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

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Flexible and Transportable Illumination Control System for Machine Vision applications 10th

Flexible and Transportable Illumination Control System for M...

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International conference on New Technologies, Development and Application - advanced Production Processes and Intelligent systems

作者： Gusic, Muhamed Sokic, Emir Univ Sarajevo Dept Automat Control & Elect Fac Elect Engn Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

During the development of machine vision setups for industrial applications, namely automatic visual inspection systems, the type of required lighting and correct illumination position and intensity are often not known in advance. In order to solve a specific machine vision task, an engineer needs to propose and implement a suitable image processing algorithm and design the accompanying lighting system. Testing different illumination concepts, especially "in the field", using off-the-shelf lighting systems is time consuming. The paper presents a custom-made, cost effective, transportable and flexible system which may be used for testing different illumination techniques and simultaneously control multiple lighting modules. In addition to the hardware part, the developed software used for control the system is presented in the paper. The proposed device usefulness is demonstrated by solving a suitable multi-light digital image processing task.

关键词： machine vision visual inspection illumination control system embedded systems digital image processing

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Design, Fabrication, and Characterisation of a Novel Piezoimpedal Tactile sensor for use in Soft-Prosthetic Devices

Design, Fabrication, and Characterisation of a Novel Piezoim...

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IEEE/ASME International conference on advanced Intelligent Mechatronics (AIM)

作者： Searle, Thomas Sencadas, Vitor Alici, Gursel Univ Wollongong ARC Ctr Excellence Elect Sci Sch Mech Mat Mech & Biomed Engn Appl Mech & Biomed Engn Res AMBER Grp Wollongong NSW 2522 Australia Univ Aveiro CICECO Aveiro Inst Mat Mat & Ceram Engn Dept P-3810193 Aveiro Portugal

ISBN: (纸本)9781665476331

Enabling the robotic ability to sense tactile interactions is a complex and interdisciplinary challenge, as traditional pressure sensors made of hard and rigid materials struggle to replicate the soft and compliant interactions of mammalian somatosensory networks. This study investigates a novel matrixed contact sensor designed for use in soft robotics and biomedical prosthesis applications. The sensor is a coupled piezocapacitive-piezoresistive tactile sensor, optimized for scalability over various mechanical stimuli, including touch, pressure, bend, stretch, and proximity. By modifying the bulk geometry to include dielectric artifacts and integrating electroactive elastomeric composites, the soft and flexible sensor is fully mechanically compliant and conforms to skin behavior. The sensor has a maximum sensitivity of 0.028kPa(-1), a resolution of 1.3%, and a bandwidth of 29Hz. The study characterizes the sensor's performance and identifies its static and dynamic response to aid in developing complex, closed-loop tactile feedback control systems toward realizing the biomimetic implementation of synthetic skin in soft-prosthetic devices.

关键词： Adaptive control systems

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Machine Learning-Based sensor Synchronization for Enhanced Spatial Awareness in Assistive Technologies

Machine Learning-Based Sensor Synchronization for Enhanced S...

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2024 IEEE International conference on Intelligent systems and advanced applications, ICISAA 2024

作者： Patel, Iftekar Kulkarni, Makarand Mehendale, Ninad Somaiya Vidyavihar University K. J. Somaiya College of Engineering Mumbai400077 India

ISBN: (纸本)9798331539948

Enhancing spatial awareness for the visually impaired is crucial for autonomy and mobility. Our research addresses this by proposing a novel approach to sensor data synchronization for assistive technologies, re-framing the challenge as a forecasting task suitable for machine learning solutions. We developed a hard hat assembly equipped with 2D LiDAR, dual 1D LiDARs, and a depth camera to create comprehensive spatial awareness for navigation. By applying various machine learning algorithms to predict 2D LiDAR readings from higher frequency 1D LiDAR data, we aimed to overcome conventional synchronization limitations. Our investigation revealed that while linear models and some non-linear approaches were inadequate, the Generalized Auto-regressive Conditional Heteroskedasticity (GARCH) model showed promise in capturing short-term volatility. Our findings contribute to assistive technologies by introducing a machine learning paradigm for sensor synchronization, potentially improving spatial awareness systems' accuracy and reliability. This system has the potential to significantly enhance navigation for the visually impaired, fostering greater independence and safety. © 2024 IEEE.

关键词： Adversarial machine learning

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Electrohydrodynamic Printing of Conductive Microstrips on Hyperelastic Substrates for Fabrication of Flexible and Stretchable sensors 6

Electrohydrodynamic Printing of Conductive Microstrips on Hy...

