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On Delay-Sensitive Healthcare data analytics at the Network Edge Based on Deep Learning 14

On Delay-Sensitive Healthcare Data Analytics at the Network ...

引用

14th IEEE international Wireless Communications and Mobile computing conference (IWCMC)

作者： Fadlullah, Zubair Md. Pathan, Al-Sakib Khan Gacanin, Haris Tohoku Univ Grad Sch Informat Sci Sendai Miyagi Japan Southeast Univ Dept CSE Dhaka Bangladesh Nokia Bell Labs Access Lab Antwerp Belgium

ISBN: (纸本)9781538620700

As the age of the Internet of Things (IoT) continues to flourish, the concept of smart healthcare has taken an unprecedented turn due to interdisciplinary thrusts. To carry the big healthcare data emanating from the plethora of bio-sensors and machines in the IoT sensing plane to the central cloud, next generation high-speed delivery networks are essential. On the other hand, once the IoT data are delivered to the cloud, the massive IoT healthcare data are processed and analyzed employing the state-of-the-art analytics tools such as deep machine learning and so forth. However, given the explosion of big data (from various sources in addition to the healthcare data), the delivery network as well the cloud may experience network and computational congestion, respectively. This may impact the real-time analytics of the healthcare data, e.g., critical for in-house patients and senior citizens aging at home. To address this issue, the emerging IoT edge analytics concept can be regarded as a promising solution to process the big healthcare data close to the source. For large-scale IoT deployments, this functionality is critical because of the sheer volumes of data being generated. In this paper, we propose a deep learning based IoT edge analytics approach to support intelligent healthcare for residential users. The performance of the proposal is validated using computer-based simulation for online training of a real dataset. The reported results of our proposal exhibit encouraging performance in terms of low loss rate, high accuracy, and low execution time to support near real-time actionable decision making on the healthcare data.

关键词： Medical services Machine learning Delays Cloud computing Senior citizens Sensors Aging"

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The Future of smart Clothing: A Kit Designed to Detect Vital Health Parameters. 2

The Future of Smart Clothing: A Kit Designed to Detect Vital...

引用

2nd international conference on intelligent computing and Control Systems (ICICCS)

作者： Kansara, Rashi Chauhan, Jigar Univ Coll Engn Mumbai Maharashtra India

ISBN: (纸本)9781538628423

The Future of smart Clothing: A Kit Designed to Detect Vital Health Parameters is a prototype that can be embedded in any type of fabric anytime, anywhere to find health related information and people can view their previously collected data on mobile application through their authentication, thereby measuring few parameters such as heart rate (BPM) using Pulse Sensor. The system counts the number of times emotion change detected by using Galvanic Skin Response (GSR) Sensor and real time body temperature is also calculated using an accurate Temperature Sensor and lastly 3- Axis Accelerometer Sensor shows the step count of an individual. All these above sensed parameters will be sent to a central processor for processing and then transferring it to a mobile web application through wireless communication. The data can be viewed by the user on smart phone application. Real time data analytics can be done for diagnosing various symptoms for detecting diseases.

关键词： Pulse sensor Beats Per Minute (BPM) Galvanic Skin Response (GSR) 3-Axis Accelerometer MLX90614 Digital Infrared Temperature Sensor NodeMCU Android Application WiFi

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Leveraging data analytics in Systems Engineering - Towards a Quantum Leap in Railway Reliability 3rd

Leveraging Data Analytics in Systems Engineering - Towards a...

引用

3rd international Asia-Pacific conference on Complex Systems Design and Management (CSD and M Asia)

作者： Tsang, Thaddeus Hong, Joyce Wong, Mun Yih Ho, Kum Fatt Land Transport Author 1 Hampshire RdBlock 10Level 3 Singapore 219428 Singapore

ISBN: (纸本)9783030028862

Today's world sees data analytics more prevalent than ever before, mining and interpreting data through various trends. In Singapore, the Land Transport Authority's (LTA) new role as asset owner for its railway operating assets has also given impetus towards establishing a sustainable digital ecosystem. Timely decisions are enabled based on accurate understanding of the asset condition from the network of data and analytic processes, to maintain safety and reliability of the Rapid Transit Systems (RTS) throughout its service life. In addition to expounding on the data analytics process, this paper also explores the potential benefits from the data discovery and the challenges in doing so. The crux is to provide a more robust, reliable and resilient public transport system through data analytics, as we strive towards a quantum leap in railway reliability for our commuters.

