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Autonomous systems for Security and Defence 2024

作者： Carley, Samantha S. Price, Stanton R. Honigfort, Haley B. Butler, Samantha J. Dabbiru, Lalitha Ball, John E. Fairley, Josh Price, Stephanie U.S. Army Engineer Research and Development Center 3909 Halls Ferry Rd. VicksburgMS39180 United States Center for Advanced Vehicular Systems 200 Research Blvd. StarkvilleMS39759 United States

ISBN: (纸本)9781510681224

Autonomous vehicles typically employ several types of sensors simultaneously, such as LiDAR (Light Detection and Ranging) sensors, visual cameras, and radar to provide information about the surrounding scene while driving. Ideally, coupling multiple sensors would improve a system that only utilizes a single sensing modality for its perception task. For an autonomous system to understand the scene intelligently, it must be equipped with object localization and classification, which is commonly employed using a visual camera. Object detection and classification may also be applied to LiDAR and thermal sensors to further enhance scene awareness of the autonomous system. Herein, we investigate the fusing of information obtained from visual (RGB), LiDAR, and infrared (IR) sensors in order to improve object classification accuracy and heighten scene awareness. In autonomy, there are several levels of fusion that can be employed, such as sensor-level, feature-level, and decision-level;for the scope of this research, we will be exploring the impact of decision-level fusion. Three state-of-the-art object detection and classification models (visual-based, LiDAR-based, and thermal-based) will be employed in parallel, and object predictions will be fused using voting-based (or rules-based) fusion methods. Some questions remain as to the discrepancies that could occur: what can we do to mitigate sensor disagreement? Does the coupling of sensor decisions generally boost confidence or induce confusion? Will different fusion methods provide differing levels of impact to the final solution? Additionally, does this multi-source fusion application transfer well to different scenes? A qualitative and quantitative analysis will be presented for applications of simple and complex fusion methods, and, understanding from past research, we hypothesize that multiple modality perception algorithms boost the final solution by balancing individual sensor strengths and weaknesses. The experiment

关键词： Optical radar

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Experimentally optimized and field validated three-dimensional electromagnetic energy harvester for smart farming applications 18

Experimentally optimized and field validated three-dimension...

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conference on Active and Passive Smart Structures and Integrated systems xVIII

作者： Blazevic, D. Ranta, J. Grunewald, M. Mizukawa, Y. Dizdarevic, J. Niiranen, R. Rasilo, P. Jukan, A. Tampere Univ Elect Engn Unit Korkeakoulunkatu 3 Tampere Finland Tech Univ Carolo Wilhelmina Braunschweig Dept Elect & Comp Engn & Phys Hans Sommer Str 66 Braunschweig Germany Ahlmanin Koulun Saatio Sr Hallilantie 24 Tampere Finland

ISBN: (数字)9781510671997

ISBN: (纸本)9781510671997;9781510671980

Kinetic energy from vibrations emerging from mechanical systems such as machines and vehicles has been thoroughly studied as a power source in the last two decades. Numerous kinetic energy harvesters have been built to convert human locomotion into electrical power but haven't been implemented on a wide commercial scale. On the other hand, energy harvesters for farm animals haven't been studied as much. In this paper, we present a three-dimensional electromagnetic induction based kinetic energy harvester optimized specifically for cattle wearable applications. All the device parameters are obtained with an empirical optimization procedure by considering specific cattle locomotion characteristics. The prototype is 3-D printed with low friction and impact resistant materials. Finally, the device is tested in a real free grazing scenario with live cattle. The kinetic energy harvester performed well and was able to power the load and transmit animal body temperature data over long distances for up to 7 times/h.

