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ieee Conference on Virtual reality and 3D User Interfaces (VR)

作者： Jin, Tao Dasari, Mallesham Smith, Connor Apicharttrisorn, Kittipat Seshan, Srinivasan Rowe, Anthony Carnegie Mellon Univ Pittsburgh PA 15213 USA Northeastern Univ Boston MA 02115 USA NVIDIA Santa Clara CA USA Nokia Bell Labs Murray Hill NJ USA Carnegie Mellon Univ Bosch Res Pittsburgh PA 15213 USA

ISBN: (纸本)9798350374025;9798350374032

3D video enables a remote viewer to observe a 3D scene from any angle or location. However, current 3D capture solutions incur high latency, consume significant bandwidth, and scale poorly with the number of depth sensors and size of scenes. These problems are largely caused by the current monolithic approach to 3D capture and the use of inefficient data representations for streaming. This paper introduces MeshReduce, a distributed scene capture, stream, and render system that advocates for the use of textured mesh data representation early in the 3D video capture and transmission process. Textured meshes are compact and can provide lower bitrates for the same quality compared to other 3D data representations. However, streaming textured meshes creates compute and memory challenges to achieve bandwidth efficiency. MeshReduce addresses these issues by using a pipeline that creates independent mesh reconstructions and incrementally merges them, rather than creating a single mesh directly from all sensor streams. While this enables a more efficient implementation, this approach requires optimal exchange of textured meshes across the network. MeshReduce also incorporates a novel approach for network rate control that divides bandwidth between texture and mesh for efficient, adaptive 3D video streaming. We demonstrate a real-time integrated embedded compute implementation of MeshReduce that can operate with commercial Azure Kinect depth cameras as well as a custom sensor front-end that uses LiDAR and 360. camera inputs to dramatically increase coverage.

关键词： Computing methodologies-Computer graphics-Graphics systems and interfaces-Mixed / augmented reality Information systems-Information systems applications-Multimedia information systems-Multimedia content creation

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DAUSK: A Transactional Graph Structure for Skewed Dynamic Graph Storage 22

DAUSK: A Transactional Graph Structure for Skewed Dynamic Gr...

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22nd ieee International symposium on Parallel and Distributed Processing with applications, ISPA 2024

作者： Ding, Anna Li, Yujun Feng, Yuening Hu, Sicong Hou, Mengshu Zhan, Yueyang University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798331509712

Dynamic graphs are widely used in real-world applications and exhibit structural skew, which leads to skewed updates. Existing systems that support transactional updates often fail to fully consider this phenomenon, struggling to balance update and query performance. Inspired by the concepts of hierarchical thinking and uneven rebalancing on PMA, we propose DAUSK, a high-performance in-memory structure for dynamic graph storage that supports efficient graph analytics and rapid transactional updates. DAUSK addresses the skewed characteristics of graphs by employing two types of data structures: an unrolled skip list for frequently updated high-degree vertices, allowing asymptotically faster searches and updates, and a compact array-like structure called UPMA for medium and low-degree vertices, enabling efficient sequential scans. At the same time, DAUSK uses a vertex-centric strategy to partition UPMA and applies uneven gap allocation based on vertex degrees. Futhermore, considering the characteristics of transactions on graphs, DAUSK uses the well-established 2PL concurrency protocol to support millions of transactional updates per second. Experimental results demonstrate that DAUSK is up to 10.17×, 3.29× and 1.52× faster in ingesting graph updates compared to three state-of-the-art transactional graph systems, i.e., LiveGraph, Teseo and Sortledton. As for graph analytics, DAUSK achieves comparable, if not superior, performance compared to the other three graph systems. © 2024 ieee.

关键词： Graph structures

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Smart embedded System for Accident Pre-Alert and Prevention Using Machine Learning 2

Smart Embedded System for Accident Pre-Alert and Prevention ...