关键词： data analytics

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Content-based analytics: Moving Beyond data Size 6

Content-based Analytics: Moving Beyond Data Size

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6th IEEE international conference on Big data computing Service and Applications (IEEE BigdataService)

作者： Tsoumakos, Dimitrios Giannakopoulos, Ioannis Ionian Univ Dept Informat Corfu Greece NTUA Sch Elect & Comp Engn Comp Syst Lab Athens Greece

ISBN: (纸本)9781728170220

Efforts on Big data technologies have been highly directed towards the amount of data a task can access or crunch. Yet, for content-driven decision making, it is not (only) about the size, but about the "right" data: The number of available datasets (a different type of volume) can reach astronomical sizes, making a thorough evaluation of each input prohibitively expensive. The problem is exacerbated as data sources regularly exhibit varying levels of uncertainty and velocity/churn. To date, there exists no efficient method to quantify the impact of numerous available datasets over different analytics tasks and workflows. This visionary work puts the spotlight on data content rather than size. It proposes a novel modeling, planning and processing research bundle that assesses data quality in terms of analytics performance. The main expected outcome is to provide efficient, continuous and intelligent management and execution of content-driven data analytics. intelligent dataset selection can achieve massive gains on both accuracy and time required to reach a desired level of performance. This work introduces the notion of utilizing dataset similarity to infer operator behavior and, consequently, be able to build scalable, operator-agnostic performance models for Big data tasks over different domains. We present an overview of the promising results from our initial work with numerical and graph data and respective operators. We then describe a reference architecture with specific areas of research that need to be tackled in order to provide a data-centric analytics ecosystem.

关键词： big data data quality Machine Learning modeling scheduling

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Identifying Water Consumption Patterns in Education Buildings Before, During and After COVID-19 Lockdown Periods 7

Identifying Water Consumption Patterns in Education Building...

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7th IEEE international conference on smart computing (smartCOMP)

作者： Zecchini, Marco Griesi, Alessandra Anna Chatzigiannakis, Ioannis Amaxilatis, Dimitrios Akrivopoulos, Orestis Sapienza Univ Rome Rome Italy Spark Works Ltd Galway Ireland

ISBN: (纸本)9781665412520

Adopting modern emerging technologies of smart metering based on IoT that extend existing water distribution systems is of paramount importance for improving the operational efficiency of the water supply system in the cities and rural communities. Real-world data collected by smart water meters allows the analysis of consumption of water. In this work, data collected over a period of 28 months is analyzed on weekly, daily and hourly basis to identify usage patterns in relation to the restrictions imposed by the local authorities as a response to the COVID-19 emergency taking place during 2020 and 2021. The evaluation of water consumption before, during and after the lockdown periods highlights the impact of human actions. A novel data-driven method is presented to profile buildings that can help identify similarities and highlight differences across water usage patterns.

关键词： smart Water Grid smart Water Meters IoT COVID-19 Usage analysis Usage Profiling

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intelligent Recognition System for High Precision Image Significant Features in Large data Background

Intelligent Recognition System for High Precision Image Sign...

引用

international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Lu, Kong Jiangxi Modern Polytech Coll Nanchang 330095 Jiangxi Peoples R China

ISBN: (纸本)9783030152352;9783030152345

High precision image pattern recognition technology based on large data background is an important part of computer application technology. With the rapid development of digital image processing technology and pattern recognition technology, image pattern recognition technology has been applied more comprehensively in various fields. This paper briefly introduces image processing technology and its new development trend, focusing on image recognition technology and new development.

关键词： Image features Image intelligent recognition Image processing

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Enabling smart Homes Through Health Informatics and Internet of Things for Enhanced Living Environments 8th

Enabling Smart Homes Through Health Informatics and Internet...

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World conference on Information Systems and Technologies (WorldCIST)

作者： Marques, Goncalo Pitarma, Rui Univ Beira Interior Inst Telecomunicacoes P-6201001 Covilha Portugal Polytech Inst Guarda P-6300559 Guarda Portugal Univ Beira Interior CISE Electromechatron Syst Res Ctr P-6201001 Covilha Portugal

ISBN: (纸本)9783030456962;9783030456979

As people spend most of their time inside buildings, indoor environment quality must be monitored in real-time for enhanced living environments and occupational health. Indoor environmental quality assessment is based on the satisfaction of the thermal, sound, light and air quality conditions. The indoor quality patterns can be directly used to promote health and wellbeing. With the proliferation of the Internet of Things related technologies, smart homes must incorporate monitoring solutions for data acquisition, transmission, and microsensors for several real-time monitoring activities. This paper presents a low-cost and scalable multi-sensor smart home solution based on Internet of Things for enhanced indoor quality considering acoustic, thermal and luminous comfort. The proposed system incorporates three sensor modules for data collection and use Wi-Fi communication technology for Internet access. The system has been developed using open-source and mobile computing technologies for real-time data visualization and analytics. The acquisition modules incorporate light intensity and colour temperature, particulate matter, formaldehyde, relative humidity, ambient temperature and sound sensor capabilities. The results have successfully validated the scalability, reliability and easy installation of the proposed system.

