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

共 9453 条记录，以下是1361-1370 订阅

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Error Analysis on the Thermal Emissive Band Calibration for the MERSI 1

Error Analysis on the Thermal Emissive Band Calibration for ...

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1st international conference on Digitalization and Management Innovation, DMI 2022

作者： Huang, Yue Gao, Peng Yang, Zhenlin Qingdao University of Science and Technology College of Mathematical and Physical Sciences Shandong Advanced Optoelectronic Materials and Technologies Engineering Laboratory Qingdao China

ISBN: (纸本)9781643683782

The remote sensor mounted on the Fengyun-3C (FY-3C) will decay naturally during the operation, causing a decrease in the accuracy of the satellite data. Therefore, an effective monitoring method must be adopted to study the performance changes of the instrument. The theoretical expressions of the absolute and relative errors for the earth field of view (FOV) radiance together with its equivalent brightness temperature are given by analyzing the response value offsets of the earth FOV along with the blackbody (BB) pixel. In order to further describe the influences of different parameters on the absolute and relative errors for the FOV radiance and equivalent brightness temperature, the computer simulations are performed, and the absolute errors for the FOV radiance and equivalent brightness temperature caused the response value offset of the BB pixel firstly decrease and then increase with the increasing of the earth FOV response value. The absolute and relative errors for the FOV radiance caused the response value offset of the earth FOV firstly decrease and then increase, and the absolute error for the equivalent brightness temperature increases while its relative error decreases with the increasing of the response value of the earth FOV. This research provides an important theoretical guidance for improving the on-orbit performance of the FY-3C/ MERSI. © 2023 The authors and IOS Press.

关键词： Pixels

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The TinyOS operating system for wireless sensor networks with a hybrid scheduler

The TinyOS operating system for wireless sensor networks wit...

引用

Network, Multimedia and Information Technology (NMITCON) international conference on

作者： Anita Patil R M Jagadish Sheetal Janthakal Dept. of CSE Ballari Institute of Technology and Management Bellary India Dept. of CSE(Data Science) Ballari Institute of Technology and Management Bellary India

ISBN: (数字)9798350372892

ISBN: (纸本)9798350372908

WSN is the basis for various applications of varying requirements including evergreen technologies like IoT. The architecture of WSN faces many challenges like numerous tiny-sized nodes with low power, wireless communication in particular radio range, being exposed to drastically changing surrounding nature, dynamically changing network size, etc. Thus, WSN needs the support of hardware, software, and operating systems installed in it. At present, there are many operating systems available such as TinyOS, Free-RTOS, RIOT, Contiki, etc. The same set of OS is used by IoT also. Among these TinyOS is the widely used, highly documented, popular, and most suitable OS for low-power devices. The only drawback of TinyOS is the availability of a single scheduler that works in FCFS (First Come First Serve) order which can’t support real-time applications. This research proposes a new hybrid scheduler that provides both FCFS and priority schedulers. Schedulers’ performance analysis is done by taking the scheduling criteria AWT (Average Waiting Time), and ATT (Average Turnaround Time).

关键词： Wireless communication Wireless sensor networks Scheduling algorithms Operating systems Multimedia systems Real-time systems Software Performance analysis Internet of Things Standards

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Boxly: Design and Architecture of a Smart Physical Therapy Clinic for People Having Mobility Disability Using Metaverse, AI, and IoT technologies in Saudi Arabia

Boxly: Design and Architecture of a Smart Physical Therapy C...

引用

Information Technology, Electronics and Intelligent Communication Systems (ICITEICS), IEEE international conference on

作者： Rayhanah Jassim Aldolaim Hina Gull Sardar Zafar Iqbal Department of Computer Information Systems College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia

ISBN: (数字)9798350382693

ISBN: (纸本)9798350382709

People with mobility limitations and impairments frequently receive repetitive remedial physiotherapy sessions to reduce functional deficits in the afflicted area. Even though therapy processes can enhance functional results and reduce the likelihood of long-term disability, patients frequently fail to fully participate in physical therapies due to procedural pain. In recent years, emerging technologies such as artificial intelligence have played a pivotal role in health care, particularly in the treatment of patients with physical limitations. Furthermore, leveraging the metaverse and the Internet of Things (IoT) provides value to therapies such as physical therapy by improving the environment while saving effort and time. In this paper, we propose a new system for physical therapy clinics in Saudi Arabia. It applies modern technologies such as metaverse, AI, and IoT to overcome the barriers that therapists and patients face during treatment, like inaccurate measurements, long periods of rehabilitation, and ongoing pain and feelings of fear.

关键词： Video games Metaverse Pain Medical treatment Position measurement sensor systems and applications Internet of Things

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Integration of Generative AI for Intelligent Diagnostic of Vehicles

Integration of Generative AI for Intelligent Diagnostic of V...

