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检索条件"任意字段=International Conference on Sensor Technologies and Applications, SensorComm"

共 9417 条记录，以下是361-370 订阅

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An Investigation on Leveraging Wireless sensor Networks and Radio Frequency Identification to Develop Internet of Things applications 14

An Investigation on Leveraging Wireless Sensor Networks and ...

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14th international conference on Advances in Computing, Control, and Telecommunication technologies, ACT 2023

作者： Suryawanshi, Soham Patankar, Nikhil S. Deshmukh, Yogesh S. Shelake, Nitin L. Sanjivani College of Engineering Department of Information Technology Kopargaon India

This topic provides a critical analysis of various Internet of Things (IoT)-based applications. This topic describes how IoT devices evolved from mobile computing and ubiquitous computing. It emphasizes the fact that objects, rather than people, are linked via the internet. Product information, electronic tags, standards expressed, and uploading information are examples of Internet of Things (IoT) properties. It uses Radio Intensity Identification (RFID) technology and wireless sensor (WSN). RFID technology uses that allows objects or people to be tracked and is primarily used in critical applications such as industrial control, and personnel connects direct connections. Demand for delivering positional information has grown significantly in recent years, and RFID positioning techniques are emerging, particularly for indoor locating, due to their rapid development and implementation. IoT applications are often used in domains such as healthcare, supply chain management, defense, and defense Ture WSN provides information about the physical conditions of objects, allowing for the creation of cost-effective services tailored to application needs. Thus, RFID but rather WSN integration is a developing technology that takes advantage of both systems' advantages, making it reliable and efficient. Finally, the paper concentrates on IoT issues. though this is a boon, IoT poses an IoT of challenges such as privacy and security. © Grenze Scientific Society, 2023.

关键词： Radio frequency identification (RFID)

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An improved Dynamic Traffic Routing Protocols for WSNs using Machine learning 15

An improved Dynamic Traffic Routing Protocols for WSNs using...

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15th international conference on Computing Communication and Networking technologies, ICCCNT 2024

作者： Jayanthi, P.R. Prabha, M. Sakthi Saravanan, N. Gunasundari, V. Ayyadurai, M. Mailam Engineering College Department of Cse Mailam India Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Chennai India S.A. Engineering College Department of Eee Chennai India Nandha Engineering College Department of Ece Erode Perundurai India Rajalakshmi Engineering College Department of Cse Chennai India

ISBN: (纸本)9798350370249

Wi-Fi sensor Networks (WSNs) are extensively used in various environmental monitoring applications, health care, and intelligent towns. However, WSNs face demanding situations of limited power and computational capabilities, which could cause network congestion and inefficient visitor routing. To cope with these problems, this has a look at proposes a progressed Dynamic Visitors Routing Protocol (DTRP) for WSNs, the usage of gadgets gaining knowledge of (ML) strategies. The proposed DTRP uses ML algorithms to predict the network site visitor load and regulate the routing paths dynamically. This facilitates balancing the visitor's load distribution and reduces community congestion, leading to advanced network overall performance. The ML algorithms are trained on historical statistics and adapt to converting traffic situations, making the network more resilient to unexpected events. The DTRP employs a hierarchical routing scheme, dividing the community into clusters to decrease the routing overhead. The clustering system uses a green energy-conscious algorithm to ensure balanced energy consumption and prolong the network lifetime. © 2024 IEEE.

关键词： Algorithm Congestion Facilitates Intelligent sensor Networks

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Can wearable technologies contribute to an age-friendly walkability environment? First insights from a systematic review of the literature 17

Can wearable technologies contribute to an age-friendly walk...

引用

17th international conference on PErvasive technologies Related to Assistive Environments (PETRA)

作者： Milella, Frida Oltolini, Michela Bandini, Stefania Univ Milano Bicocca Dept Informat Syst & Commun DISCo Milan Italy

ISBN: (纸本)9798400717604

Research on wearable devices and sensors applied to older adults has witnessed significant growth, primarily focusing on health monitoring but also on researching real-world applications of urban walking, specifically, walkability. The use of pedestrians' bodily responses to the environment, known as the people-centric sensing strategy, has been demonstrated to be more suitable for detecting challenging environmental conditions and enhancing walkability. However, the extent to which such data may accurately pinpoint environmental distress in a particular demographic, such as older adults, has not been thoroughly investigated. The purpose of this in-progress systematic review of the literature is to outline the strategy employed and highlight some preliminary findings on the use of wearable sensors or sensor-based technologies in gathering the bodily responses of older adults and/or their family caregivers to stimuli originating from real urban walking scenarios. Our preliminary findings showed that the current research on using wearable devices to detect bodily responses in older adults (or informal caregivers) population in relation to walkability in outdoor environments tends to exhibit a uniform strategy, that is, collecting physiological and location data from older adults through controlled outdoor walking routes using wrist-wearable and GPS;training supervised classifiers to differentiate between physiological stress and non-stress signals to environmental conditions of external interaction;and finally, using hotspot analysis to group together individual physiological responses in areas with high-stress interactions with the external environment using GIS. Although the body of literature appears to be still in its early stages, using wearable sensors and a GIS-based approach could be a promising method for spatio-temporally capturing people's direct bodily responses to the environmental stressors, and this offer rooms for potential integration of simulation-ba

