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EDAARP-Efficient and data-Aggregative Authentic Routing Protocol for Wireless Sensor Networks

EDAARP-Efficient and Data-Aggregative Authentic Routing Prot...

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international conference on data analytics, intelligent computing, and Cyber Security, ICDIC 2020

作者： Arun Kumar, Kurakula Jayaraman, Karthikeyan SITE VIT Tamil Nadu Vellore India

ISBN: (纸本)9789811941610

Wireless sensor networks (WSN) are quickly gaining a lot of research attention, and several communications are required for data sensing in WSN. The sensor nodes collect data from multiple locations and relay it to the central control unit. However, few of the nodes have insufficient resources. Despite the fact that existing routing algorithms support cluster-based routing, these techniques do not consider all of the resource constraints associated with the nodes. The goal is to discuss the design and implementation of a cluster-based network strategy that uses Presumptive data Gathering (PDG) and Selective Information Standards (SIS) algorithms. "This aims to improve energy efficiency by creating a fully connected dedicated node that connects all sub-clusters" is connected using the best processes of a controlled set associated with it, and in these cases, relay nodes are used. The Efficient data-Aggregative Authentic Routing Protocol (EDAARP) is proposed in this work, to preserve actual energy usage and even consistent transmission of sensed data. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Routing protocols

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Target Domain Training data Generation by Moving Object Detection and Label Propagation

Target Domain Training Data Generation by Moving Object Dete...

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ASCE international conference on computing in Civil Engineering (I3CE)

作者： Kim, Taegeon Shin, Giwon Kim, Seokhwan Asari, Vijayan K. Kim, Hongjo Yonsei Univ Dept Civil & Environm Engn Seoul South Korea Univ Dayton Dept Elect & Comp Engn Dayton OH 45469 USA

ISBN: (数字)9780784485224

ISBN: (纸本)9780784485224

Although computer vision technology has shown great potential, its reliability can significantly degrade in the target domain where the model is applied. Collecting and labeling training data from the target domain can address this issue;however, it is a tedious and time-consuming task. To address this issue, this paper presents a novel method generating training data for construction site monitoring. The proposed method consists of extracting moving objects, classifying each region by comparing their features to the target classes, and then assigning class labels. The newly labeled data is copied and pasted to a clear background of the target domain where its foregrounds are removed by image inpainting. Experiments were conducted on construction site videos captured in far-field monitoring environments. The proposed method can significantly reduce the amount of effort required for data collection and labeling, thereby increasing the efficiency of developing robust computer vision models for construction site monitoring.

关键词： Computer vision

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IoT based Novel Design of intelligent Healthcare Monitoring System with Internet of Things and smart Sensors 3

IoT based Novel Design of Intelligent Healthcare Monitoring ...

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3rd international conference on Applied Artificial Intelligence and computing, ICAAIC 2024

作者： Ahmad, Waseem Akhtar Khursheed Suneel, Sajja Nanthini, L. Srivastava, Shambhu Sharan Veerraju, M.Sai Moharekar, Tejashree Tejpal M.S.G. Arts Science & Commerce College Department of Commerce & Management College Road Malegaon Camp 423203 India Telangana Dundigal Hyderabad500043 India India School of Management Sciences Department of Computer Science Varanasi India S R.K.R. Engineering College Dept. of Eee Bhimavaram India Shivaji University Yashwantrao Chavan School of Rural Development Maharashtra Kolhapur India

ISBN: (纸本)9798350375190

This research study introduces the IoT based Healthcare Monitoring System (LIoTHMS), a revolutionary framework designed to enhance healthcare monitoring through the integration of smart sensors. The proposed system incorporates sensors, including the ECG Shield, Heart Rate Muscle Sensor, Pulse Rate Sensor, KY-037 Sound Sensor, and DS18B20 Digital Temperature Sensor. These sensors collectively form a comprehensive solution for real-time patient monitoring. The ECG Shield ensures continuous electrocardiogram monitoring for early detection of cardiac anomalies, while the Heart Rate Muscle Sensor and Pulse Rate Sensor provide valuable data on cardiovascular health. The KY-037 Sound Sensor captures environmental sounds, contributing to auditory health monitoring, and the DS18B20 Digital Temperature Sensor monitors the patient's body temperature. This research study details the architecture of LIoTHMS, emphasizing sensor interconnectivity and its role in creating a healthcare monitoring ecosystem. Through advanced data analytics and machine learning algorithms, LIoTHMS processes real-time data, offering healthcare professionals timely and accurate insights into patient health. This implementation signifies a significant advancement in proactive and personalized healthcare, supporting early disease detection and timely medical interventions. LIoTHMS stands as a testament to the potential of IoT in revolutionizing modern healthcare monitoring. © 2024 IEEE.

关键词： Electrocardiograms

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A smart Electronic Wheelchair Design Using Artificial Intelligence and intelligent Sensors Association 2

A Smart Electronic Wheelchair Design Using Artificial Intell...

