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Deep Learning-Based Strategies for Integrated Autonomous Navigation: A Review

Deep Learning-Based Strategies for Integrated Autonomous Nav...

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Telecommunications conference (ITC-Egypt), International

作者： Alaa Fekry Ahmed M. Kamel Yehia Elhalwagy Ashraf Abosekeen Department of Electrical and Computer Engineering Military Technical College Cairo Egypt Department of Mechatronics Systems Engineering October University for Modern Sciences and Arts Giza Egypt

ISBN: (数字)9798350351408

ISBN: (纸本)9798350351415

Multi-sensor integrated navigation/positioning systems (MSINPS) play a crucial role in achieving precise positioning and navigation in challenging environments. By combining data from various sensors such as Global Navigation Satellite System (GNSS), Inertial Measurement Units (IMUs), cameras, and Light Detection and Ranging (LiDar), MSINPS enhance accuracy and robustness, ensuring uninterrupted operation even in the event of sensor malfunction. This paper explores autonomous vehicle guidance for safe and efficient navigation, focusing on two paths of data fusion: sensor-based fusion and learning-based fusion. The effectiveness of MSINPS hinges on meticulous sensor selection and optimization to meet the requirements of autonomous navigation applications. Addressing noise, biases, and inconsistencies through data pre-processing is essential for robust data fusion. advanced fusion algorithms leveraging machine learning and deep learning techniques exhibit superior accuracy and adaptability. Furthermore, integrating MSINPS with artificial intelligence (AI) opens new avenues for navigation and positioning enhancement. This integration can lead to improvements in sensor technology and solution outcomes. Striking a balance between computational complexity and available resources promotes efficient operation while implementing fault tolerance strategies ensures system robustness across diverse environments.

关键词： Global navigation satellite system Laser radar Noise Radio navigation Predictive models sensor systems Robustness

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Real-Time Indoor Target Tracking Using IoT and Wireless sensor Networks

Real-Time Indoor Target Tracking Using IoT and Wireless Sens...

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Sentiment Analysis and Deep Learning (ICSADL), International conference on

作者： Sachin R. Katakwar Kapil K. Jajulwar Surekha Tadas M. Tech Communication Engineering G H Raisoni College of Engineering Nagpur India Department of Electronics and Telecommunication Engineering G H Raisoni College of Engineering Nagpur India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

Indoor target tracking presents significant challenges across various fields such as security surveillance, industrial automation, and healthcare. This research paper outlines the design and implementation of a reliable direction monitoring system aimed at achieving accurate indoor target tracking using IoT and wireless sensor networks. By utilizing advanced sensor technologies and sophisticated data processing algorithms, the proposed system enables real-time monitoring and precise localization of targets within indoor spaces. The combination of IoT devices and wireless sensor networks facilitates effective data collection, analysis, and visualization, thereby improving the overall performance of the monitoring system. The results indicate that the developed system is effective in accurately tracking and localizing targets, fulfilling the essential requirement for efficient indoor direction monitoring solutions. The paper concludes with a discussion on the practical implications and potential applications of this system, emphasizing its importance in enhancing indoor target localization across diverse sectors.

关键词： Location awareness Wireless sensor networks Sentiment analysis Target tracking Accuracy Surveillance Real-time systems Safety Internet of Things Security

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AI-Driven Energy Management System for Industrial and Commercial Facilities to Enhance Energy Optimization

AI-Driven Energy Management System for Industrial and Commer...