关键词： Wearable sensors walkability elderly informal caregiver outdoor environment bodily responses active learning

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Transmuting Wearable sensor Data: From Inertial to Electrical-Like Measurements of Heart Activity 1

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5th international conference on Deep Learning Theory and applications (DeLTA)

作者： Maiorana, Emanuele Roma Tre Univ Rome Italy

ISBN: (数字)9783031666940

ISBN: (纸本)9783031666933;9783031666940

Wearable sensor technology is revolutionizing several research fields, ranging from healthcare to fitness monitoring or biometric recognition, thanks to its many advantages against potential alternatives, such as non-invasiveness and long-term operation capabilities. In more detail, seismocardiography (SCG) and gyrocardiography (GCG) are emerging as useful tools for cardiovascular assessment, relying on inertial measurements of cardiac activity. However, the knowledge and confidence about these signals is still limited in many fields, including the medical one, where the use of electrical measurements, such as those obtained via electrocardiography (ECG), is largely preferred. This paper presents a pioneering study about the possibility of converting SCG and GCG data into ECG-like representations, with the aim of expanding the applicability of inertial wearable sensors to scenarios where their characteristics could provide relevant benefits, yet there could still be the need to exploit knowledge regarding electrical heart activity measurements. In more detail, the effectiveness of recurrent neural networks (RNNs) in performing such task is here investigated. Extensive experimentation on a public dataset demonstrates the feasibility and efficacy of the proposed method in generating signals that significantly resemble the desired ECG data. The capability of the proposed approach in reproducing relevant characteristics of ECG signals in the created data is evaluated considering two potential real-world applications, regarding heart rate estimation and ECG-based biometric recognition.

关键词： Electrocardiography (ECG) Seismocardiography (SCG) Gyrocardiography (GCG) Biometrics Wearable sensors Recurrent Neural Networks (RNNs)

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Simulation of marine wireless sensor network coverage based on improved grey wolf optimization algorithm 6

Simulation of marine wireless sensor network coverage based ...

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2024 6th international conference on Artificial Intelligence technologies and applications, ICAITA 2024

作者： Yang, Zhongqiang Palaoag, Thelma Domingo University of the Cordilleras Baguio2600 Philippines

A new improved algorithm (IGWO) is proposed based on the Grey Wolf Optimization (GWO) algorithm to solve the issue of low overall coverage easily caused by the random deployment of nodes in wireless sensor networks. The IGWO algorithm improves its searchability by adjusting the convergence factor a and changing the updating rules of individual gray wolf positions. IGWO improves the overall search capabilities of the algorithm by converging and adjusting the trend of convergence factors and dynamically adjusts the gray wolf position update strategy by taking the Euclidean distance ratio values of the omega wolf to the alpha wolf, beta wolf, and delta wolf as parameters, further expanding the search capability of the algorithm. Using MATLAB for simulation, we select 20, 30, and 40 sensor nodes respectively, and the coverage of IGWO compared to GWO’s WSN increases by 0.09%, 2.09%, and 1.17%, respectively, proving that the IGWO algorithm can effectively improve the coverage and performance of WSN. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Optimization algorithms

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Integrative Framework for Disaster Surveillance in Wireless sensor Networks 3

Integrative Framework for Disaster Surveillance in Wireless ...

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3rd international conference on Electrical, Electronics, Information and Communication technologies, ICEEICT 2024

作者： Malarkodi, K. Yakkala, Bhaskarrao Revathi, G. Raja, S. Ramesh, K. Dhanalakshmi, Ammal Saveetha University Saveetha School of Engineering Simats Chennai India Sri Chandrasekhendra Saraswathi Viswa Mahavidyalaya Chennai India P.S.V. College of Engineering & Technology Krishnagiri India

ISBN: (纸本)9798350369083

Monitoring disasters is one of WSNs' most important duties., especially in swiftly reporting earthquake data, a pivotal aspect of disaster surveillance. In our proposed model, we focus on leveraging Wireless sensor Networks (WSNs) for preemptive disaster detection. Our discourse delves into the foundational architecture of WSNs and elucidates their potential role in effective disaster management strategies. There are two phases to this plan: setup and steady-state. During the setup phase, a clustering strategy was suggested for heterogeneous networks. Operating in duty cycle mode during steady-state, the proposed MAC utilizes a virtual token ring among ordinary nodes, enabling simultaneous polling of all superior nodes, while alert transmissions employ a low-power listening (LP) and shortened preamble approach during the sleep state, ensuring efficient and timely data delivery. Three different sorts of data requirements can be simultaneously satisfied by the suggested system in disaster-monitoring applications. By constructing a MAC model that is suggested utilizing embedded Markov chains, it was possible to ascertain average upper bound of the frame delay, average cycle time, and average queue length. Through the use of simulations run in a variety of conditions, the clustering technique outperformed the alternatives. © 2024 IEEE.

