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检索条件"任意字段=Conference on Advanced Sensor and Control-System Interface"

共 6868 条记录，以下是961-970 订阅

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An Optimized system for Maize Seed Sowing And Soil Moisture control

An Optimized System for Maize Seed Sowing And Soil Moisture ...

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Smart Electronics and Communication (ICOSEC), International conference on

作者： Thiyagarajan Jayaraman E Kannan S Deepak M S Gowtham T P Nirmal S V Gokul Krishna Department of Mechatronics Engineering Sona College of Technology Salem India Department of EEE KSR College of Engineering Namkkal India

ISBN: (数字)9798331504403

ISBN: (纸本)9798331504410

Agriculture is the backbone of many nations’ economies. As India is an agricultural country where, 70% of the population depends on farming, the processing of grains plays a vital role in the national economy. Maize (Zea mays) stands as one of the world’s most crucial cereal crops, contributing significantly to global food security and economic stability. However, maximizing maize yield requires a complete understanding of its cultivation practices, particularly concerning seed sowing techniques and soil moisture management. The proposed system explores the integration of optimized maize seed sowing methods and advanced soil moisture monitoring systems to enhance crop productivity while ensuring sustainable agricultural practices. This research study highlights the critical role of integrating advanced agronomic practices, such as precision seed sowing and soil moisture monitoring, in modern maize production systems. By adopting these integrated approaches, farmers can not only enhance crop resilience and productivity but also contribute to sustainable agriculture practices and food security in a changing climate scenario.

关键词： Productivity Soil moisture Moisture Food security sensor systems Real-time systems Seeds (agriculture) sensors Monitoring Resilience

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Real Time Implementation of a Speed/Torque sensorless Observer for Induction Motor Utilizing Extended Kalman Filtering Technique

Real Time Implementation of a Speed/Torque Sensorless Observ...

引用

International conference on advanced Electrical Engineering (ICAEE)

作者： Younes Djellouli Sid Ahmed El Mehdi ARDJOUN Emrah Zerdali Mouloud Denai Houcine Chafouk IRECOM Laboratory Faculty of Electrical Engineering Djillali Liabes University Sidi Bel-Abbes Algeria Department of Electrical and Electronics Engineering Ege University Izmir Turkiye Higher School of Elecrical Engineering and Energetics Oran Algeria Normandy University UNIROUEN ESIGELEC IRSEEM Rouen France

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349368

sensorless induction motor (IM) drives eliminate the problems encountered with physical sensors such as the complexity of the installation, cost, and accuracy of the measurements. This paper presents the design and real-time implementation of speed and torque observers for IMs. The observer is based on the extended Kalman filter (EKF) known for its ability to handle nonlinear systems and noise. The aim is to accurately predict the crucial operational point of IMs without direct measurement. The paper discusses the theoretical framework of the EKF, detailing its real-time implementation for induction motor control. The experimental results demonstrate the effectiveness of the proposed EKF-based speed/torque observer as a viable alternative to traditional speed/torque sensors. Consequently, the proposed solution brings tangible benefits such as reducing the drive system's size, enhanced system reliability, improved motor efficiency and reduced costs.

关键词： Induction motors Costs Torque Observers Real-time systems sensor systems Kalman filters Reliability Noise measurement Nonlinear systems

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A Noise Filter for Dynamic Vision sensor Based on Spatiotemporal Correlation and Hot Pixel Detection

A Noise Filter for Dynamic Vision Sensor Based on Spatiotemp...