关键词： Animal locomotion Energy harvesting Energy scavenging Internet of Things Precision livestock farming Smart farming Wearables Wireless sensor networks

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Waveforms revisited for new-generation ELF-LF systems 32

Waveforms revisited for new-generation ELF-LF systems

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conference on Signal Processing, sensor/Information Fusion, and Target Recognition xxxII

作者： Ahmed, Mohiuddin Mohin HRL Labs LLC 3011 Malibu Canyon Rd Malibu CA 90265 USA

ISBN: (数字)9781510662117

ISBN: (纸本)9781510662100;9781510662117

Radio frequency (RF) communication and radar applications in the low frequency ranges (3 Hz - 300 kHz ELF-LF range and beyond) form an important subclass of RF use cases that have to utilize waveforms that are inherently limited in bandwidth and hence information throughput capability. Thus, the challenge is maximizing the performance of suitable classes of waveforms in terms of throughput, noise and interference suppression, power and practical realizability. In this paper, we summarize the limitations of the traditional approach using sinusoidal waveforms, and briefly describe alternative and modified approaches using OFDM, wavelets, filter bank-based methods and optimized prolate spheroidal waveforms.

关键词： low frequency communications VLF LF waveforms for ELF-LF OFDM filter bank-based waveforms prolate spheroidal waveform

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Shielded fringe field compression sensors for open ocean applications 26

Shielded fringe field compression sensors for open ocean app...

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conference on Electroactive Polymer Actuators and Devices (EAPAD) xxVI

作者： Bruns, Arne Papotti, Gabor Mahmoudinezhad, Masoumeh Hesam Anderson, Iain Auckland Bioengn Inst Biomimet Lab Auckland New Zealand

ISBN: (数字)9781510671973

ISBN: (纸本)9781510671973;9781510671966

Fringe field sensors based on piezo dielectrics offer opportunities in under water sensing as they are solid state, incompressible and robust. Questions remain regarding their susceptibility to noise. Specifically, we refer to anomalous outputs when the sensor is brought in close proximity to or just touching a conductive object. One solution involves isolation through a flexible Faraday cage. We have investigated two approaches for such a Faraday cage. One approach utilizes a conductive fabric while the other is based on a carbon filled dielectric. We compared the performance of both shielding approaches regarding noise suppression and their influence on sensitivity. The anomalous effects upon contact with conductive objects leading to inconsistent measurements were overcome. Furthermore, their response to salinity levels and submersion time were investigated and the influence of design parameters on the performance of the sensor determined in a Design of Experiment study. Varied parameters include overall footprint alongside electrode spacing and width. Performing a full factorial design plan enabled us to quantify the relations between the parameters. This investigation improved signal stability in the piezo dielectric fringe field sensors, making it possible to design a broader range of sensory systems able to withstand the harsh marine environment. The sensor will assist fish robots in their exploration of the 'Silent World'.

关键词： Fringe field shielding piezo dielectric ocean drone

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A 10-Channel, 1.2 μW, Reconfigurable Capacitance-to-Digital Converter for Low-Power, Wearable Healthcare applications

A 10-Channel, 1.2 μW, Reconfigurable Capacitance-to-Digital...

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2023 IEEE Biomedical Circuits and systems conference, BioCAS 2023

作者： Faruqe, Omar Lee, Daehyun Ownby, Natalie B. Calhoun, Benton H. University of Virginia Department of Electrical Engineering CharlottesvilleVA United States

ISBN: (纸本)9798350300260

This paper presents a multi-channel capacitive sensor interface for low-power wearable healthcare applications. The proposed capacitance-to-digital converter (CDC) shares an analog front-end (AFE) and analog-to-digital converter (ADC) among 10 input channels (10 Ch). The architecture allows programmable channel access and duty cycles inactive channels. The CDC avoids operational transconductance amplifiers (OTAs) to improve energy efficiency and features adaptive sensitivity to support the dynamic range of sensors. The CDC measures a change of capacitance (ΔC) of up to 5.34 pF for 1x sensitivity and up to 1.8 pF for 3x sensitivity, chosen to match the target sensors with on-chip offset correction and sensor baseline calibration. The total power consumption is 1.2 μW for 1.6 kHz sampling frequency (fs) when driven by a 32 kHz clock. The energy per conversion is 28.57 pJ at the maximum fs of 5.6 kHz. The proposed architecture achieves a 4.6x reduction in power/channel and an 8.6x reduction in energy per conversion compared to prior works. Implemented in 65 nm CMOS process, the 10-channel CDC occupies 0.251 mm2 of active area (0.0251 mm2/Ch). © 2023 IEEE.