关键词： Markov processes

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A Novel OPC UA PubSub Protocol Binding Using MQTT for sensor Networks (MQTT-SN) 29

A Novel OPC UA PubSub Protocol Binding Using MQTT for Sensor...

引用

29th IEEE international conference on Emerging technologies and Factory Automation, ETFA 2024

作者： Nast, Michael Raddatz, Hannes Golatowski, Frank Haubelt, Christian Institute of Applied Microelectronics and Computer Engineering University of Rostock Rostock Germany

ISBN: (纸本)9798350361230

In this paper, we present the integration of MQTT for sensor Networks (MQTT-SN) into OPC Unified Architecture (OPC UA) as a novel publish/subscribe (PubSub) protocol binding in order to enhance the industrial communication stack. By leveraging the lightweight MQTT-SN protocol, which is currently not considered in the architecture, we improve OPC UA's capability for high-frequency, low-latency messaging, which is essential for Industrial Internet of Things (IIoT) applications. We discuss related work and describe the design and implementation in detail. Our hybrid approach combines the rich data modeling and security capabilities of OPC UA with the communication efficiency of MQTT-SN, providing a scalable solution for real- time data management in industrial automation systems. © 2024 IEEE.

关键词： Network security

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Attack Detection in IoT using RF and ANN 4

Attack Detection in IoT using RF and ANN

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4th IEEE international conference on Smart Information Systems and technologies, SIST 2024

作者： Adamova, Aigul Zhukabayeva, Tamara Adamov, Nurgalym Department of Computer Engineering Astana IT University Astana Kazakhstan Faculty of Information Technology L.N. Gumilyov Eurasian National University Astana Kazakhstan Astana International University Astana Kazakhstan

ISBN: (纸本)9798350374865

Internet of Things (IoT) devices are the weak link in organizing a Wireless sensor Network. Various Attacks on IoT devices can lead to different complex consequences. Real applications of the IoT generate a large amount of data every second, the confidentiality of which is of very high value. Therefore, detecting attacks in IoT interactions is of paramount interest from both science and industry. Among various attack detection approaches, machine learning methods show great potential due to their early detection ability. The paper presents a methodology for detecting attacks based on two machine learning methods: Random Forest (RF) and Artificial Neural Network (ANN). To conduct the experiment, various data sets were considered, the descriptions of which are given in the work. The experiment was carried out using open data sets obtained from real IoT devices. As a result, RF demonstrated a high accuracy of 98.6%. © 2024 IEEE.

关键词： Adversarial machine learning

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I-Shoe: Smart Insole for Gait Monitoring 12th

I-Shoe: Smart Insole for Gait Monitoring

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12th international conference on Distributed, Ambient and Pervasive Interactions (DAPI)

作者： Aburajouh, Hala Abdulrahman, Eman Al-Zeyara, Nayla Al-Dosari, Wasmiya Al-Sada, Mohammed Halabi, Osama Qatar Univ Dept Comp Sci & Engn Doha Qatar

ISBN: (纸本)9783031600111;9783031600128

Gait analysis is a crucial method for evaluating and treating individuals with walking-related conditions. The process is typically utilized in hospitals or specialized gait labs, often involving tools operated by medical professionals. However, conventional methods have become more time-consuming and costly, leading to decreased accuracy in gait analysis. Wearable sensor technologies have emerged as a solution. This project introduces the i-Shoe, a smart insole equipped with eight force-sensitive resistors (FSR) and a low-power microcontroller to capture gait features. A mobile application displays real-time sensor data and an average heat map, showcasing the most concentrated pressure area in the foot. Machine learning algorithms are applied to identify abnormalities like flatfoot or imbalance. The system has been successfully tested on several individuals and has potential applications in diabetic foot detection, rehabilitation, and monitoring athletes' gait.

关键词： Gait analysis Smart insole Wearable sensor Machine learning

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Classification of Mechanical Failures in Provoked Ignition Engine by Means of ANN and SVM 8th

Classification of Mechanical Failures in Provoked Ignition E...

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8th international conference on Science, Technology and Innovation for Society (CITIS)

作者： Contreras Urgiles, Rafael Wilmer Maldonado Ortega, Jose Rocano, Esteban Chiluisa, Jorge Univ Politecn Salesiana Cuenca Ecuador

ISBN: (纸本)9783031243264;9783031243271

This paper presents the methodology applied to determine the mechanical failures in an internal combustion engine caused by the application of artificial intelligence in the classification of mechanical failures associated with the cancellation of cylinder work, that is to say this methodology is applied on the data obtained from the signal of the KS sensor (Knock sensor) and the CMP sensor (Camshaft Position sensor) during engine operation. To evaluate the data obtained, the acquisition of samples applied to different operating conditions is carried out, after which an attribute matrix is created that allows a selection and reduction of variables with the application of methods based on the Random Forest architecture. Subsequently, an ANN (artificial neural network) and an SVM (support vector machine) was created and trained, from which a classification error value of 0.1267% and 0.0067%, respectively, was obtained.

关键词： Diagnostic Mechanical failures K-sensor CMP-sensor Artificial neural networks Support-vector machines

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