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2nd International Conference on Artificial Intelligence and Machine Learning applications, AIMLA 2024

作者： Shakunthala, M. Vimal Kumar, M.N. Dinesh Reddy, P. Pavan Reddy, P. Sai Sohith Reddy, P. R.M.D. Engineering College Department of Electronics and Communication Engineering Chennai India Sona College of Technology Department of Mechatronics Engineering Salem India

ISBN: (纸本)9798350349221

Road traffic accidents remain a significant global concern, necessitating innovative solutions for accident prevention. This paper introduces a Smart embedded System for Accident Pre-Alert and Prevention Using Machine Learning (SESAPP) designed to mitigate road safety risks through real-time accident pre-alerts and prevention measures. SESAPP integrates various sensors, including heart rate, ultrasonic, MEMS, eye blink, and alcohol sensors, along with an Arduino Mega microcontroller for data acquisition and processing. Additionally, the system incorporates GPS and GSM modules for location tracking and communication. Python programming language, coupled with Random Forest and Linear Regression algorithms, is employed for data analysis and accident prediction. Experimental results demonstrate the effectiveness of SESAPP in enhancing road safety by accurately predicting potential accidents and triggering timely interventions. © 2024 ieee.

关键词： Accident prevention

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Scheduling with time Aware Shaping in Integrated Ethernet and Wi-Fi Networks

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SN Computer Science 2024年第8期5卷 1-10页

作者： Gopalakrishnan, Abhilash Duttagupta, Subhasri Nadig, Deepak Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Amritapuri Kerala Kollam 690525 India Department of Computer and Information Technology Purdue University 401 N Grant St West Lafayette 47907-2021 IN United States

Communication technologies play a significant role in systems engineering. The proliferation of connected embedded systems has resulted in Internet of Things applications. Many of these systems are safety or mission critical. For example, in smart manufacturing or health, reliability and low latency are significantly important. A deterministic communication system with real-time capability is essential for ensuring safety in those circumstances. Patient monitoring and remote surgery are two such examples. The maximum permitted delay for video in remote surgery is 200 ms and the minimum allowed latency for tactile feedback is 10 ms. The prior efforts of VLAN tagging over Ethernet are insufficient to ensure determinism and reliability. The upcoming ieee time-Sensitive Networking (TSN) standards have enabled determinism by regulating latency, jitter, and packet loss across different types of flows. However, currently, it is only widely available on Ethernet. The paper explores a scheduling approach for an integrated Ethernet and WiFi scenario dealing with mixed-priority traffic that leads to minimal violations of the end-to-end delay requirement. With WiFi TSN bridges and access points equipped with time Aware Shapers, the proposed scheduling strategy is able to offer determinism while satisfying the requirements of a specific class of IoT applications. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Ethernet Reinforcement learning Scheduling Simulation time sensitive networking WiFi

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Water Quality Monitoring and Control in Urban Areas in real-time via IoT and Mobile applications 3

Water Quality Monitoring and Control in Urban Areas in Real-...

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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Mohanasundaram, R. Sagar, Raghav Kumar Khandelwal, Animan Upadhyay, Diwas Poddar, Harshit Rajagopal, Sivakumar Vellore Institute of Technology School of Computer Science and Engineering Vellore India Vellore Institute of Technology School of Electronics Engineering Vellore India

ISBN: (纸本)9798350372120

The presence of impurities in water resulting from the expansion of industrial activities and the disregard of regulations aimed at protecting the environment presents considerable threats to the well-being of the general population. The establishment of reliable access to uncontaminated drinking water assumes paramount importance in the realm of disease prevention. The continuous monitoring of the quality of water in real-time serves as an indispensable measure for ensuring its safety. The objective of this article is to introduce a system that capitalizes on the Internet of Things (IoT) to automate the distribution and management of water resources within urban areas. By making use of embedded technology, this system allows for the uninterrupted surveillance and regulation of water quality. To further streamline the management process, an application compatible with the Android operating system has been developed to promptly notify users of any irregularities, thereby enabling remote control. Moreover, a web-based application has been designed to cater to the needs of iOS users, thereby broadening accessibility. This comprehensive approach not only heightens the level of user awareness but also provides them with greater control over their water supply, thereby enhancing public health outcomes. © 2024 ieee.

关键词： Internet of things

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Research on Internal Temperature and Strain of Soft-packed Batteries under Overcharging Conditions based on Built-in Fiber Bragg Grating Sensors

Research on Internal Temperature and Strain of Soft-packed B...