关键词： Ambient assisted living Enhanced living environments Health informatics Indoor environmental quality Internet of Things smart home

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A Blockchain-based and Privacy-Protected Method for Sharing of BIM Big data 7

A Blockchain-based and Privacy-Protected Method for Sharing ...

引用

7th international conference on Cloud computing and Big data analytics, ICCCBDA 2022

作者： Wang, Hongwei Hao, Xiaohan Yin, Lian Gong, Peisong Xiong, Feng Ren, Wei Wuhan Municipal Road and Bridge Co. Ltd Wuhan430050 China School of Software University of Technology Sydney UltimoNSW2007 Australia School of Computer Science China University of Geosciences Wuhan430074 China School of Economics and Management China University of Geosciences Wuhan430074 China School of Business Administration Zhongnan University of Economics and Law Wuhan430073 China Hubei Key Laboratory of Intelligent Geo-Information Processing Wuhan430074 China

ISBN: (纸本)9781665487115

Currently, cloud computing and big data are largely applied in smart construction, or so-called industrial Internet of Things 4.0. Building Information Model (BIM) performs as an elemental information and data unit, which is extensively employed in entire construction processes (lifespan) and inter-Acted with various entities including investors, employers, design institutes, construction companies, and monitors. They thus can achieve quantitative computing, measurement, and managements by sharing BIM data. The accumulation of BIM data will finally approach to a big data for construction intelligence. However, sharing BIM big data may be subtle in terms of privacy leakage, since BIM data may enclose the critical infrastructure information, homeland security data, structure parameters, and design intellectual property. It thus is of urgent importance to protect privacy in the BIM data sharing. In this paper, we propose a blockchain based method to protect data privacy in BIM data sharing, which can be applied for guaranteeing the information security in next generation industrial Internet of Things for smart construction. © 2022 IEEE.

关键词： data privacy Cloud computing Computational modeling Information security Big data data models Blockchains

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Forecasting the potential influence of Covid-19 using data Science and analytics

Forecasting the potential influence of Covid-19 using Data S...

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2021 IEEE international conference on Innovative computing, intelligent Communication and smart Electrical Systems, ICSES 2021

作者： Murale, Monish Devi, N. Gokul, Ar Guru Leela Rani, P. Navishvardanaa, S. Sri Venkateswara College of Engineering Department of Information Technology Sriperumbudur India

ISBN: (纸本)9781665435215

The major purpose of the study topic is to use data science to anticipate the future effect of COVID-19 using existing data. The goal of this research is to use data science and analytics to generate precise forecasts of the number of substantiations and deaths. LSTM, GRUs, and Prophet are the major models created and tested for the solution. An LSTM model is a type of Recurrent Neural Network that is used to forecast datasets with increasingly changing patterns. Gated recurrent units only has two gateways: reboot and update. The prophet is best suited for forecasting assignments involving observation swith at least a year of history. The various models discussed above were used to the covid-19 data set to forecast the number of positive cases, active cases, and deaths associated with covid-19. We trained the model using data from April and May 2021 to demonstrate a comparison between the observed and expected number of positive events. To assume the future happing of COVID-19 by applying models which are in use, so that we will be able to calculate the impact of the disease's potential spread throughout the human being, preparing our selves to make proper planning and idea to prevent further transmission and equip health systems to manage the disease properly and battle the worldwide pandemic. © 2021 IEEE.

关键词： Speech recognition

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smart Food Scanner System Based on Mobile Edge computing 8

Smart Food Scanner System Based on Mobile Edge Computing

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8th IEEE international conference on Cloud Engineering (IC2E)

作者： Javadi, Bahman Quoc Lap Trieu Matawie, Kenan M. Calheiros, Rodrigo N. Western Sydney Univ Sch Comp Data & Math Sci Sydney NSW Australia

ISBN: (纸本)9781728110998

smart applications, including Internet of Things (IoT) and Big data analytics, are traditionally hosted by cloud infrastructures, which can result in high latency and cost beyond users expectation. Edge computing has emerged as a paradigm that can alleviate the pressure on clouds by delegating parts of the computation to devices in the edge of the network, at closer proximity to end users and IoT devices. In this paper, we discuss a smart application, built on top of mobile edge computing concept, to enables users to measure and analyse their food intake and support nutritional decision-making. The approach utilizes mobile edge computing to offload application computations and communications to the edge, thus saving battery life, increasing the processing capacity, and improving user comfort. In order to develop this system, we propose a loosely coupled architecture for a smart food scanner and then implement it using various IoT sensors. The performance evaluation results reveal that the implemented system can be used as an interactive appliance by users with minimum dependency and usage of their mobile phones.

关键词： Mobile edge computing

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