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International conference on Flexible and Printable sensors and systems (FLEPS)

作者： Philippin, Nadine Kuehne, Ingo Schrag, Gabriele Heilbronn Univ Appl Sci Kuenzelsau BW Germany Tech Univ Munich Professorship Microsensors & Actuators Munich BY Germany

ISBN: (纸本)9798350383270;9798350383263

Recently, sensors are subjected to a vast transformation process from planar and rigid devices towards flexible or rather stretchable versions. This can be traced back to a continuous development of novel functional materials and the enhancement of various fabrication techniques. Thus, entirely new sensor designs and applications can be realized. In the present paper, electrohydrodynamic (EHD) printing as advanced non-contact printing technology is utilized for patterning of conductive microstrips serving as stretchable sensor elements. As printing medium particle-based silver inks with particle diameters in the range of 50nm and 1 mu m are used. In contrast to the most commonly applied substrate materials for flexible printed sensors, e.g. polydimethylsiloxane (PDMS), hyperelastic and shape-adjustable thermoplastic polyurethane (TPU) with a thickness of 100 mu m is applied within this work. In addition to straight conductive silver lines more complex geometries such as meanders with improved stress-strain characteristics are realized. With respect to the antagonistic material behavior of TPU and the silver inks as well as their processability, EHD printing represents a promising fabrication technique for future stretchable sensors.

关键词： electrohydrodynamic printing hyperelastic sensor material thermoplastic polyurethane

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advanced IoT-Based Wireless sensors for Remote Geotechnical Monitoring and Structural Diagnostics 18

Advanced IoT-Based Wireless Sensors for Remote Geotechnical ...

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18th IFAC conference on Programmable Devices and Embedded systems (PDES)

作者： Pies, Martin Velicka, Jan Hajovsky, Radovan VSB Tech Univ Ostrava Fac Elect Engn & Comp Sci Dept Cybernet & Biomed Engn 17 Listopadu 15 Ostrava Czech Republic

This paper presents an innovative design and implementation of a wireless sensor module using low-power Internet of Things (IoT) technologies for applications in geotechnical engineering and structural diagnostics, with a main focus on monitoring rock formations below the water surface in areas without access to electrical power. Designed for continuous monitoring of linear displacements and other critical parameters in structural engineering, geotechnical engineering and engineering diagnostics, this sensor module is particularly useful in remote locations. Utilizing wireless data transmission and advanced IoT technologies such as LoRa, IQRF and NB-IoT, this system allows for flexible coverage options and efficient remote management. The system allows users to remotely change measurement parameters, the period of messaging and set thresholds for alarm activation. The study highlights the importance of innovative IoT solutions to improve accuracy and efficiency in monitoring geotechnical and civil engineering structures, especially in challenging sub-surface environments, opening new opportunities for predictive maintenance and risk management in these specific applications. Copyright (c) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Multi sensor systems Networks of sensors and actuators Measurement and instrumentation IoT sensor Networks Geotechnical Monitoring Wireless Data Transmission Underwater Rock Formations Remote Energy-independent systems

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BLDC Motor Trapezoidal Regulation Using Hall Effect sensor

BLDC Motor Trapezoidal Regulation Using Hall Effect Sensor

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2024 IEEE International conference on Intelligent systems and advanced applications, ICISAA 2024

作者： Bhatiya, Hansa Patil, Dushyant Makune, Shriram Kadam, Swaraj Mahajan, Vishal Vaidya, Harshal Dr. D. Y. Patil Institute of Technology Department of Electrical Engineering Pimpri Pune India R. C. Patel College of Polytechnic Department of Electrical Engineering India Marathwada Mitramandal's IoT Lohgaon Department of Engineering Science Pune India

ISBN: (纸本)9798331539948

BLDC motors provide excellent performance, durability, and efficiency, making them ideal for a variety of applications. The motor was operated by means of the six-step commutation process of the trapezoidal control approach, which was applied to the exact rotor position data obtained via Hall effect sensors. This approach perfectly times the commutation sequence, reducing torque ripple and improving motor performance. The design, modeling, and experimental findings validated the effectiveness of the proposed control technique, suggesting that it can be used to maximize BLDC motor performance in commercial and industrial applications. © 2024 IEEE.

关键词： Hall effect transducers

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Statement Graphs: Unifying the Graph Data Model Landscape 29th

Statement Graphs: Unifying the Graph Data Model Landscape

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29th International conference on Database systems for advanced applications (DASFAA)

作者： Gelling, Ewout Fletcher, George Schmidt, Michael Eindhoven Univ Technol Eindhoven Netherlands Amazon Web Serv Seattle WA USA

ISBN: (纸本)9789819755745;9789819755752

Graph database users today face a choice between two technology stacks. The Resource Description Framework (RDF), on one side, is a data model that was originally developed by the W3C to exchange interconnected data on the Web. On the other side, Labeled Property Graphs (LPGs) are geared towards efficient graph processing and have strong roots in developer and engineering communities. The two models look at graphs from different abstraction layers, expose - at the surface distinct features, come with different query languages, and are embedded into their own software ecosystems. Typical industry use cases call for applications which must bridge data systems under both stacks, leading to ad hoc and costly solutions. Towards remedying this pain point, we introduce a novel unifying graph data model called Statement Graphs, which combines the traits of RDF and LPG, and achieves interoperability at different levels: it (a) provides the ability to manage RDF and LPG data as a single, interconnected graph, (b) enables read querying over the integrated graph using any RDF or LPG query language, while (c) clearing the way for graph stack independent data exchange mechanisms. As a proof of concept, we present the 1G Playground;an in-memory DBMS built on the concepts of Statement Graphs, which facilitates storage of both RDF and LPG data, and allows for cross-model read querying using SPARQL and Gremlin.

