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Optimizing IoT-Based Healthcare systems with Scalable AI and Machine Learning Using Cloud Platforms 1

Optimizing IoT-Based Healthcare Systems with Scalable AI and...

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1st international conference on Innovations in Communications, Electrical and Computer Engineering, ICICEC 2024

作者： Dankan Gowda, V. Ingole, Balaji Shesharao Agarwal, Suvidha Prafulla, P.S. Srinivas, D. Kumari, Gajanethi Swathi Bms Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Evans GA United States Jims Engineering Management Technical Campus Greater Noida India Bgsit Adichunchanagiri University Faculty of Engineering Management & Technology Dept. of Ece Karnataka B G Nagara571448 India Sr University School of Business Telangana Warangal India Symbiosis Centre for Management Studies Hyderabad India Pune India

ISBN: (纸本)9798350376517

The connection of IoT-based healthcare systems with large-scale artificial intelligence and cloud platforms can be considered as radical in terms of prognosis and improvement of real-time patient attention. IoT technology in healthcare calls for an intelligent model in the cloud computing paradigm for efficient collection, processing, and analysis of the gathered data, which is provided by this paper's framework. It is intended to improve the precision and speed of the applications in the field of predictive health care including with regard to heart rate, blood pressure, and oxygen saturation, as well as the growability and resource utilization of the system. The feasibility and efficiency of the proposed framework were discussed via specific simulations, indicating that the entire system can process great numbers of data with low latency and high predictive accuracy. The XGBoost model with a 93% prediction accuracy is suggested by results;intra-cloud resource consumption has been consistent. The utilization of AI models within cloud infrastructure also enabled effective real time data management. Thus, the challenges like data privacy, long time of data processing, high energy consumption were revealed but the system has a good potential for further developments of IoT based health care systems. © 2024 ieee.

关键词： Cloud platforms

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Interactive Programming as an "Operating System" for Resilience in Distributed systems 42

Interactive Programming as an "Operating System" for Resilie...

引用

42nd ieee international conference on Distributed computing systems (ICDCS)

作者： Zak, Albert Univ Appl Sci Tech Wien Vienna Austria

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

Accrued incidental complexity in software systems lowers their resilience. This thesis proposes means for understanding and evolving complex situated systems through broadening the scope of what is considered to be the act and medium of programming. The key idea of this thesis is a universal data model based on accreting assertions and retractions of atomic facts over time to represent code and state in a single level, ephemeral and persistent. Changes to both code and data together with provenance are immutably reified in the same model. A minimal set of interactions is expected to support live inspection and controlled modification of a running system by coupling the editing environment to the runtime and extending the language of REPL (read-evaluate-print-loop) interactions with means of direct manipulation. Combining algebraic effect systems with object capabilities allows safe experimentation on a live production system. By way of Design Science Research, this thesis will iteratively yield designs, implementations, and evaluations of usable proof-of-concept artifacts comprising a resilient interactive programming system.

关键词： read-evaluate-print-loop entity-attribute-value capabilities effect handlers direct manipulation

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DRA: Ultra-Low Latency Network I/O for TSN embedded End-systems 31

DRA: Ultra-Low Latency Network I/O for TSN Embedded End-Syst...

引用

31st ieee/ACM international Symposium on Quality of Service, IWQoS 2023

作者： Li, Chenglong Li, Tao Li, Junnan Fu, Wenwen Wang, Baosheng College of Computer Science and Technology National University of Defense Technology Changsha China