引用

International conference on Autonomous Unmanned systems, ICAUS 2021

作者： Xu, Ninghui Zhao, Jiajia Ren, Yuan Wang, Lihui Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of Education School of Instrument Science and Engineering Southeast University Nanjing210096 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789811694912

As a new type of neuromorphic sensor, the events-driven Dynamic Vision sensor (DVS) has the advantages of low latency and wide dynamic range. The development of DVS overcomes the application limitations of traditional cameras in the field of high speed robots and autonomous driving. However, there are abundant unwanted noise events contained in the output of DVS, which severely affects the subsequent data-processing. To tackle the problem, a novel noise filter for DVS is proposed in this paper. Firstly, since the noise is composed of hot pixel events with high-frequency and random background activities, a time window is constructed to continuously detect hot pixels. Secondly, a spatiotemporal correlation-based denoising approach for each incoming event is conducted, while excluding its surrounding hot pixels, to avoid the negative effect caused by their high temporal correlation on the filter. Finally, the hot pixels are compensated with the events that are most probably to occur depending on the adjacent events, to achieve the completeness and precision of the output event stream. Experiments in different scenes demonstrate that the proposed noise filter can effectively eliminate the noise from the event stream of DVS and obviously outperforms the baseline method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Pixels

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Design and Implementation of FPGA based Rescue Bot

Design and Implementation of FPGA based Rescue Bot

引用

International conference on Computing Methodologies and Communication (ICCMC)

作者： K. SUDHAKAR S. SHANKAR PIRAJIN J. SHANMUGAPRIYAN S. SUJEETH Electronics and Communication Engineering M.Kumarasamy College of Engineering Karur India

Presently, surveillance in border areas is a very difficult feat. The security staff is enforcing the law at the border in a hostile way. Already implanted video surveillance is helpful, but they would only cover a tiny area. Due to the incapacity to instantly change the camera point of view, the cameras that already are left in place are not very invaluable. Also, it is not permitted to put cameras in tropical areas since trees obstruct the cameras' angle of view. The design and implementation of a wireless robot that can recognize about internet and it can able to detect matter with the help of a passive infrared sensor are obscured in the given paper. The entire system consists of an Internet-controlled mobile robot with a mounted camera and a PIR sensor for the detection of living creatures. The user will have wireless control of the robot thanks to the ability to operate it through the internet. The PIR sensor will also provide the user with information about the detection of live beings on the computer, and the user can also view the robot's video transmission at the same time. The arm camera can move vertically along its vertical axis and diagonally around its vertical axis. The user interface on the internet allows the user to control the camera's movement, giving them a better perspective of their surroundings.

关键词： Wireless communication Wireless sensor networks Robot vision systems Vegetation User interfaces Cameras Video surveillance

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Review and application of Edge AI solutions for mobile collaborative robotic platforms 55

Review and application of Edge AI solutions for mobile colla...

引用

55th CIRP conference on Manufacturing systems, CIRP CMS 2022

作者： Ramasubramanian, Aswin K. Mathew, Robins Preet, Inder Papakostas, Nikolaos Laboratory for Advanced Manufacturing Simulation and Robotics School of Mechanical and Materials Engineering University College Dublin Ireland CeADAR-Ireland's Center for Applied AI University College Dublin Ireland

Edge AI technologies have emerged as a powerful solution for gathering and processing data in real-time, supporting the development of advanced applications for process monitoring, planning and control. Edge AI devices coupled with different sensory systems can be used for facilitating the synergetic human-robot collaboration at the shop floor level. This paper reviews edge AI devices and solutions that may potentially support the operation of cells or workstations comprising human operators and mobile robotic platforms. The use of edge AI-capable devices for operator tracking in real-world applications and the potential of edge AI technologies towards developing and deploying process digital twins are discussed. The main goal is to investigate how edge AI solutions may improve the performance of processes where a collaborative mobile manipulator works alongside a human operator in a safe and reliable manner. Lastly, the use of advanced communication frameworks, such as the Robot Operating system (ROS), is discussed in the context of supporting the seamless interaction between a collaborative mobile platform and Edge AI devices. © 2022 The Authors. Published by Elsevier B.V.

关键词： Collaborative Manipulators control Robot sensor

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Design and Development of RV-IoT Board - Prototyping Platform for Designing IoT Projects

Design and Development of RV-IoT Board - Prototyping Platfor...