关键词： Analog to Digital Converter (ADC) Baseline Calibration Capacitance-to-Digital Converter (CDC) Leakage Multi-Channel Offset Correction

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A Skin sensor for Epileptic Seizure Detection and Notification applications

A Skin Sensor for Epileptic Seizure Detection and Notificati...

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IEEE SoutheastCon conference

作者： Leon, Luis Contreras, Nicolas Polanco, Fantaysia Fentry, Ebony Sajal, Sayeed Parvez, Imtiaz Florida Int Univ Dept Elect & Comp Engn Miami FL 33174 USA Utah Valley Univ Dept Comp Sci 800 Univ Pkwy Orem UT 84058 USA

ISBN: (纸本)9781665476119

Internet of Things (IoT) allows us to digitize the world around us. Its priority focus has been automatizing actions depending on data collected from all types of sensors. Healthcare has benefited from its development in a phenomenal grade. Previously sensors were attached to cables to central monitoring systems to collect and process the monitored patients' data. These cables restricted the subject's movements and did use to cause grief. These intelligent systems have been evolving in the wireless world and now provide minor mobility issues to patients. The extreme cases allow users to wear such sensors for a prolonged time, permitting continuous monitoring and alerting systems to send data to the cloud. In this paper, we propose a monitoring system based on a low-power Bluetooth communication device that registers immediate changes in heart rate and skin capacitance. These changes can be measured and sent alerts to an app installed on the user's cellular phone. The phone app has the capability of contacting relatives or emergency response.

关键词： Skin capacitance body-centric communication epilepsy GSR sensor arduino SUDEP

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AIoT-driven multi-source sensor emission monitoring and forecasting using multi-source sensor integration with reduced noise series decomposition

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JOURNAL OF CLOUD COMPUTING-ADVANCES systems AND applications 2024年第1期13卷 1-18页

作者： Bhatti, Mughair Aslam Song, Zhiyao Bhatti, Uzair Aslam Syam, M. S. Nanjing Normal Univ Sch Geog Nanjing 210023 Peoples R China Jiangsu Ctr Collaborat Innovat Geog Informat Reso Nanjing 210023 Peoples R China Hainan Univ Sch Informat & Commun Engn Haikou 570100 Peoples R China Shenzhen Univ Guangdong Hong Kong Macao GBA New Generat Intelli Shenzhen 518060 Guangdong Peoples R China

The integration of multi-source sensors based AIoT (Artificial Intelligence of Things) technologies into air quality measurement and forecasting is becoming increasingly critical in the fields of sustainable and smart environmental design, urban development, and pollution control. This study focuses on enhancing the prediction of emission, with a special emphasis on pollutants, utilizing advanced deep learning (DL) techniques. Recurrent neural networks (RNNs) and long short-term memory (LSTM) neural networks have shown promise in predicting air quality trends in time series data. However, challenges persist due to the unpredictability of air quality data and the scarcity of long-term historical data for training. To address these challenges, this study introduces the AIoT-enhanced EEMD-CEEMDAN-GCN model. This innovative approach involves decomposing the input signal using EEMD (Ensemble Empirical Mode Decomposition) and CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) to extract intrinsic mode functions. These functions are then processed through a GCN (Graph Convolutional Network) model, enabling precise prediction of air quality trends. The model's effectiveness is validated using air pollution datasets from four provinces in China, demonstrating its superiority over various deep learning models (GCN, EMD-GCN) and series decomposition models (EEMD-GCN, CEEMDAN-GCN). It achieves higher accuracy and better data fitting, outperforming other models in key metrics such as MAE (Mean Absolute Error), MSE (Mean Squared Error), MAPE (Mean Absolute Percentage Error), and R 2 (Coefficient of Determination). The implementation of this AIoT-enhanced model in air pollution prediction allows decision-makers to more accurately anticipate changes in air quality, particularly concerning carbon emissions. This facilitates more effective planning of mitigation measures, improvement of public health, and optimization of resource allocation. Moreover, the mo

关键词： Multi-source forecasting AIoT sensors CEEMDAN GCN

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A hybrid high speed eye tracking sensor by fusion of video oculography and laser feedback interferometry 5

A hybrid high speed eye tracking sensor by fusion of video o...

