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Refractive index sensor based on Fano resonance in a ring with a stub cavity structure 4

Refractive index sensor based on Fano resonance in a ring wi...

引用

4th International conference on intelligent Control, Measurement and Signal processing, ICMSP 2022

作者： Wu, Wenchang Zhang, Xiaoyu Chen, Zhanbo Zhang, Yi Wen, Feng Yan, Shubin The College of Electron and Information Engineering Ningbo University of Technology Ningbo China The College of Electrical and Control Engineering North University of China Taiyuan China The College of Electrical Engineering Zhejiang University of Water Resources and Electric Power Hangzhou China The College of Instrument and Electronics North University of China Taiyuan China

ISBN: (数字)9781665486583

ISBN: (纸本)9781665486583

With the continuous development of sensors and the continuous progress of detection technology, the optical sensors based on SPPs are expected to have an excellent prospects in the field of sensing. Herein, a novel refractive index sensor is presented, which consists of a metal-insulator-metal (MIM) waveguide with two rectangular baffles and circular ring cavity with a stub (CRCS). The characteristics of sensor are analyzed theoretically by finite element method. The simulation results showed that the narrow-band modes directly excited by the CRCS resonator interfere with the broad-band modes indirectly excited by the MIM waveguide, resulting in the formation of the Fano resonance phenomenon. A maximum sensitivity is 2520 nm/RIU and the figure of merit (FOM) is 61.46. The simple structure and high sensitivity lay a foundation for the application of high sensitivity plasmonic sensor in biomedical and temperature detection fields. © 2022 IEEE.

关键词： Finite element method

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Voice Controlled Smart Home System

Voice Controlled Smart Home System

引用

Network, Multimedia and information Technology (NMITCON) International conference on

作者： K Manjula V Dhananjaya Computer Science & Engineering Nitte Meenakshi Institute of Technology Bangalore India Computer Science & Engineering Impact college of Engineering Bangalore India

ISBN: (数字)9798350372892

ISBN: (纸本)9798350372908

The Internet of Things (IoT) is a significant technological advancement that uses the internet to enable seamless communication between various devices, allowing people and objects to connect anytime and from anywhere. In this research, we present an intelligent smart automation model that can remotely operate household appliances and water the garden plants from anywhere in the world. “Home automation” is a quickly emerging technology that minimizes the work that humans must perform. Certain home automation systems are offered to people seeking luxurious, advanced home automation systems. This method is safe because it works best for the elderly and disabled people. However, certain people could find it more challenging to use certain systems because of their special demands. The system’s primary features are voice recognition and intelligent interaction. Our main objective is to develop an advanced home automation system that has combined Alexa with the ESP 8266 module to improve security, reduce power consumption and minimize user effort. The model includes two essential sensors, a soil moisture sensor, a temperature and humidity sensor. All hardware components in this model are cost-effective, readily available, and easily replaceable.

关键词： Temperature sensors Smart agriculture Home appliances Virtual assistants Soil moisture Smart homes Speech recognition Internet of Things Usability intelligent sensors

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Design and Implementation of intelligent Acquisition Terminal Based on Modbus 14

Design and Implementation of Intelligent Acquisition Termina...

引用

14th IEEE International conference on Computational Intelligence and Communication networks, CICN 2022

作者： Zhang, Bin Hu, Shejiao Hefei University of Technology Dept. of Information and Communication Engineering Anhui China

ISBN: (纸本)9781665487719

With the continuous development of social economy, intelligent acquisition terminal plays an important role in some remote and abusive environments. In this paper, an intelligent integrated acquisition terminal is proposed, which can be effectively applied to irrigation area information collection, earthquake disaster monitoring and other scenarios. The acquisition terminal (RTU) proposed in this paper adopts a design scheme combining GD32F407 embedded system and embedded industrial computer to complete data collection, processing, transmission, display, storage and intelligent control of equipment. The RTU acquisition base plate is designed by GD32F407 chip, including RS485, 4-20MA, SSI Gray code, relay control, Ethernet and other interfaces [1]. The RS485 interface uses Modbus Rtu protocol to request data from sensors connected to the outside. SSI Gray code interface can be connected to absolute value encoder to collect data, gray code interface carries on data transmission through 422 interface on hardware, and carries on data latching at corresponding edge through analog clock signal on software level. Modbus TCP protocol is used to exchange information between the acquisition baseboard and the industrial computer through Ethernet. The industrial computer runs the fast control configuration software, which can receive the transmitted data and realize intelligent control of external devices. © 2022 IEEE.

关键词： Embedded systems

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Comparison Study of Inertial sensor Signal Combination for Human Activity Recognition based on Convolutional Neural networks 15

Comparison Study of Inertial Sensor Signal Combination for H...