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Intelligent systems and advanced applications (ICISAA), International conference on

作者： M. Pushpavalli Mohd Noman Shubham Kumar Satya Praksh W.Abitha Memala C. Bhuvaneshwari P. Sivagami Sathyabama Institute of Science and Technology Chennai India

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

This Paper presents a comprehensive review of the literature on An AI-powered system that can help commercial facilities cut down on energy consumption. With increasing pressure to enhance the consumption of energy efficiency and reduce costs, businesses are turning to advanced technologies such as artificial intelligence (AI) to optimize energy usage. The abstract begins by highlighting the importance of energy management in industrial and commercial sectors, emphasizing its impact on cost efficiency, environmental sustainability, and operational performance. It then provides an overview of key studies and findings in the field, including research on AI techniques inclusive of optimization algorithms, machine learning, and deep learning, applied to energy management.. The abstract discusses the potential benefits of AI-powered energy management systems, including cost savings, environmental impact reduction, and operational efficiency improvement. It also addresses challenges and future directions for research and development in this area. Overall, the abstract emphasizes the significance of AI-powered energy management systems in achieving sustainable energy solutions for industrial and commercial facilities. At its core, an AI-powered energy management system leverages advanced algorithms to examine vast amount of data collected from the facility’s operational systems, meters, and sensor. Through predictive analytics and real-time monitoring, the system can forecast energy demand, identify inefficiencies, and dynamically adjust energy usage to optimize performance. The ability of these systems to adjust and learn from past data is a major benefit as it enables ongoing optimization and development over time. By integrating with existing infrastructure and control systems, AI-powered energy management systems provide actionable insights and recommendations to facility managers, enabling informed decision-making and proactive energy management strategies.

关键词： Energy consumption Renewable energy sources Costs Green products Prediction algorithms Real-time systems Energy management systems Artificial intelligence Predictive analytics Optimization

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A Prototype of an Arduino-Based Home Automation System

A Prototype of an Arduino-Based Home Automation System

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International conference on advanced systems and Electric Technologies (IC_ASET)

作者： Yamna Ghoul Naoufel Zitouni Assaad Jmal LR11ES20 Analysis Conception and Control of Systems Laboratory University of Tunis El Manar National Engineering School of Tunis Le Belvédère Tunis Tunisia Faculty of Sciences of Tunis Loboratory of Applications of Energy Efficiency and Renewable Energies UR-LAPER Tunis El Manar University Tunis Tunisia Electrical Engineering Department Control and energy management laboratory (CEM lab) - BP 1173 Sfax University Engineering National School Sfax Tunisia

ISBN: (数字)9798350384895

ISBN: (纸本)9798350384901

This paper explores the realm of home automation, focusing on the development and implementation of a sophisticated system leveraging Internet of Things (IoT) technology. The core of the proposed system revolves around the Arduino Nano board, showcasing its adaptability and versatility. A DHT11 sensor is utilized to actively collect current information on temperature and humidity, and a MQ2 sensor is deployed to monitor kitchen gas leaks with an Arduino microcontroller processing this data. The continuously refreshed data is subsequently sent to an Android mobile app through the Zigbee protocol. The home automation system presented in this paper boasts a unique combination of essential features, including real-time functionality, cost-effectiveness, flexibility, upgradability, and reconfiguration capabilities. This research contributes to the expanding landscape of home automation by providing an innovative solution that addresses key aspects of modern living.

关键词： Temperature sensors Temperature measurement Temperature distribution Home automation Microcontrollers Zigbee Smart homes

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Energy Efficient Workflow Scheduling Algorithm for Latency-Sensitive applications using Cloud-Fog Collaboration

Energy Efficient Workflow Scheduling Algorithm for Latency-S...

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International Symposium on advanced Networks and Telecommunication systems (ANTS)

作者： Prashant Shukla Sudhakar Pandey Department of Information Technology National Institute of Technology Raipur Chhattisgarh India