引用

National conference with international Participation (TELECOM)

作者： Vladimir Ranchev Rumen Jordanov Rosen Miletiev Faculty of Electronic Engineering and Technology (FEET) Technical University of Sofia Sofia Bulgaria Faculty of Telecommunications Technical University of Sofia Sofia Bulgaria

ISBN: (数字)9798350355000

ISBN: (纸本)9798350355017

The latest update on Generative AI, especially the OpenAI platform, confirms they are no longer single-domain proficiency. It already has been adopted by a variety of applications, emphasizing speech, audio, vision, and multimodal interactions. GPT family of large language models (LLM) is evolving where GPT4o is a few times faster, way more intelligent, and at the same time much cheaper as a service compared to the previous version. Additional services such as “AI Assistant” make it possible to be utilized with fewer resources available in the embedded systems. The advancement of semiconductor technology and microelectronics in the form of Wireless connected SoC in small sizes opens many fields for various IoT (Internet of Things) applications. The proposed solution in this paper will present a system that combines those two technologies in the form of a standalone embedded connected device, that can perform autonomously diagnostic of vehicle by identifying and prompting the owner or driver for troubles in the vehicle and efficiently suggesting for corrective actions. The results show how comprehensive troubleshooting of logged errors is with a standalone embedded system by the support only of GPT AI Assistant.

关键词： Wireless communication Performance evaluation Wireless sensor networks Embedded systems Generative AI sensor systems Telecommunications Internet of Things Object recognition Vehicles

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Opportunistic RL-based WiFi Access for Aerial sensor Nodes in Smart City applications

Opportunistic RL-based WiFi Access for Aerial Sensor Nodes i...

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international conference on Smart Communications and Networking (SmartNets)

作者： Mehmet Ariman Lal Verda Cakir Mehmet Özdem Berk Canberk Department of Computer Engineering Istanbul Technical University Istanbul Turkey Türk Telekom Turkey School of Computing Engineering and The Build Environment Edinburgh Napier University UK

Unmanned air vehicles are becoming widespread, driven by improved wireless technologies. However, the WiFi technology used for communication has a highly crowded and unevenly distributed channel occupancy in its spectrum. To overcome this, WiFi resources need to be utilized efficiently. Therefore, this paper proposes the Opportunistic Reinforcement Learning-based WiFi Access scheme, which exploits intermittent channel occupancy to solve the NP-hard channel assignment problem. As a result, the proposed model has improved the accurate channel selection on the UAVs by 9%, performing 91% accuracy, compared to the trivial channel scoring-based selection algorithms.

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Hospital Bed Vacancy Detection using Depthwise Separable CNN

Hospital Bed Vacancy Detection using Depthwise Separable CNN

引用

Advanced Computing technologies (ICoACT), international conference on

作者： R Balaji V Deepan S Faiz J Mythili Satyanarayana Murthy Polisetty Computer Science and Engineering K. S. Rangasamy College of Technology Tiruchengode India Bank of America United States

ISBN: (数字)9798331509859

ISBN: (纸本)9798331509866

The rising demand for real-time hospital bed man-agement in healthcare institutions requires creative solutions to improve patient care and resource allocation. This research introduces an IoT-enabled system for detecting hospital bed vacancies utilising a Depthwise Separable Convolutional Neural Network (DSCNN). The proposed system utilises IoT sensors to perpetually monitor bed occupancy, guaranteeing precise and prompt updates to medical personnel. The DSCNN is utilised to diminish computing complexity while preserving high detection accuracy, attaining a notable accuracy of 92.4%. The model's performance is assessed in comparison to traditional CNNs, revealing notable enhancements in both speed and accuracy, with accelerated convergence times enabled by the Adam optimiser. The system guarantees minimal latency in hospital bed detection, rendering it suitable for real-time applications on resource-limited devices. This system provides a scalable and effective method for optimising hospital resource management, especially during high demand or emergencies.

关键词： Accuracy Hospitals Rendering (computer graphics) Real-time systems sensor systems sensors Internet of Things Convolutional neural networks Resource management Personnel

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Increasing cyclists safety using intelligent Bicycle Light Based On Artificial Intelligence

Increasing cyclists safety using intelligent Bicycle Light B...

