A novel low-power distributed Visual Sensor Network (VSN) system is proposed, which performs real-time collaborative barcode localization, tracking, and robust identification. Due to a dynamic triggering mechanism and efficient transmission protocols, communication is organized amongst the nodes themselves rather than being orchestrated by a single sink node, achieving lower congestion and significantly reducing the vulnerability of the overall system. Specifically, early detection of the moving barcode is achieved through a dynamic triggering mechanism. A hierarchical transmission protocol is designed, within which different communication protocols are used, depending on the type of data exchanged among nodes. Real-Time Transport Protocol (RTP) is employed for video communication, while the Transmission Control Protocol (TCP) and Long Range (LoRa) protocol are used for passing messages amongst the nodes in the VSN. Through an extensive experimental evaluation, we demonstrate that the proposed distributed VSN brings substantial advantages in terms of accuracy, power savings, and time complexity compared to an equivalent system performing centralized processing.
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http://dx.doi.org/10.3390/s22041433 | DOI Listing |
Philos Trans A Math Phys Eng Sci
January 2025
Microsystems Group, School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
The increasing demand for processing large volumes of data for machine learning (ML) models has pushed data bandwidth requirements beyond the capability of traditional von Neumann architecture. In-memory computing (IMC) has recently emerged as a promising solution to address this gap by enabling distributed data storage and processing at the micro-architectural level, significantly reducing both latency and energy. In this article, we present In-Memory comPuting architecture based on Y-FlAsh technology for Coalesced Tsetlin machine inference (IMPACT), underpinned on a cutting-edge memory device, Y-Flash, fabricated on a 180 nm complementary metal oxide semiconductor (CMOS) process.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Institute of High Pressure Physics, Polish Academy of Sciences, Warsaw 01-142, Poland.
Ultrasmall micro-light-emitting diodes (μLEDs), sized below 10 μm, are indispensable to create the next-generation augmented and virtual reality (AR/VR) devices. Their high brightness and low power consumption could not only enhance the user experience by providing vivid and lifelike visuals but also extend device longevity. However, a notable challenge emerges: a decrease in efficiency with a reduced size.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Guangxi Key Laboratory of Machine Vision and Intelligent Control, Wuzhou University, Wuzhou 543000, China.
A high-quality optical path alignment is essential for achieving superior image quality in optical biological microscope (OBM) systems. The traditional automatic alignment methods for OBMs rely heavily on complex masker-detection techniques. This paper introduces an innovative, image-sensor-based optical path alignment approach designed for low-power objective (specifically 4×) automatic OBMs.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
College of Physics Science & Technology, School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei University, Baoding, 071002, China.
Hardware system customized toward the demands of graph neural network learning would promote efficiency and strong temporal processing for graph-structured data. However, most amorphous/polycrystalline oxides-based memristors commonly have unstable conductance regulation due to random growth of conductive filaments. And graph neural networks based on robust and epitaxial film memristors can especially improve energy efficiency due to their high endurance and ultra-low power consumption.
View Article and Find Full Text PDFUltrason Sonochem
January 2025
Marwadi University Research Centre, Department of Microbiology, Marwadi University, Rajkot, Gujarat 360003, India.
Escalating global protein demand necessitates the commercialization of protein rich products. Oat is a promising high-quality protein source but it requires structural and functional modifications to diversify its application. The current investigation was focused on the impact of different powers of ultrasonic waves (200, 400, and 600 W) on structural and functional characteristics of oat protein isolates to improve its techno-functional properties.
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