The objectives of most studies are aimed at employing fog computing (FC) as an effective support to cloud computing (CC) in order to monitor sensor data and their associated necessities via the rapid advancements in Internet of Things (IoT). FC is completely dedicated to IoT sensor systems and delivers CC based computing, networking, and storage services. The cloud-Fog Collaboration (CFC) Environment will be more suitable for real-time IoT data sensing and workflow applications where fast and reliable internet connectivity is available. Workflow Scheduling means efficiently assigning the interdependent tasks to available computing resources. The workflow scheduling techniques play a significant role in minimizing the latency in Heterogeneous Computing systems (HCS). In this paper, we present a novel Hybrid-metaheuristics Multi-objective based Workflow Scheduling Algorithm (HMWSA) by combining Harmony Search (HS) and Genetic Algorithm (GA) for optimizing workflow scheduling in heterogeneous CFC. The proposed minimization objective function takes into account goals like makespan, energy usage, and cost. To preserve the precedence relationship among tasks, a topologically sorted execution sequence is constructed. Extensive testing results show that our proposed approach yields substantially better cost-makespan trade-offs while significantly reducing energy consumption than other existing algorithms.

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Design and simulation analysis of fiber optic current sensor using orbital angular momentum beam 11

Design and simulation analysis of fiber optic current sensor...

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conference on advanced sensor systems and applications XI

作者： Zhao, Yuxin Wang, Guochen Zhang, Boya Yu, Fei Wang, Zhuo Harbin Inst Technol Instrumentat Sci & Engn Harbin 150000 Peoples R China Mil Off Rocket Armaments Dept Harbin Dist Harbin 150000 Peoples R China

ISBN: (数字)9781510646520

ISBN: (纸本)9781510646520;9781510646513

A fiber optic current sensor utilizing orbital angular momentum (OAM) beam is proposed in this paper. The superposition principle of composite OAM beam is deduced, and the current sensing process is derived by Jones matrix. The current is measured by detecting the rotation angle of petal-like patterns formed after the composite OAM beam through the polarizer. The reflective structure of the sensor doubles the rotation angle, which improves the measuring sensitivity and the reciprocity of the system. Through simulation analysis, we verified that the rotation angle changes linearly with the increase of current, and the sensitivity of the proposed sensor is 0.1254 degrees/A. Finally, on this basis, the angle recognition method is optimized, and the final measurement error is less than +/- 0.2% in the range of 50A-1500A.

关键词： Faraday effect orbital angular momentum current measurement petal-like pattern topological charge

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Evaluation of the potential of high index Chalcogenide lenses for automotive application 7

Evaluation of the potential of high index Chalcogenide lense...

引用

conference on advanced Optics for Imaging applications - UV through LWIR VII

作者： Druart, Guillaume Reux, Valentin Calvez, Laurent Zhang, Xiang-Hua De La Barriere, Florence Volatier, Jean-Baptiste Tartas, Elodie Proux, Raphael Off Natl Etud & Rech Aerosp Chemin Huniere F-91761 Palaiseau France Univ Rennes CNRS ISCR Inst Sci Chim Rennes UMR 6226 F-3500 Rennes France LYNRED Route Valence F-38113 Veurey Voroise France UMICORE ZA Boulais F-35690 Acigne France

ISBN: (纸本)9781510650831;9781510650824

Infrared cameras could serve automotive applications by delivering breakthrough perception systems for both in-cabin passengers monitoring and car surrounding. However, low-cost and high-throughput manufacturing methods are essential to sustain the growth in thermal imaging markets for automotive applications, and for other close-to-consumer applications, which have a fast growth potential. With the reduction of the pixel pitch of microbolometer detectors, their cost has decreased considerably and now the optical part represents a significant part of the system cost. Fast low cost infrared lenses suitable for microbolometers are already sold by companies like Umicore, Lightpath, FLIR. Chalcogenide glasses are widely used as materials for optics because they have many cost advantages, especially due to the possibility of mass molding the optics. However, with the reduction of the pixel pitch, it is more and more difficult to design high performance lenses with a limited number of optics. The possibility of molding the optics allows us to use many highly aspherical surfaces at affordable costs. However, Chalcogenide glasses have usually a lower refractive index than other more expensive infrared materials such as Germanium. Indeed, high refractive index materials are known to be effective in attenuating the amplitude of many geometric aberrations. In this presentation, we evaluate the interest of high index Chalcogenide lenses, especially TGG and TGS, to design optical systems meeting the needs of the automobile with a limited number of optics. TGG glass has an index of refraction of 3.396 at a wavelength of 10 mu m, i.e. its index of refraction is close to the Silicon one and was initially studied for space applications. TGS has a lower index of refraction (3.12@10 mu m) but can be used in a cost effective manufacturing process by using flash spark plasma sintering (SPS) on raw powder. Demonstrators with TGG glass have been made and their performance evaluated.