ISBN: (纸本)9798350399738

time-Sensitive Networking (TSN) is a promising open-source technique for hard real-time embedded fields such as industrial automation and autonomous driving. The embedded end-system deployed in TSN must guarantee deterministic latency and jitter for network I/O in above scenarios. Recent researchers focus on eliminating jitter but neglect to reduce latency. The network I/O latency is still too high to satisfy the dozen-microsecond requirements of latency-sensitive applications. We observed that (1) the data path from registers to external storage is actually the bottleneck for latency reduction, and (2) the serial processing of CPU and NIC can be further optimized. Therefore, we proposed DRA (Direct Register Access), a novel network I/O mechanism to achieve microsecond-level latency. DRA delivers whole packet data from the NIC directly into extended registers inside the CPU, avoiding the waste of time to move data between internal registers and external storage. Moreover, DRA promotes parallelization of CPU processing and NIC transfer to reduce latency. Considering the increasing popularity of RISC-V ISA in embedded systems, we prototype DRA using an open-source RISC-V core on FPGA and evaluate it under real-life application scenarios. Compared with existing mechanisms, experimental results demonstrate that DRA reduces the network I/O latency and jitter by at least 60% and 30%, achieving microsecond-level network I/O processing. © 2023 ieee.

关键词： Jitter

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A Comprehensive Study on Simultaneous Localization and Mapping (SLAM): Types, Challenges and applications

A Comprehensive Study on Simultaneous Localization and Mappi...

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2023 international conference on Sustainable computing and Smart systems, ICSCSS 2023

作者： Khole, Aneesh Thakar, Atharva Shende, Shreyas Karajkhede, Varad Pune India

ISBN: (纸本)9798350333602

Simultaneous Localization and Mapping (SLAM) has emerged as a pivotal research area within the realm of artificial intelligence mobile robots. Its significance lies in the ability to facilitate self-exploration of unknown environments without the aid of human intervention. The unique and distinctive aspect of SLAM is its ability to map and localize the robot's surroundings recursively and continuously. With the advent of SLAM, numerous algorithms have been proposed to address the challenges encountered in real-world applications of this technique. The main aim of this research is to provide a comprehensive and thorough analysis of the theoretical underpinnings, recent advancements, distinctive features, implementation strategies, and emerging issues in the domain of SLAM. This exploration intends to enhance the understanding and promote the advancement of this critical research area. © 2023 ieee.

关键词： Extended Kalman filters

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Enhancing Network Security with Deep Learning on Intrusion Detection and Prevention systems 5

Enhancing Network Security with Deep Learning on Intrusion D...

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2023 5th international conference on Artificial Intelligence and Computer applications, ICAICA 2023

作者： Wang, Ruibin Dongying Vocational Institute Dongying China

ISBN: (纸本)9798350323313

The significance of real-time threat identification in network security in an age of constantly changing cyberthreats cannot be emphasised. Conventional Intrusion Detection and Prevention systems (IDPS) frequently find it difficult to stay up with the evolving strategies used by cybercriminals. This study investigates how to greatly improve real-time threat detection capabilities in IDPS by integrating Long Short-Term Memory (LSTM) approaches. The difficulties faced by conventional IDPS are discussed, along with the contribution of LSTM to real-time threat identification, near real-time threat identification, adaptability to new threats, and the effectiveness of LSTM-based IDPS in scenarios with heavy traffic. The findings show that by shortening the detection-to-mitigation time gap and guaranteeing a more secure and robust network architecture, LSTM-based IDPS has the potential to completely transform network security. © 2023 ieee.

关键词： Long short-term memory

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Acceleration of video stabilization using embedded GPU 33

Acceleration of video stabilization using embedded GPU

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33rd international conference on Application-specific systems, Architectures and Processors (ASAP)

作者： Mimura, Yuzuki Qiong, Chang Maruyama, Tsutomu Univ Tsukuba Sch Sci & Engn Tsukuba Ibaraki Japan Tokyo Inst Technol Sch Comp Tokyo Japan Univ Tsukuba Intelligent & Mech Interact Syst Tsukuba Ibaraki Japan