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International conference on Computation system and Information Technology for Sustainable Solutions (CSITSS)

作者： K Badari Nath Shreyas Shankar Sumith S Tantry S Varun Vinay Kalagi Department of CSE R.V. College Of Engineering Bengaluru India

ISBN: (数字)9798331505462

ISBN: (纸本)9798331505479

An All-In-One IoT board offers benefits such as a simplified and convenient development platform. It integrates various hardware components on a single board, reduces the physical footprint, accelerates prototyping, and ensures compatibility and reliability of integrated parts. These boards are power-efficient, cost-effective in the long run, and facilitate easier debugging and troubleshooting. They are made for rapid iterative development, making them ideal for educational purposes whilst catering to a diverse range of IoT project needs. Many industries such as Home Automation, Energy, Healthcare, Retail and Agriculture are extensively using embedded systems. Though different industries have different needs, most embedded system projects rely on using sensors to obtain inputs, the microcontroller for computations and actuators to provide outputs. With this in mind, a plethora of parts along with an ESP-32 microcontroller were used in the proposed board. As the primary purpose of the board is for education and prototyping, it is predicted that certain parts will suffer frequent damage and will need replacing. Therefore, the part selection process placed emphasis on cost-effectiveness, robustness, and market availability of parts. The design process was focused on increasing the board's robustness and providing a plug-and-play system. In addition, opto-isolators were used to protect the board from high voltage inputs. With inputs from industry professionals, the proposed design features essential components such as SD card interface for storage, a TFT touchscreen display, Audio modules, keypad input, an array of sensors, and motor control interfaces. Using these, prototype projects such as cloud data loggers, remote-controlled audio players, vending machines, and automated irrigation systems were developed in laboratory environments.

关键词： Technological innovation Embedded systems Microcontrollers Tactile sensors Touch sensitive screens sensor phenomena and characterization Robustness sensor systems Thin film transistors sensor arrays

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IoT-Based Smart Home system Integrated with Deep Learning on the FPGA Development Board

IoT-Based Smart Home System Integrated with Deep Learning on...

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IEEE International conference on systems, Man and Cybernetics

作者： Guo-Ming Sung Fan-Ning Kuo Chih-Yu Lin Chwan-Lu Tseng Jen-Hsiang Chou Li-Fen Tung Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

This study proposes an Internet of Things (IoT)-based smart home system that sends and receives packets through the RS232 protocol and processes them using deep learning. A Field-Programmable Gate Array (FPGA) development board serves as a transceiver, operating a universal serial bus (USB) interface and a Wi-Fi module. The proposed system comprises a built-in wireless transceiver, a set of sensors, a development board running a deep learning algorithm, an MQTT communication protocol, and a terminal device controller. The objective is to implement an IoT -based smart home system with wireless data transmission. Node-RED is used to develop a comprehensive smart home system on the server side for IoT applications, facilitating data access, data processing, and terminal device control. The aim is to achieve automatic regulation and ensure comfortable indoor temperatures. In experiments, the root mean squared error difference between actual and predicted temperatures was approximately 0.4426 °C. After evaluation experiments with the FPGA development board, an application-specific integrated circuit (ASIC) based on the TSMC 0.18-μm CMOS process was used. Simulation results indicate that the chip area is approximately 1.186 × 1.188 mm 2 , and the dynamic power consumption is approximately 8.1674 mW at a power supply of 1.8 V and operating frequencies of 50 and 5 MHz.

关键词： Deep learning Wireless communication Wireless sensor networks Smart homes Universal Serial Bus Temperature control Internet of Things Servers Field programmable gate arrays Wireless fidelity

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Design and Optimization of a Wearable Sonomyography sensor for Dynamic Muscle Activity Monitoring

Design and Optimization of a Wearable Sonomyography Sensor f...

