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unmanned/unattended sensors and sensor networks xii

作者： Carapezza, Edward M. Datskos, Panos G. Tsamis, Christos

This PDF file contains the front matter associated with SPIE Proceedings Volume 9986 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing. © 2016 SPIE.

ISBN: (纸本)9781510603769

关键词： sensor networks

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E3-Net: Event-Guided Edge-Enhancement Network for UAV-based Crack Detection

E3-Net: Event-Guided Edge-Enhancement Network for UAV-based ...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Ran Duan Bo Wu Hao Zhou Haobo Zuo Zhengshu He Chenxi Xiao Changhong Fu Department of Land Surveying and Geo-Informatics The Hong Kong Polytechnic University Hong Kong China Department of Computer Science University of Hong Kong Hong Kong China MOE Key Laboratory of Transportation Tunnel Engineering Southwest Jiaotong University Chengdu China School of Information Science and Technology ShanghaiTech University Shanghai China School of Mechanical Engineering Tongji University Shanghai China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Buildings, bridges, and other exteriors of infrastructure are commonly susceptible to damages that may reduce safety and longevity. When left unattended, small cracks can cause catastrophic failures. However, crack inspection is a challenging process that requires significant human effort and can expose inspectors to risks. To address this challenge, the use of unmanned Aerial Vehicles (UAVs) has emerged as an approach to survey areas that are difficult to reach. However, the cracks are small and may blend into background textures, making them difficult to discriminate. Furthermore, the motion of quadrotors can potentially cause motion blur, increasing the difficulty of crack detection. To address these challenges, we propose a neural network designed to detect cracks robustly. Our neural network architecture includes two stages. First, a V2E (Video-to-Event) model transforms the image data into Dynamic Vision sensor (DVS) events. This procedure aims to make the output crack feature identifiable in the presence of motion blur. Then, an edge-enhancement net that combines UNet and non-local block net is designed to augment the crack feature and suppress the background texture concurrently. The background texture suppression is achieved by training on our annotated crack dataset using a triplet loss. Lastly, these proposed cracks can be highlighted by the YOLOv8n-seg network. Experimental results demonstrate that the proposed network can effectively detect small wall cracks in the presence of diverse background patterns.

关键词： Training Surveys Image edge detection Neural networks Transforms Inspection Vision sensors Safety Voltage control Vehicle dynamics

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sensors Cybersecurity

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sensors 2021年第5期21卷 1762-1762页

作者： Gritzalis, Dimitris A. Pantziou, Grammati Roman-Castro, Rodrigo Athens Univ Econ & Business Dept Informat GR-10434 Athens Greece Univ West Attica Dept Informat & Comp Engn Athens 12241 Greece Univ Malaga Dept Comp Sci Malaga 29071 Spain

At present, sensors are increasingly used in all kinds of platforms, manned or unmanned, particularly in view of the emerging Internet of Things (IoT). The quality and capabilities of drones, wearables, driverless cars, sensor-aided shipping and aviation, robots, and any other sensor-based platform or application mainly depend on the sensing technology they use. No single type of sensor can provide solutions to all problems, and most of them are vulnerable to cyberattacks. For example, host-based sensors provide more extensive and accurate information, but this only applies to phenomena that they are manufactured to describe. From their side, network-based sensors provide extensive coverage, but they can be deceived by traffic engineering. Further, they cannot describe encrypted traffic and often can hardly estimate the activity of a host. In addition, because of the wireless- and resource-constrained nature of sensor networks and their possible deployment in harsh environments or unattended areas, they are susceptible to many security threats. Therefore, sensor-based platforms and applications are highly vulnerable to cyberattacks, and many valuable assets are exposed and vulnerable to sensor and sensor network-based cyber threats. As a result, the need for adequate sensor and sensor network infrastructure protection and the development of secure information monitoring systems is increasing. However, due to the communication, computation, and delay constraints of sensor networks and applications, achieving an acceptable level of security has been a difficult issue to solve. Therefore, we need to develop new theories, technologies, and practical solutions so as to protect the network infrastructure and the sensors that are integrated in the platforms of drones, mobile phones, cars, vessels, airplanes, robots, critical infrastructures, etc. From their side, the developers of secure information monitoring systems should take into account that these systems are based o

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Study of UGS Target Recognition Method based on Recurrent Neural Network and Peak Value Region Extraction

Study of UGS Target Recognition Method based on Recurrent Ne...

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IEEE International Conference on unmanned Systems (ICUS)

作者： Wei Zhao Xiong Li Nan Wang Tonghua Xu Department of Information Technology Hunan Police Academy National University of Defense Technology Changsha China College of Intelligence Science and Technology National University of Defense Technology Changsha China

In order to improve the accuracy of unattended Ground sensors (UGS) for human activity recognition, this paper proposes a target recognition method based on Recurrent Neural Network (RNN) and peak value region extraction. The ground seismic signal is obtained from the seismic sensor, and the peak value region of the signal is extracted and trained by Recurrent Neural Network (RNN) to form the target recognition network model. Simulation results show that the proposed approach has an obvious improvement in the accuracy of human target recognition compared with the existing seismic target recognition methods.