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ieee International Conference on High Voltage Engineering and applications (ICHVE)

作者： Shen, Zhi-Wei Zhang, Yubo Li, Meng Wang, Jianxin Song, Ruimin Chen, Weigen Zhang, Sida Ming, Zifeng Chongqing Univ Sch Elect Engn Natl Innovat Ctr Ind Educ Integrat Energy Storage State Key Lab Power Transmiss Equipment Technol Chongqing Peoples R China

ISBN: (纸本)9798350374995;9798350374988

The grim situation of the gradual depletion of primary energy sources enables the utilization of battery storage such as lithium-ion batteries to present a trajectory of rapid growth, and the safe and reliable operation of lithium-ion batteries has always been emphasized. Lithium iron phosphate soft-packed batteries are widely used in the field of grid energy storage due to their low explosiveness and design flexibility, but currently, there are fewer studies on internal temperatures and strains, which under over-charging condition are hidden dangers affecting safe operation. Thus, this paper adopts the fiber Bragg grating (FBG) technology with the advantages of small size, anti-electromagnetic interference, chemical inertness, and fast response speed, enabling real-time in-suit monitoring of temperature and strain of lithium-ion soft-packed battery under over-charging conditions, realizing multi-parameter characteristic quantity online monitoring based on FBG implantation, analyzing the temperature variability between inside and outside of the battery, and providing support for the early warning of battery failures and laying a foundation for the enhancement of the stability and reliability of the practical application of electrochemical energy storage batteries.

关键词： Lithium-ion battery(LIB) battery overcharging online temperature and strain measurement fiber optics embedded sensors

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Artificial Intelligence Based System on Enhancing the Capabilities of Transport System: A Systemic Literature Review

Artificial Intelligence Based System on Enhancing the Capabi...

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2023 ieee symposium on Industrial Electronics and applications, ISIEA 2023

作者： Malik, Muhammad Zain Nazir, Shah Khan, Habib Ullah College of Management and Technology Qatar University Dept. of Accounting & Information System Doha Qatar University of Swabi Swabi Pakistan Dept. of Computer Science Swabi Pakistan

ISBN: (纸本)9798350347494

Recent years have seen a considerable increase in the difficulty for our society in ensuring deep-rooted sustainability of traditional technology involve in critical structure. The role of Artificial intelligence (AI) is gaining importance significantly. By delivering ubiquitous real-time applications, It has aided in improving smart environments in many different industries, including smart cities, manufacturing, transportation, health, and the Internet of Things (IoT) by delivering ubiquitous real-time applications. As the technologies like natural language processing, deep learning, machine learning (ML), and others dramatically improve the functionality of communications, digital commerce, content, and apps, AI is poised to fundamentally change the information and communications technology (ICT) industry. Technological advancements brought changes that affect how we live nationally and internationally. The expansion of the economy has been significantly influenced by transportation. It has recently faced several challenges, including the competitiveness of public transportation and an inability to improve its services. Transport systems continue to have operational issues that deter people from using them. These include the fact that drivers frequently travel either deliberately, slowly, or dangerously quickly, making the schedules posted at bus stops untrustworthy. The most effective remedies to these cyber threats are developed using AI, which also offers the best answer. Security hazards are another unexpected effect of these technological improvements. In order to increase the effectiveness of transportation operations and improve public service, this study makes use of cutting-edge artificial intelligence technology. It also clarifies the capabilities of an AI-based transport system to guarantee high dependability and security in the future. The paper also discusses how AI-based systems can play a part in the intelligent transport system. © 2023 ieee.

关键词： Deep learning

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Improved Bus Contention Analysis for 3-Phase Tasks 29

Improved Bus Contention Analysis for 3-Phase Tasks

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29th ieee International Conference on embedded and real-time Computing Systems and applications, RTCSA 2023

作者： Arora, Jatin Rashid, Syed Aftab Nelissen, Geoffrey Maia, Claudio Tovar, Eduardo CISTER ISEP Porto Portugal VORTEX CoLab Portugal Eindhoven University of Technology Eindhoven Netherlands

ISBN: (纸本)9798350337860

The 3-phase task execution model has shown to be a good candidate to tackle the memory bus contention problem. It divides the execution of tasks into computation and memory phases that enable a fine-grained memory bus contention analysis. However, existing works that focus on the bus contention analysis for 3-phase tasks, neglect the fact that memory bus contention strongly relates to the number of bus/memory requests generated by tasks, which, in turn, depends on the content of the cache memories during the execution of those tasks. These existing works assume that the worst-case number of bus/memory requests will be generated during all the memory phases of all tasks, irrespective of the already existing content in the cache memory. This overestimates the memory bus contention of tasks, leading to pessimistic worst-case response time (WCRT) bounds. This work proposes a holistic approach towards bus contention analysis for 3-phase tasks by (1) deriving an upper bound on the actual cache misses of tasks that lead to bus/memory requests;(2) improving State-of-the-Art (SOTA) bus contention analysis of two bus arbitration schemes that dominate all existing works on the bus contention analysis for 3-phase tasks;and (3) performing an extensive experimental evaluation under different settings to compare the proposed analysis against the SOTA. Results show that incorporating a tighter bound on the number of cache misses of tasks into the bus contention analysis can lead to a significant improvement in the task set schedulability. © 2023 ieee.