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15th IEEE International conference on Human System Interaction (HSI)

作者： Nazari, Farhad Mohajer, Navid Nahavandi, Darius Khosravi, Abbas Nahavandi, Saeid Deakin Univ Inst Intelligent Syst Res & Innovat IISRI Melbourne Vic Australia

ISBN: (数字)9781665468220

ISBN: (纸本)9781665468220

Human Activity Recognition (HAR) is one of the essential building blocks of so many applications like security, monitoring, the internet of things and human-robot interaction. The research community has developed various methodologies to detect human activity based on various input types. However, most of the research in the field has been focused on applications other than human-in-the-centre applications. This paper focused on optimising the input signals to maximise the HAR performance from wearable sensors. A model based on Convolutional Neural networks (CNN) has been proposed and trained on different signal combinations of three Inertial Measurement Units (IMU) that exhibit the movements of the dominant hand, leg and chest of the subject. The results demonstrate k-fold cross-validation accuracy between 99.77 and 99.98% for signals with the modality of 12 or higher. The performance of lower dimension signals, except signals containing information from both chest and ankle, was far inferior, showing between 73 and 85% accuracy.

关键词： Human Activity Recognition Assistive Devices Convolutional Neural networks Classification

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Adaptive FCM Clustering Routing Algorithm Based on PSO Optimization

Adaptive FCM Clustering Routing Algorithm Based on PSO Optim...

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Signal processing and intelligent Computing (SPIC), International conference on

作者： Yue Liu Ying Liang School of Information Science and Engineering Shenyang Ligong University Shenyang China

ISBN: (数字)9798350368888

ISBN: (纸本)9798350368895

To solve the problems of large node energy consumption and missing data transmission path in Marine sensor networks, a clustering routing algorithm utilizing particle swarm optimization (PSO-DAFCA) was introduced. The algorithm uses fuzzy C-means method of particle swarm optimization to optimize cluster head selection and cluster member configuration, and selects the best cluster head by dynamically updating cluster center. During the data transmission phase, combined with the global search ability of cat swarm optimization algorithm, the path evaluation function based on energy and distance parameters is introduced to determine the optimal transmission route. Simulation results indicate that the PSO-DAFCA algorithm can enhance network energy efficiency, prolong network lifespan, and improve the real-time accuracy of marine environmental monitoring.

关键词： Wireless communication Energy consumption Wireless sensor networks Heuristic algorithms Simulation Signal processing algorithms Clustering algorithms Routing Data communication Particle swarm optimization

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Impaired behavior recognition based on multi-head-Siamese neural network

Impaired behavior recognition based on multi-head-Siamese ne...

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2022 International conference on Image, Signal processing, and Pattern Recognition, ISPP 2022

作者： Lun, M.A. Xin, Liu Zhao, Bin Wang, Ruiping Zhang, Yajing School of Information Engineering Chang’an University Shaanxi Xi’an710064 China

ISBN: (纸本)9781510654846

sensor-based human behavior recognition is a classification recognition task and is widely used in medical care, environmentally assisted living, and other fields. But multiple sensors sense the impaired behavior without considering the correlation between sensors. In this paper, a multi-head-siamese neural network, combined with weight sharing is proposed based on deep learning theory. The network hyperparameters are adjusted by Bayesian optimization. Due to the problem of over-fitting during impaired behavior recognition introduced by Adam optimizer, L2 regularization is improved by using AdamW optimizer. processing results of raw data show that the network achieves a classification accuracy of 96.0%. Compared with the baseline network and single input network, its accuracy has increased by 6.1% and 8.8% respectively. Compared with multiple input network, its accuracy has increased by 2.4%, and reduced the number of training parameters by 92%. Verified the effectiveness of the proposed network for impaired behavior recognition © 2022 SPIE.

关键词： Neural networks

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Integrating Wireless sensor networks with Organic Polymers for Sustainable 8

Integrating Wireless Sensor Networks with Organic Polymers f...

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8th International Technical conference on Frontiers of Hydraulic and Civil Engineering Technology, HCET 2023

作者： Yumalin, T.T. Salikhov, R.B. Salikhov, T.R. Ufa University of Science and Technology Z. Validi St. 32 Ufa450076 Russia

ISBN: (纸本)9781643684642

Advancements in compact integrated circuit fabrication have significantly progressed, allowing for the integration of wireless transceivers, signal processing units, and sensors into a unified and compact unit. This technological breakthrough has paved the way for seamless interactions with the physical world, finding applications across various domains, including security, production management, and environmental monitoring. In this study, we delve into the intricate design aspects of a distributed sensor network, where each node operates within defined energy and communication constraints. The integration of prevailing wireless technologies, computational capabilities, and organic polymers into an innovative generation of intelligent devices represents a critical dimension of our exploration. This article meticulously examines the implementation of a wireless sensor network employing the Bluetooth Low Energy (BLE) protocol. The incorporation of organic polymers as a sensing layer amplifies energy efficiency and enables selective sensitivity in diverse monitoring applications. A notable advantage is the rapid and cost-effective production of electronics using organic polymers, underlining their substantial potential. Furthermore, we emphasize flexible organic electronics, underpinned by the semiconducting and flexible properties inherent in organic materials, constituting a fundamental element of our technological paradigm. Key prerequisites for achieving optimal operational device performance are thoroughly discussed, encompassing achievements and technical challenges in the design and fabrication of next-generation devices, with a keen focus on product optimization. © 2023 The Authors.