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Applied Sensing conference (APSCON), IEEE

作者： Anne Tryphosa Kamatham Biswarup Mukherjee Centre for Biomedical Engineering Indian Institute of Technology Delhi India

Sonomyography is a non-invasive modality that uses ultrasound for sensing muscle activity. The ability of this modality to robustly sense muscle activity with good resolution makes it suitable as a biomechatronic control interface. However, the most sonomyography-based studies utilize B-mode ultrasound imaging which require large form-factor clinical ultrasound imaging devices. In order to extend the utility of sonomyography techniques to wearable systems, the size of the ultrasound system and associated sensors needs to be greatly reduced. In this paper, we design and optimize the performance of a wearable ultrasound sensor for muscle activity monitoring applications. We fabricated a custom ultrasound transducer with a backing layer by mixing varying amounts of Tungsten powder to epoxy resin to optimize the bandwidth of the transducer. Our results showed that increasing the proportion of Tungsten improves the bandwidth of the transducers. Following optimization of the transducer design, we developed a wearable sonomyography sensor and demonstrated real-time measurement of dynamic muscle activity during hand open-close movement.

关键词： Image sensors Ultrasonic imaging Transducers Tungsten Bandwidth Muscles Biomedical monitoring

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Classifying EEG-based Upper Limb Motor Imagery Tasks for Brain-Robot interface-based system Development

Classifying EEG-based Upper Limb Motor Imagery Tasks for Bra...

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International conference on advanced Robotics and Mechatronics (ICARM)

作者： Kuldeep Gurjar Sanskar Agrawal Kazi Newaj Faisal Rishi Raj Sharma Department of Electronics Engineering Defence Institute of Advanced Technology Pune India

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Cognitive robotics and engineering strive to develop brain-robot interfaces (BRI) that enable effective collaboration between robots and humans. The continued advancements in neuroscience, robotics, and machine learning are projected to broaden the scope of BRI applications, ultimately improving human-robot cooperation. A major area of focus for BRI-based system development involves mapping brain activities to control actions through motor imagery (MI) based technologies such as electroencephalogram (EEG). In this paper, a novel technique for classifying different tasks involving MI of upper limb movements from EEG signals is presented. To emphasize the inter-related information within various bands of EEG signals, ratio of band power (RBP)-based features are proposed for categorizing different upper limb-based MI tasks. The combination of these proposed features and an optimized KNN classifier produced remarkable accuracy in classifying diverse MI tasks from EEG signals. This approach was compared with recent methods applied to the same dataset, illustrating its superiority in performance. Furthermore, a comparison between the proposed RBP-based features and conventional band power-based features underscored the effectiveness of RBP-based attributes for classifying MI-related tasks. The improved effectiveness of the proposed approach could lead to progress in BRI-based systems development across a range of applications.

关键词： Accuracy Sensitivity Signal processing algorithms Machine learning Nearest neighbor methods Signal processing Motors Electroencephalography Reliability Signal to noise ratio

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Application of Deep Neural Networks for EEG Signal Processing in Brain-controlled Wheeled Robotic Platform 11

Application of Deep Neural Networks for EEG Signal Processin...

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11th IEEE International conference on Intelligent Data Acquisition and advanced Computing systems - Technology and Applications (IDAACS)

作者： Artemuk, Serhii Brydinskyi, Vitalii Mykytyn, Ihor Khoma, Yuriy Lviv Polytech Natl Univ 12 Bandera St UA-79013 Lvov Ukraine

ISBN: (纸本)9781665426053

The article describes the essence of functioning of the neural computer interface, as well as provides the prototype of the custom neural computer control system, which includes the helmet with the Open BCI Cyton platform, BCI-server on the basis of the personal computer and, the wheeled robot itself with the on-board computer Raspberry Pi. Transmission of the recorded 16-channel EEG-records onto the BCI-server is performed using the Bluetooth protocol, and the Wi-Fi standard is applied for the communication between the robot and the BCI-server. The main task was to create and research the possibility of application of the deep learning technologies to classification of the filtered signals (frequency band of the EEG Alpha-waves) under relatively low data volume scenario. Program architecture and system functioning algorithm are presented, convolutional neural network and the multi-layer perceptron are researched as the neural classifiers. EEG-signals filtering and their classification are performed on the BCI-server. Neuroclassifier on the basis of the convolutional neural network showed higher accuracy, however it demands bigger calculating resources for its realization.

关键词： EEG-signals 'brain-computer' interface deep learning convolutional neural networks multilayer perceptron

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