关键词： real time systems

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Multi-Sensing System Based on Fiber Bragg Grating technology in Variable Stiffness Catheter for Temperature and Force Measurements

Multi-Sensing System Based on Fiber Bragg Grating Technology...

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ieee International symposium on Medical Measurements and applications (MeMeA)

作者： De Tommasi, Francesca Richter, Michiel D'Alvia, Livio Carassiti, Massimiliano Palermo, Eduardo Del Prete, Zaccaria Schena, Emiliano Misra, Sarthak Venkiteswaran, Venkatasubramanian Kalpathy Univ Campus Biomed Roma Sch Engn Rome Italy Univ Twente Biomech Engn Enschede Netherlands Sapienza Univ Rome Mech Engn Rome Italy Univ Campus Biomed Roma Sch Med Rome Italy Fond Pol Univ Campus Biomed Rome Italy Univ Groningen Biomat & Biomed Technol Groningen Netherlands

ISBN: (纸本)9798350308006;9798350307993

This study focuses on the design, development, characterization, and feasibility assessments of a multi-sensing system based on fiber Bragg grating sensors (FBGs) to monitor force and temperature within a shape-memory polymer (SMP) guiding catheter. SMPs possess the unique ability to transition between rigid and flexible states based on user's needs, making them invaluable resources in minimally invasive surgery (MIS), as they allow for improved flexibility and adaptability even in anatomically complex areas. As the softening action takes place by heating the SMP, temperature monitoring is a key factor in determining the SMP flexibility. By embedding FBGs, it is possible to get real-time feedback, ensuring that the catheter achieves optimal flexibility. Additionally, this study tackles a significant hurdle clinicians face: the absence of tactile feedback. Sensing variations in tissue properties is essential for achieving reliable performance. For this reason, this work introduces a novel approach by equipping a biopsy needle with FBGs capable of measuring both temperature and force. The thermal characterization performed to assess the thermal sensitivity ( ST) of the FBGs used for temperature measurements revealed a mean ST value of 0.029 nm.C-1. Additionally, temperature measurements during thermal activation demonstrated the suggested system's ability to track temperature variations along the SMP catheter length (with a maximum of 68 degrees C). Lastly, compression tests were performed to evaluate the multi-sensing system's capacity to distinguish between compounds with varying stiffness (DragonSkin10 and 30). The observed greater force values in the tests involving DragonSkin30 (2.3 N), compared to DragonSkin10 (up to 1.3 N) for identical displacements, underscore the capability of the proposed system to discriminate between materials based on their stiffness levels.

关键词： force measurements fiber Bragg grating magnetically-actuated shape memory polymer temperature measurements variable stiffness guiding catheter

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Anomaly Detection from CCTV Camera Feed 10

Anomaly Detection from CCTV Camera Feed

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10th ieee International symposium on Smart Electronic Systems, iSES 2024

作者： Aakash Chauhan, Lakshay Sharma, Shubham Deb, Sujay Indraprastha Institute of Information Technology Delhi Computer Science & Engineering Department Delhi India

ISBN: (纸本)9798331533229

The paper presents a novel approach for detecting anomalies like arson, explosion, vandalism, etc in public spaces using CCTV camera feeds. We propose a deep learning-based system that analyzes video streams to identify unusual events or behaviours that deviate from normal patterns. Our method combines Convolutional Neural Networks (CNNs) and Spiking Neural Networks (SNNs) for feature extraction with Long Short-Term Memory (LSTM) networks to model temporal dependencies in the video sequences. The system is trained on the UCF Crime Dataset to learn normal activity patterns and can flag potential anomalies in emulated real-time situations. To enhance accuracy, we incorporate additional computer vision technique, like optical flow, with CNN/SNN and LSTM to get various combinations of models (OF-CNN, OF-CNNLSTM, OF-SNN, OF-SNNLSTM, CNNLSTM) for improved anomaly detection. The proposed system has potential applications in enhancing public safety and security monitoring in urban environments. © 2024 ieee.

关键词： Convolutional neural networks

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