vicinity. The data from both the camera and the sensors are integrated to determine the predominant color around the robot. The hybrid camouflaging approach involves feeding the combined data into the machine learning model, which then calculates the color of maximum distribution. The robot then activates its RGB panels, adjusting their color to blend with the identified predominant color in the environment thereby making it difficult to locate. This process allows the robot to effectively camouflage itself, minimizing its visual footprint. KNN and sensor fusion techniques are used to achieve this task. © 2024 IEEE.

关键词： Nearest neighbor search

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