关键词： Infrared Microbolometers Chalcogenide Automotive Application Curved sensor

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

Electrohydrodynamic Printing of Conductive Microstrips on Hy...

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

作者： Nadine Philippin Ingo Kuehne Gabriele Schrag Heilbronn University of Applied Sciences Kuenzelsau BW Germany Technical University of Munich Professorship of Microsensors and Actuators Munich BY Germany

ISBN: (数字)9798350383263

ISBN: (纸本)9798350383270

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 1μm 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 100μm 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： Printing Fabrication Silver Ink Thermal sensors sensor phenomena and characterization sensor systems

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Simultaneous measurement of refractive index and temperature based on bent core-offset in-line fiber Mach-Zehnder interferometer 11

Simultaneous measurement of refractive index and temperature...

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conference on advanced sensor systems and applications XI

作者： Wu, Bingcheng Bao, Haiyang Zhou, Yanfei Liu, Yuan Zheng, Jie Jilin Univ Coll Elect Sci & Engn State Key Lab Integrated Optoelect Changchun 130012 Peoples R China

ISBN: (数字)9781510646520

ISBN: (纸本)9781510646520;9781510646513

A bent core-offset in-line fiber Mach-Zehnder interferometer (MZIs) is proposed for refractive index (RI) sensing. After simply bending, not only the RI sensitivity but also the temperature sensitivity can be enhanced as the bending radius decreases. To solve the cross-sensitivity problem, a simultaneous measurement of RI and temperature was carried out. When the bending radius is 35.64 mm, the highest RI sensitivity of -44.55 nm/RIU for the RI range from 1.333 to 1.373, and the highest temperature sensitivity of 0.0799 nm/degrees C for the temperature range from 25 degrees C to 60 degrees C were measured simultaneously.

关键词： Fiber optic sensor Mach-Zehnder interferometer temperature refractive index bent fiber core-offset

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A Simulation Platform for Intelligent UAV Cybersecurity and Reliability Analysis

A Simulation Platform for Intelligent UAV Cybersecurity and ...

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International conference on Unmanned Aircraft systems (ICUAS)

作者： Boyin Yang Yanyan Li Ryan Callaghan Houbing Song Jiawei Yuan Department of CIS University of Massachusetts Dartmouth Department of CSIS California State University San Marcos Department of Information Systems University of Maryland Baltimore

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Unmanned aerial vehicles (UAVs) are increasingly adopted in various applications due to their high mobility and advanced sensing capabilities. However, they also face significant security threats and reliability concerns arising from external adversarial attacks and internal system failures. AI and machine learning techniques have shown promise in detecting security threats and anomalies in UAVs, but their effectiveness heavily depends on high-quality UAV security datasets for training. In this paper, we present an open-source simulation platform designed to model diverse UAV security scenarios. Our platform offers flexible customization of attacking effects on major UAV components, including onboard sensors, communication systems, vision modules, and flight control. Additionally, it provides rapid generation and collection of UAV system data under adversarial conditions, facilitating intelligent cybersecurity and reliability analysis. Our experiments successfully simulated over 30 attacking effects toward UAVs, demonstrating our platform's capability to support extensive UAV security research.

关键词： Training Streaming media sensor phenomena and characterization Autonomous aerial vehicles Reliability engineering sensor systems Security Computer security Intelligent sensors Aerospace control

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