关键词： Energy efficiency

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Enhancement of a Smart Assistive Cane for Visually Impaired People Based on IoT

Enhancement of a Smart Assistive Cane for Visually Impaired ...

引用

Advances in Engineering Science and Technology (AEST), International conference on

作者： Laith Ali Abdul-Rahaim Alaa J. Mousa Alaa H. Omran Luay Mahdi Kadhum Department of Electrical Engineering College of Engineering University of Babylon Babylon Iraq Department of Technical Communication Engineering Al-Shaab University Baghdad Iraq Department of Information System Management University of Information Technology and Communication Baghdad Iraq

ISBN: (数字)9798331502690

ISBN: (纸本)9798331502706

This paper presents the design and implementation of an intelligent assistive cane for visually impaired individuals, integrating multiple sensors and wireless communication technologies to enhance mobility and safety. The system incorporates an ultrasonic sensor, a GPS device, a gyroscope, and a heartbeat rate sensor, all connected to an Arduino microcontroller. The ultrasonic sensor detects obstacles in the user’s path, providing real-time feedback to help avoid collisions. The GPS device enables outdoor navigation, offering location tracking and assistance for route guidance. The gyroscope measures the orientation and movement of the cane, providing data for better navigation control and detecting sudden changes in posture. Additionally, the heartbeat rate sensor continuously monitors the user’s physical condition, alerting them of any abnormal readings. The data collected by these sensors is wirelessly transmitted to a cloud computing platform for real-time processing and analysis. This cloud-based approach allows for continuous monitoring, remote assistance, and data storage, offering a robust, scalable solution for enhancing the independence and safety of visually impaired individuals. The design of the intelligent cane provides an innovative approach to assistive technology, combining environmental sensing, health monitoring, and cloud integration to offer a comprehensive aid for the visually impaired.

关键词： Cloud computing Navigation Heart beat sensor systems Real-time systems Safety Gyroscopes intelligent sensors Monitoring Global Positioning System

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Design of Multi-target Tracking Algorithm Based on Multi-sensor Fusion 3rd

Design of Multi-target Tracking Algorithm Based on Multi-sen...

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3rd International conference on Artificial Intelligence, 2022

作者： Song, Zhangchi Qiang, Xiaomin Sun, Peng Cao, Laitian Zhang, Lijia Yang, Baisheng Beijing Aerospace Automatic Control Institute Beijing100854 China National Key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing100854 China

ISBN: (纸本)9789811694226

In the modern battlefield environment, the traditional single sensor often cannot give full play to its optimal performance. The advantages of different sensors are used for combined detection and tracking to obtain all-round multi-dimensional information of the target. Through multi-sensor fusion processing, interference is eliminated, and the target state estimation is obtained to achieve precise positioning of the target. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Target tracking

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Multiple Input Single Target Streamflow Forecast by Neurowavelet networks 2

Multiple Input Single Target Streamflow Forecast by Neurowav...

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2nd IEEE International conference on information Communication and Software Engineering (ICICSE) / 7th International conference on Mathematics and Artificial Intelligence (ICMAI)

作者： Criswell, Jackson A. Cent Michigan Univ Dept Math Mt Pleasant MI 48859 USA

ISBN: (纸本)9781665482202

In this work a methodology of time series analysis and forecasting is implemented and tested against streamfiow data measured from the Mississippi River. Measurements from a set of twelve data stations along the river is used in various configuration to test the potential improvement in predictive efficiency from incorporation of a network of sensors. The forecast system is based on combining the discrete wavelet transform with the well-established feed forward non-linear auto regressive design multilayer perceptron artificial neural network. These networks, referred to as neurowavelets, are able to improve predictive ability. The novel neurowavelet system is capable of processing multiple external inputs with separate selection of wavelet family and resolution. Improved performance and stability is gained through an evolutionary genetic algorithm applied to the backpropagation training process combined with the use of ensemble learning. The system is tested both with and without performing multiresolution analysis of the inputs and a clear advantage is seen when introducing the wavelet decomposition. Results show improvement from the refined model and best forecast performance is obtained from use of the full sensor cascade and the Coiflet wavelet family.

关键词： mathematical analysis applied computing earth sciences algorithms neural networks wavelets

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