关键词： Training Feature extraction sensors Data mining Target recognition Recurrent neural networks Legged locomotion

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Power for sensors - sensors for power 12

Power for sensors - Sensors for power

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Conference on unmanned/unattended sensors and sensor networks xii

作者： Siegel, Mel Carnegie Mellon Univ Sch Comp Sci Inst Robot Pittsburgh PA 15213 USA

ISBN: (数字)9781510603776 s

ISBN: (纸本)9781510603769;9781510603776

As sensors are increasingly deployed in locations removed from mains power and increasingly expected to operate for times that are long compared to battery lifetimes we look to means for "harvesting" or "scavenging" energy from the sensors' operating environments. Whereas many sensors are "parametric" - their interaction with the environment causes a change in one or more of their electrical parameters - many other are true transducers - they perform their sensing function by extracting energy from their environment. These kinds of sensors can thus serve - under suitable operating conditions - both as measuring devices and as power supplies. In this paper we review this background, review the fundamental restrictions on our ability to extract energy from the environment, enumerate and summarize sensing principles that are promising candidates to double as power supplies, and provide several examples that span the range from already off-the-shelf at low cost to in laboratory prototype stage to sufficiently speculative that there might be reasonable doubt regarding whether they can actually work even in principle. Possibilities examined across this spectrum include thermal noise, ambient RF scavenging (briefly), thermoelectricity, piezoelectricity, pyroelectricity, and electrochemistry, especially including electrochemistry facilitated by microorganisms.

关键词： sensing sensors power energy transduction harvesting scavenging noise thermodynamics

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Laser ablation method for production of surface acoustic wave sensors 12

Laser ablation method for production of surface acoustic wav...

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unmanned/unattended sensors and sensor networks xii

作者： Lukyanov, Dmitry Shevchenko, Sergey Kukaev, Alexander Safronov, Daniil Dept. of Laser Measurement and Navigation Systems Saint-Petersburg Electrotechnical University prof. Popova str. 5 St.-Petersburg Russia

ISBN: (数字)9781510603776 s

ISBN: (纸本)9781510603769

Nowadays surface acoustic wave (SAW) sensors are produced using a photolithography method. In case of inertial sensors it suffers several disadvantages, such as difficulty in matching topologies produced on opposite sides of the wafer, expensive in small series production, not allowing further topology correction. In this case a laser ablation method seems promising. Details of a proposed technique are described in the paper along with results of its experimental test and discussion. © 2016 SPIE.

关键词： Laser ablation

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Data Fusion for Target Tracking and Classification with Wireless sensor Network 12

Data Fusion for Target Tracking and Classification with Wire...

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Conference on unmanned/unattended sensors and sensor networks xii

作者： Pannetier, Benjamin Doumerc, Robin Moras, Julian Dezert, Jean Canevet, Loic Off Natl Etud & Rech Aerosp French Aerosp Lab Informat Proc Dept F-91761 Palaiseau France Rocade Est Echangeur Guerry DGA Tech Terrestres F-18021 Bourges France

ISBN: (数字)9781510603776 s

ISBN: (纸本)9781510603769;9781510603776

In this paper, we address the problem of multiple ground target tracking and classification with information obtained from a unattended wireless sensor network. A multiple target tracking (MTT) algorithm, taking into account road and vegetation information, is proposed based on a centralized architecture. One of the key issue is how to adapt classical MTT approach to satisfy embedded processing. Based on track statistics, the classification algorithm uses estimated location, velocity and acceleration to help to classify targets. The algorithms enables tracking human and vehicles driving both on and off road. We integrate road or trail width and vegetation cover, as constraints in target motion models to improve performance of tracking under constraint with classification fusion. Our algorithm also presents different dynamic models, to palliate the maneuvers of targets. The tracking and classification algorithms are integrated into an operational platform (the fusion node). In order to handle realistic ground target tracking scenarios, we use an autonomous smart computer deposited in the surveillance area. After the calibration step of the heterogeneous sensor network, our system is able to handle real data from a wireless ground sensor network. The performance of system is evaluated in a real exercise for intelligence operation ("hunter hunt" scenario).