ISBN: (数字)9781665483087

ISBN: (纸本)9781665483087

Video stabilization is a technique used to eliminate the shakiness in video. It plays an important role to improve the quality of the videos captured by cameras mounted on drones and autonomous robots, and handheld cameras. In these cases, it is generally required to achieve real-time video stabilization using low-power and low-cost devices. In this research, we focus on software video stabilization, and propose a new implementation method using an embedded GPU. Our target device is Nvidia Jetson Nano, which is one of the smallest and least power consumption embedded GPUs. In our implementation, 1) multi-threads on the CPU on Jetson Nano and the GPU run asynchronously and in parallel to achieve high performance, 2) the size of the search area is minimized to reduce the amount of computation assuming that sufficiently fast processing speed is possible using the GPU, and 3) the data transfer from the global memory of the GPU is minimized to hide the high latency. Our implementation achieves 81.4 fps for full HD videos, and its quality is high enough for practical use.

关键词： video stabilization embedded GPU real-time

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Detection of Dangerous Situations by Sounds in real-time Using Deep Learning 4

Detection of Dangerous Situations by Sounds in Real-Time Usi...

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4th ieee international conference on Smart Information systems and Technologies, SIST 2024

作者： Momynkulov, Zeinel Omarov, Nurzhan Uxikbayev, Yerkebulan Department of MCM International Information Tehnology University Almaty Kazakhstan Department of Information Systems Al-Farabi Kazakh National University Almaty Kazakhstan Khoja Akhmet Yassawi International Kazakh-Turkish University Turkistan Kazakhstan

ISBN: (纸本)9798350374865

This research paper presents a comprehensive exploration of the utilization of advanced machine learning techniques, specifically the Bidirectional Long Short-Term Memory (BiLSTM) neural network model, for the classification of dangerous urban sounds. In the context of increasingly complex urban environments, where a multitude of acoustic signals coexist, accurate identification of hazardous auditory cues is imperative for bolstering urban safety and security. The BiLSTM model emerges as a pivotal tool, adept at capturing intricate temporal relationships and contextual nuances, thereby facilitating the discrimination between benign and perilous urban sounds. Through rigorous experimentation, our model achieves a commendable 90% accuracy rate, signifying its potential for practical deployment in urban settings. Beyond model development, this research extends its impact by introducing a web application that enables real-time sound analysis and user engagement, bridging the gap between sophisticated machine learning capabilities and practical urban safety applications. As urban centers continue to evolve and confront the challenges posed by increasing population density and complexity, the fusion of advanced machine learning with the urban soundscape holds immense promise in the creation of safer and smarter urban ecosystems, ultimately enhancing the well-being and security of urban dwellers worldwide. © 2024 ieee.

关键词： Population statistics

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IoT-Based embedded Device Development and real-time Analysis for Unexpected Operations of Motors 6

IoT-Based Embedded Device Development and Real-Time Analysis...

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6th international conference on Measurement Instrumentation and Electronics (ICMIE)

作者： Riyota, Teerapat Boonpramuk, Panuthat Nuratch, Santi King Mongkuts Univ Technol Thonburi KMUTT Dept Control Syst & Instrumentat Engn Bangkok Thailand

ISBN: (纸本)9781665468435

In most industrial automation systems, all machines and equipment must operate smoothly and continuously to maintain the system performance. Therefore, all kinds of unexpected failures of the system cannot be accepted. For this reason, the maintenance processes are the essential operations performed periodically to avoid system failures. Of course, this operation takes time and resources, but it cannot be avoided. It is known that most automation systems compose of electrical motors. They are the core devices for robots and other movable machines. Each motor produces meaningful parameters such as temperature, vibration, speed, noise, and power consumption. This paper presents the design and development techniques of the IoT-based embedded device that can be used for real-time monitoring and analysis of the unexpected operations of motors. The proposed device continuously senses and analyzes motor parameters to monitor and predict unexpected operations. We focus on temperature and unbalanced phenomenal measurement of the motors. The unbalanced parameter is implicitly measured from the speed changes using the time measurement of the sensing signals. The proposed device also supports wireless real-time data exchange to the server. The device and server exchange their data using the WebSockets protocol. The data sent to the server can be used for storage, processing, and monitoring. In this work, we also develop a web-based application that allows users to control and monitor the parameters of motors in real-time. The experimental results show that the proposed method can detect the unbalance operations and temperature of the motors at different operations. Therefore, the proposed system can be used in real-world applications that require abnormality detection, abnormal condition warning, and prediction of mechanical devices.

