Palm recognition systems play an important role in biometric authentication;however, existing systems frequently have low accuracy and resiliency due to problems such as changing lighting conditions, occlusions, and h...
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Customers now also worry in restricting factors in the Electric Vehicle industry like battery life, charge stations location, power grid capacity, restricted drive range, and slow battery charging. However, there is a...
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The area of continuous learning, which addresses the difficulty of learning and adapting in changing contexts, has attracted much interest lately. Although continual learning approaches have seen significant theoretic...
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In light of the remarkable development of Face Recognition (FR) technology in education, this study focuses on development of a Student Support System (SSS) which includes realtime FR based Attendance tracking, Cours...
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The work in this research is under the area of AUVs, which are specialized unmanned surface vessels with fixed or rotating propellers to implement real-time water quality monitoring systems with AI. The extended proce...
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In this paper, we propose an intelligent edge computing system that supports unmanned aerial vehicles (UAVs) and low-Earth orbit (LEO) satellites for real-time utilization of Internet of Things (IoT) data within the s...
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With the growth of motion imagery, the ability to visually analyze video data and extract key features has advanced significantly. This technology incorporates essential geo-tagging, sensor, and platform orientation d...
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Safety-critical systems are integral to ensuring the reliability and safety of operations in sectors where failures can lead to severe losses. These systems are characterized by their complex and reactive nature, requ...
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Recent advances in Model Predictive Control (MPC) algorithms and methodologies, combined with the surge of computational power of available embedded platforms, allows the use of real-time optimization-based control of...
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ISBN:
(纸本)9781728196817
Recent advances in Model Predictive Control (MPC) algorithms and methodologies, combined with the surge of computational power of available embedded platforms, allows the use of real-time optimization-based control of fast mechatronic systems. This paper presents an implementation of an optimal guidance, navigation and control (GNC) system for the motion control of a small-scale electric prototype of a thrust-vectored rocket. The aim of this prototype is to provide an inexpensive platform to explore GNC algorithms for automatic landing of sounding rockets. The guidance and trajectory tracking are formulated as continuous-time optimal control problems and are solved in real-time on embedded hardware using the PolyMPC library. An Extended Kalman Filter (EKF) is designed to estimate external disturbances and actuators offsets. Finally, indoor and outdoor flight experiments are performed to validate the architecture.
WiFi Channel State Information (CSI) is widely-used in research for human sensing applications, yet its actual deployment in commercial real-timeapplications remains sparse with few examples. Existing demonstrations ...
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ISBN:
(数字)9798350387957
ISBN:
(纸本)9798350387964
WiFi Channel State Information (CSI) is widely-used in research for human sensing applications, yet its actual deployment in commercial real-timeapplications remains sparse with few examples. Existing demonstrations in research literature predominantly rely on specialised deployments of a single sensing apparatus, which cannot efficiently be used in large-scale deployments. Additionally packet loss is common which leads to an over-reliance on interpolation for missing points. Addressing these gaps, this paper presents a low-cost, and scalable solution for CSI-based human sensing, tailored for high performance and consistent operation in residential *** approach leverages ESP32 hardware which is renowned for its high availability and low-cost compared to popular CSI collection solutions. We define a methodology for remotely collecting CSI data from multiple sensors concurrently over WiFi, by employing a single beacon for traffic generation while CSI data is gathered over a separate channel. We further optimize this process using DEFLATE compression on CSI payloads to minimize airtime contention during transmission. This proposed system has been evaluated through a series of experiments designed to assess its viability, scalability, and environmental adaptation capability. Notably, we demonstrate the system’s capability to support 30 sensors sampling CSI data at over 90Hz simultaneously, with additional projected capacity. This validation has been conducted across two distinct residential environments, affirming the adaptability and effectiveness of our approach for high-performance CSI sensing in real-world scenarios.
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