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Optical Architectures for Displays and Sensing in Augmented, Virtual, and Mixed Reality (AR, VR, MR) V 2024

作者： Meyer, Johannes Mühlbauer, Michael Corporate Sector Research and Advance Engineering Dpt. of Advanced Technologies and Micro Systems Optical Microsystems Robert Bosch GmbH Renningen Germany

ISBN: (纸本)9781510670860

High-speed eye tracking is a key requirement for upcoming AR and VR devices, as it enables novel applications such as display enhancement through gaze-contingent rendering, saccadic endpoint prediction to minimize system latency, and gaze-based biometric user identification. The update rate of state-of-the-art mobile video oculography sensors is limited by system-level power consumption, which is mainly caused by the exponentially increasing computational power requirements for pupil detection in camera images with respect to the update rate. To overcome this limitation and enable unconstrained high-speed eye tracking with low power consumption, we propose to fuse eye movement velocity data acquired by laser feedback interferometry sensors with camera images acquired at a low sampling rate. We propose a model-based sensor fusion approach that involves a combination of a glint-free, model-based video-oculography approach and high-speed interpolation between successive camera images using velocity information derived from the laser feedback interferometry sensors to achieve an outstanding eye tracking sensor system update rate of 1 kHz. We evaluated the proposed hybrid sensor system in an experimental setup and achieved a gaze accuracy of 1.63°. © 2024 SPIE.

关键词： Eye tracking

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Design of control system for automated semiconductor etching equipment

Design of control system for automated semiconductor etching...

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2024 International conference on Physics, Photonics, and Optical Engineering, ICPPOE 2024

作者： Qian, Jun Hong Kong Baptist University China

ISBN: (数字)9781510689121

ISBN: (纸本)9781510689114

In the semiconductor manufacturing process, the etching process is crucial for the accuracy and performance of the device, but the PID (Proportional Integral Derivative) control method has significant shortcomings in control accuracy, reaction rate, and stability, and cannot meet the increasingly stringent requirements of modern chip manufacturing. To solve this problem, this paper designs a control system for automated semiconductor etching equipment. First, this paper builds a multi-parameter real-time monitoring system based on advanced sensor networks and embedded control units to accurately obtain key data during the etching process. Next, an adaptive control algorithm is designed to adjust the etching parameters through feedback control strategy to ensure the stability and accuracy of the etching process. Finally, an expert system based on fuzzy logic is used to optimize the process control to cope with the nonlinear characteristics in complex environments. The experimental results show that the maximum etching error of the adaptive control system is 4 nm, and the average error is 1.7 nm, while the maximum error of the traditional PID control system is 9 nm and the average error is 5.3 nm. In addition, the adaptive control system has a recovery time of 5 seconds when dealing with process disturbances, while the PID control system needs 8 seconds to recover. Compared with traditional PID control systems, adaptive control systems have shown significant advantages in etching accuracy, system stability, and response speed, successfully solving the problem of process fluctuations in the etching process and improving the consistency and process stability of etching depth. © 2025 SPIE.

关键词： Three term control systems

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sensor Data Integration Using Ontologies for Event Detection 1

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37th International conference on advanced Information Networking and applications, AINA 2023

作者： Amará, Jefferson Ströele, Victor Braga, Regina Bauer, Michael Juiz de Fora Brazil London Canada

ISBN: (数字)9783031290565

ISBN: (纸本)9783031290558

Nowadays, computing applications operate in environments with multiple and heterogeneous data sources, such as data generated from IoT devices. Without contextual information, the information derived from these isolated data sources may cause bias, error, or a lack of correct comprehension. Data integration can help to promote a holistic view of data and support getting the most trustful meaning from the information. This work proposes an architecture in which ontologies help to provide context for data integration. Furthermore, ontologies and complex network concepts enrich context awareness and derive relations among data to identify events of interest. The approach is evaluated in a controlled experiment using real data from hydrological and hydrometric sensors. The results indicate it is possible to detect context and relate events from different data sources to new significant events through ontology and graph network analysis. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Ontology

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