关键词： embedded system real-time motor measurement internet-of-things machine maintenance industrial automation

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Joining Edge-Enabled Metaverse Services with Network Externality: A Stackelberg Game Approach

Joining Edge-Enabled Metaverse Services with Network Externa...

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2023 ieee international conference on Metaverse computing, Networking and applications, MetaCom 2023

作者： Jiang, Yuna Kang, Jiawen Niyato, Dusit Ge, Xiaohu Xiong, Zehui Xu, Minrui Deng, Ruilong Huazhong University of Science and Technology School of Electronic Information and Communications Wuhan China Guangdong University of Technology School of Automation Guangzhou China Nanyang Technological University School of Computer Science and Engineering Singapore Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China Shenzhen Huazhong University of Science and Technology Research Institute China

ISBN: (纸本)9798350333336

The metaverse is defined as a three-dimensional virtual-real fusion network focused on social connection. Edge computing can empower the metaverse by providing computing resources to realize real-time motion tracking, visual or auditory rendering and virtual scene dynamic change at the edge of networks. Users enjoy the immersive experience provided by the Metaverse Service Provider (MSP), and interact through digital avatars in the virtual world by requesting metaverse services. In this paper, we formulate the edge computing resources pricing, metaverse service rendering bitrate pricing and request problem in the metaverse. Especially, we model the interactions among edge servers, the MSP and Metaverse Service Users (MSUs) as a hierarchical three-stage Stackelberg game. The problem of joining edge-enabled metaverse services is also studied with the consideration of network externality, including the network effect and congestion effect. Based on the backward induction method, we derive the optimal computing resources pricing of edge servers, rendering bitrate pricing of the MSP, and rendering bitrate requests of MSUs. We also prove the existence and uniqueness of the Stackelberg game equilibrium. Simulation results show that the network effect can bring more positive utilities to entities when the social tie coefficient among MSUs is higher. Besides, all entities in the edge-enabled metaverse are affected negatively by the congestion effect. © 2023 ieee.

关键词： Edge computing

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TEEVseL4: Trusted Execution Environment for Virtualized seL4-Based systems

TEEVseL4: Trusted Execution Environment for Virtualized seL4...

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ieee international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Borna Blazevic Michael Peter Mohammad Hamad Sebastian Steinhorst Department of Computer Engineering Technical University of Munich NIO GmbH

The growing computing power of embedded systems has led to an increase in the use of general-purpose Operating systems (OSs) such as Linux. However, the substantial attack surface arising from their complexity makes them unsuitable for safety and security-critical use cases. Addressing this issue requires isolating the security-critical functionalities into separate execution environments and protecting them from the untrusted OS. Arm TrustZone applies this approach by providing hardware-based partitioning of the system into a secure and non-secure world, facilitating a Trusted Execution environment for the protection of security-critical functionality in the secure world. TrustZone, however, falls short when dealing with systems that virtualize multiple operating systems. Another approach to isolate functionality is employing a microkernel, such as the formally proven correct seL4 kernel, especially if it also offers virtualization functions. While current seL4-based virtualization systems offer good security and safety properties, they do not provide TrustZone-compatible security services to their virtualized guests. In this paper, we propose TEEVseL4, a TrustZone-compatible virtualization system leveraging the strengths of the seL4 microkernel, that can provide security services to the Linux guests based on the dynamic, scalable and flexible Trusted computing Base of an seL4 system. A high-level performance benchmarking shows that TEEVseL4 can provide security services with acceptable overheads (less than 20%) when compared to a native TrustZone system, making it an attractive option for platforms with multiple, mutually-distrustful virtualized guests.

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