关键词： database systems knowledge graphs graph modeling

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Multi-Modal AI for Enhanced Forest Fire Early Detection: Scalar and Image Fusion

Multi-Modal AI for Enhanced Forest Fire Early Detection: Sca...

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International conference on advanced systems and Emergent Technologies (ICASET)

作者： Azzabi, Tarek Jeridi, Mohamed Hechmi Mejri, Ikbel Ezzedine, Tahar Tunisian Naval Acad Lab LR DN02 19 Menzel Bourguiba 7050 Tunisia Tunisian Naval Acad Menzel Bourguiba 7050 Tunisia Natl Engn Sch Tunis ENIT SYSCOM LR ES21 99 Tunis Tunisia

ISBN: (纸本)9798350384901;9798350384895

Forest fires pose significant threats to both the environment and human safety, underscoring the critical importance of early detection methods. This article introduces a novel approach grounded in artificial intelligence to enhance the early detection of forest fires. The fusion of sensor technology and imagery holds substantial potential for augmenting prediction accuracy. sensors furnish crucial environmental data encompassing factors such as temperature, humidity, and wind speed, all pivotal in the ignition and propagation of forest fires. In contrast, imagery supplies visual evidence of fire or smoke presence, a particularly invaluable asset in densely forested regions where vegetation cover can obscure sensor-derived information. Employing machine learning algorithms proficient in the analysis and interpretation of this composite data, we achieve a heightened level of accuracy in forest fire detection and probability prediction. This methodology undergoes rigorous evaluation using historical forest fire datasets, demonstrating impressive effectiveness in detecting fires. The potential applications extend to the enhancement of early warning systems for forest fires, ultimately mitigating the loss of life and property attributable to these catastrophic events.

关键词： Forest Fires Scalar sensors Artificial intelligence Machine Learning Deep Learning rTPNN CNN Multi-sensor fusion Concentrations Smoke density

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advanced Autonomous Navigation Technologies for UAVs: Challenges and Opportunities 4

Advanced Autonomous Navigation Technologies for UAVs: Challe...

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4th International conference on Innovative Research in Applied Science, Engineering and Technology, IRASET 2024

作者： Senhaji-Mouhaddib, Issam Bouzakri, Samir Lagrat, Ismail Ibn Tofail University Ensa Lab Of Advanced Systems Engineering Kenitra Morocco

ISBN: (纸本)9798350309508

The utilization of Unmanned Aerial Vehicles (UAVs) has revolutionized numerous industries, with navigation being a crucial factor in ensuring their operational success. This literature review examines the subject of UAV navigation, discussing fundamental concepts, GPS-denied challenges, and cutting-edge technologies. The review commences with an explanation of the basic principles of UAV navigation, including the employment of IMUs, GPS, LiDAR, and Stereo Vision systems. A dedicated section then delves into the challenges posed by GPS-denied environments, emphasizing the importance of GPS in navigation and exploring alternative approaches. The subsequent sections investigate advanced navigation technologies, such as INS/IMU, Multi-sensor Fusion, and AI applications. These innovative research areas cover enhancements to sensors, the development of hybrid navigation systems, deep learning for sensor fusion, and other related topics. The conclusion emphasizes the transformative potential of emerging technologies, providing a roadmap for researchers and practitioners. The identified research directions aim to address current limitations and develop next-generation UAV navigation systems capable of precise navigation in complex and challenging environments. © 2024 IEEE.

关键词： Global positioning system

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Leveraging AI-Driven Chatbots for Legal Literacy: advanced Computing and Communication Technologies for Legal Awareness

Leveraging AI-Driven Chatbots for Legal Literacy: Advanced C...

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

作者： Trivedi, Chetan Kumar, Sunil Mohd, Imran Bhalla, Rajiv Ahmad Lone, Naseer Dogra, Disha University Institute of Legal Studies Chandigarh University Punjab India

ISBN: (纸本)9798331517953

In a democratic society, public legal awareness is crucial for empowering citizens with knowledge of their rights and obligations. However, the vast complexity and volume of legal information can make it difficult for non-experts to access and understand their legal standing. This paper explores the development and deployment of AI-driven chatbot systems aimed at enhancing public legal literacy. These systems leverage advanced computing techniques, including natural language processing (NLP) and machine learning (ML) algorithms, to process legal queries and deliver personalized legal information to users in real time. The architecture, scalability, and implementation challenges of deploying these chatbots across diverse communication platforms (e.g., web, mobile) are examined. Additionally, the paper addresses the potential of these systems to bridge the gap in legal knowledge for underserved populations and discusses the importance of real-time communication technologies for ensuring effective system performance. Finally, the paper explores future advancements to further integrate AI and communication technologies for widespread legal literacy. © 2024 IEEE.

关键词： Natural language processing systems

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