关键词： unattended wireless sensor network ground target tracking track classification map information classification fusion

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Collaborative Autonomous Sensing with Bayesians in the Loop 12

Collaborative Autonomous Sensing with Bayesians in the Loop

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Conference on unmanned/unattended sensors and sensor networks xii

作者： Ahmed, Nisar Univ Colorado Boulder Aerosp Engn Sci Boulder CO 80309 USA

ISBN: (数字)9781510603776 s

ISBN: (纸本)9781510603769;9781510603776

There is a strong push to develop intelligent unmanned autonomy that complements human reasoning for applications as diverse as wilderness search and rescue, military surveillance, and robotic space exploration. More than just replacing humans for 'dull, dirty and dangerous' work, autonomous agents are expected to cope with a whole host of uncertainties while working closely together with humans in new situations. The robotics revolution firmly established the primacy of Bayesian algorithms for tackling challenging perception, learning and decision-making problems. Since the next frontier of autonomy demands the ability to gather information across stretches of time and space that are beyond the reach of a single autonomous agent, the next generation of Bayesian algorithms must capitalize on opportunities to draw upon the sensing and perception abilities of humans-in/on-the-loop. This work summarizes our recent research toward harnessing 'human sensors' for information gathering tasks. The basic idea behind is to allow human end users (i.e. non-experts in robotics, statistics, machine learning, etc.) to directly 'talk to' the information fusion engine and perceptual processes aboard any autonomous agent. Our approach is grounded in rigorous Bayesian modeling and fusion of flexible semantic information derived from user-friendly interfaces, such as natural language chat and locative hand-drawn sketches. This naturally enables 'plug and play' human sensing with existing probabilistic algorithms for planning and perception, and has been successfully demonstrated with human-robot teams in target localization applications.

关键词： Human-machine systems collaborative sensing Bayesian methods machine learning sensor fusion estimation robotics

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Tunable mechanical monolithic sensors for large band low frequency monitoring and characterization of sites and structures 12

Tunable mechanical monolithic sensors for large band low fre...

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Conference on unmanned/unattended sensors and sensor networks xii

作者： Barone, F. Giordano, G. Acernese, F. Romano, R. Univ Salerno Scuola Med Salernitana Dept Med Surg & Dent Fisciano SA Italy Ist Nazl Fis Nucl Sez Naples Italy Univ Salerno Fisciano SA Italy Univ Salerno Dept Pharm Fisciano SA Italy

ISBN: (数字)9781510603776 s

ISBN: (纸本)9781510603769;9781510603776

Among the different mechanical architectures present in literature, the Watts linkage is one of the most promising ones for the implementation of a new class of mechanical accelerometers (horizontal, vertical and angular). In this paper, we present monolithic implementations of uniaxial and triaxial mechanical seismometers and accelerometers based on the UNISA Folded Pendulum mechanical configuration, optimized for low frequency characterization of sites (including underground sites) and structures as inertial sensor (seismometer). This mechanical architecture allows the design and implementation of very large band monolithic sensors (10(-7)Hz 10(2) Hz), whose sensitivities for the most common applications are defined by the noise introduced by their readouts (e.g. < 10(-12) m/root(Hz) with classical LVDT readouts). These unique features, coupled other relevant properties like scalability, compactness, lightness, high directivity, frequency tunability (typical resonance frequencies in the band 10(-1) Hz 10(2) Hz), very high immunity to environmental noises and low cost make this class of sensors very effective for the implementation of uniaxial (horizontal and/or vertical) and triaxial seismometers and accelerometers for ground, space and underwater applications, including UHV and cryogenics ones. Typical applications of this class of monolithic sensors are in the field of earthquake engineering, seismology, geophysics, civil engineering, characterization of sites (including underground sites), structures (e.g. buildings, bridges, historical monuments), and, in general, in all applications requiring large band-low frequency performances coupled with high sensitivities and compactness.

关键词： Seismometer Accelerometer Monolithic sensor Folded Pendulum Seismic Noise

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Application of wireless multimedia sensor networks for green borderline surveillance 27

Application of wireless multimedia sensor networks for green...

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27th DAAAM International Symposium on Intelligent Manufacturing and Automation, DAAAM 2016

作者： Hulaj, Astrit Shehu, Adrian Bajrami, Xhevahir

ISBN: (纸本)9783902734082

The security of the state borderline is one of the global concerns and main goal of every country. Intensive human involvement in application of conventional systems for border patrol is one of the serious problematic issues. In recent times, border security systems in their composition include high-tech equipment, such as: various unattended sensors, unmanned aerial vehicle, surveillance towers equipped with cameras, etc. However, these systems are faced with unsolvable problems, as regards their application along border areas with difficult terrain and covered with high forests. In this paper we will give ideas for a new system, which can be placed alongside the green borderline with a much cheaper cost and which could offer better results. In the new system for the green borderline surveillance, we propose the application of advanced sensors technology, respectively multimedia wireless sensor nodes (MWSN). This technology will have direct impact on reducing the involvement of human factor (police patrols) to the security of the green borderline and will impact on elimination of false alarms.

关键词： Security systems

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