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international conference on Emerging eLearning technologies and applications (ICETA)

作者： Adam Tomčala Rastislav Bencel Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Bratislava Slovakia

Nowadays, there is a lot of effort to increase safety on roads. The main focus of research is on vehicles and their associated functionality. This paper focuses on increasing safety for other cyclist road transport participants. The research is focused on intelligent light for which propose a solution based on a connection between the mobile device and light device. The solution is aimed at brake light and turn signals. We use data gathered from motion sensors to achieve a simple device that can only be mounted on a bicycle and provide lighting functionality. The data was evaluated by artificial intelligence, namely LSTM (Long Short-Term Memory). The model was trained in the prototype phase, where labeled braking data was created. For labeling data hall sensor was used located on the bicycle brake. Additionally, the solution introduces a turn signal light controlled by voice. Through the utilization of an offline voice recognition library on a mobile phone, the directional lights are governed by verbal commands. This paper describes the hardware, communication, and software parts required to build the intelligent light. Experimental analysis has been conducted to collect data in different situations that occur while cycling, such as braking with different intensities or braking when the bicycle is tilted differently. During the testing phase, we evaluate the effectiveness of the trained LSTM model in detecting bicycle braking during the real ride.

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Measurements of the Safety Function Response Time on a Private 5G and IO-Link Wireless Testbed

Measurements of the Safety Function Response Time on a Priva...

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international conference on Emerging technologies and Factory Automation (ETFA)

作者： Henry Beuster Kevin Tebbe Thomas Robert Doebbert Gerd Scholl Electrical Measurement Engineering Helmut-Schmidt- University Hamburg Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

In the past few years, there has been a growing sig-nificance of interactions between human workers and automated systems throughout the factory floor. Wherever static or mobile robots, such as automated guided vehicles, operate autonomously, a protected environment for personnel and machines must be provided by, e.g., safe, deterministic and low-latency technologies. Another trend in this area is the increased use of wireless communication, offering a high flexibility, modularity, and reduced installation and maintenance efforts. This work presents a testbed implementation that integrates a wireless framework, employing IO-Link Wireless (IOLW) and a private 5G cellular network, to orchestrate a complete example process from sensors and actuators up into the edge, represented by a programmable logic controller (PLC). Latency assessments identify the system's cycle time as well as opportunities for improvement. A worst-case estimation shows the attainable safety function response time for practical applications in the context of functional safety.

关键词： Wireless communication Wireless sensor networks Remotely guided vehicles 5G mobile communication Programmable logic devices Time measurement Production facilities Safety sensors Time factors

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Semi-Supervised Anomaly Detection in the TinyML Domain Through Multi-Target Few-Shot Domain Adaptation

Semi-Supervised Anomaly Detection in the TinyML Domain Throu...

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international conference on Emerging technologies and Factory Automation (ETFA)

作者： Johannes Kühnel Timo Eißmann Christian Wiede Dorothea Schwung Anton Grabmaier Fraunhofer IMS Duisburg Germany Artificial Intelligence and Data Science in Automation Hochschule Düsseldorf - University of Applied Sciences Düsseldorf Germany Department of Electronic Circuits and Systems University of Duisburg-Essen Duisburg Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

Tiny ML, defined by its ability to integrate AI into the smallest devices, unlocks the potential for always-on AI solutions at the edge. This capability is essential in predictive maintenance, enabling smart sensors within the Industrial In-ternet of Things (1IoT). In factory automation, the ability to detect anomalies and adapt those anomaly detection models to varying operating conditions is crucial for the efficiency and longevity of machinery. However, the challenge of semi-supervised anomaly detection with domain adaptation across diverse working conditions has not been sufficiently addressed in TinyML. This paper presents Shared Encoder Domain Adaptation (SEDA) to overcome these limitations. SEDA is a multi-target domain adaptation method for anomaly detection tailored to TinyML applications. Our approach facilitates the transfer of knowledge from existing domains to new ones, ensuring reliable anomaly detection in all domains with minimal data under new operational conditions. This is particularly relevant for IloT applications, where sensors must perform condition monitoring in a self-learning manner. The effectiveness of our method is evaluated through an extensive parameter study on the Toy-ADMOS 2 data set and compared to various baseline methods. The results show an improvement of up to 0.212 on the Area Under the Receiver Operating Characteristic Curve (ROC-AUC) score. It demonstrates that our method significantly enhances performance in multi-target domain adaptation. Importantly, it does this while remaining efficient for resource-constrained systems. This method has the potential to enable self-learning sensor systems with adaptation strategies to different working conditions while requiring only a few data points from these new domains.

关键词： Employee welfare Training Tiny machine learning Training data sensor phenomena and characterization sensor systems Artificial intelligence Anomaly detection Manufacturing automation Signal to noise ratio

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

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

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IEEE international Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and applications

作者： Sergiy Yakovlev Adam Wojciechowski Dmytro Podzeha Oleg Illiashenko Iryna Yakovleva National Aerospace University “KhAI” Kharkiv Ukraine Lodz University of Technology Lodz Poland Software Engineering & Dependable Computing Laboratory Institute of Information Science and Technologies “Alessandro Faedo”—ISTI CNR Pisa Italy National University of Urban Economy in Kharkiv Kharkiv Ukraine

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.

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