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2nd IEEE international conference on intelligent and Innovative Technologies in computing, Electrical and Electronics, ICIITCEE 2024

作者： Balamurugan, R. Kanchana, D. Anni Princy, B. Jaisudha, J. Malathi, P. Glory, E. Ajk College of Arts and Science Department of Artificial Intelligence and Machine Learning Tamil Nadu Coimbatore India Srm Institute of Science and Technology Department of Computer Applications Tamil Nadu Chennai India Panimalar Engineering College Department of Computer and Communication Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Ece Tamil Nadu Chennai India Simats Saveetha College of Liberal Arts and Sciences Department of Data Analytics Tamil Nadu Chennai India Simats Department of Biosciences Saveetha School of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350306415

Since the beginning of the seventeenth century, wheelchairs have been used to transport hospital patients and those with mobility impairments. The power of people is what spreads wheelchairs. Wheelchair users propel themselves forward using their upper bodies or, more commonly, require the assistance of another person to propel them. In this work, we examine how to build an autonomous electric wheelchair for the disabled at the lowest possible cost without sacrificing quality of design or control. This research presents the planning and development of an AI-enhanced electric wheelchair that can be controlled automatically to climb stairs, making it accessible to those with mobility impairments. The chair's controls allow the user to move it in any direction and raise the landing and staircases to varying heights. The chair's DC power source (battery used) may be recharged, allowing it to function for an extended period of time. In addition, a safety system was created that monitors and provides feedback on the user's pulse rate, as well as the wheelchair's functioning state (including acceleration, climate, and inclination position). This proposed AI based Wheelchair (AIWC) design is suitable for any aged people and the proposed model is cross-validated with the conventional wheelchair design using mobile based operations handling system called Mobile-Wheelchair (MWC) to test the efficiency of the proposed design in clear manner. © 2024 IEEE.

关键词： Accelerator AI Artificial Intelligence Batteries DC Power intelligent Sensors Mobile-Wheelchair MWC Wheelchair

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A Malmquist Index for Measuring Productivity and Efficiency of ICTs on Literacy Rate Versus Life Expectancy 1

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8th international conference on Information and Communication Technology for intelligent Systems, ICTIS 2024

作者： Maidi, Refilwe Bankole, Felix School of Computing University of South Africa Pretoria South Africa HarpDome Technologies Inc Winnipeg Canada HarpDome Technologies Inc Coronado United States

ISBN: (数字)9789819757992

ISBN: (纸本)9789819757985

The research examines whether there is a noticeable trend towards increasing Information Communication Technologies and internet access in improving the efficiency of Sub-Saharan African countries literacy rate and life expectancy. data Envelopment Analysis (DEA) was used to examine the relationship between ICTs and internet access in relation to life expectancy and literacy rate. To determine efficiency and productivity for each Sub-Saharan African countries, data Envelopment Analysis (DEA) and Malmquist Index (MI) was used. The United Nations data Bank was used to extract raw data ranging from 2010 to 2023 period. The results indicated that there is a significant relationship between ICTs and internet access to the lifespan of Sub-Saharan African countries. The summarized outcomes indicated that more research need to be conducted to create polices and frameworks to ensure that access to ICTs and internet is possible and that African countries can be on par with one another in terms of sustainable development. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： analytics data Envelopment Analysis (DEA) Information Communication Technology (ICT`s) Internet Life expectancy Literacy rate Malmquist Index (MI) Sub-Saharan African Countries

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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 ...

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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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data analytics of Restaurants using AI 9

Data Analytics of Restaurants using AI

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9th international conference on smart computing and Communications, ICSCC 2023

作者： Balakrishnan, Biju Gawali, Sakshi Tiwari, Sunny Kalsi, Shubhjeet Singh Naregal, Vishal Sies Graduate School of Technology Dept. Electronics and Telecommunication Navi Mumbai India

ISBN: (纸本)9798350314090

At present, there are 4.3 million restaurants worldwide. With such a huge number of restaurants, the level of competition between them to attract interested customers will increase, thereby affecting the sales market the most. Various surveys have shown that customers rely a lot on online reviews and ratings given by previously visited customers and then try a new restaurant or cuisine. This is because customer reviews affect the sustainability of the restaurant business. There are various websites and applications like Zomato, Trip Advisor, and similar models that focus only on customer satisfaction services, but not regarding business satisfaction services/models. If some of them still include the business side of these services, they would not give their 100 percent as customer services are much more in demand. Taking insights from these, this paper focuses mainly on the concept of reviews and ratings to create a web platform that will provide enormous options according to the expectations and needs of the business consumer/consultancy companies and help them analyze the entire restaurant market in an area based on what type of cuisine is the most tried, number of ratings and many more important parameters. This can be a successful venture between businesses and restaurants, which will help in expanding the restaurant community according to the real-time data of a particular region/area. © 2023 IEEE.

关键词： Customer satisfaction

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international IoT, Electronics and Mechatronics conference, IEMTRONICS 2024

International IoT, Electronics and Mechatronics Conference, ...

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international IoT, Electronics and Mechatronics conference, IEMTRONICS 2024

ISBN: (纸本)9789819747795

The proceedings contain 40 papers. The special focus in this conference is on IoT, Electronics and Mechatronics. The topics include: Exploring Mangrove Complexity with Gate-Based Fractal Analysis Through AND Circuitry;enhancing Paralympic Athlete Performance: Kinematic Analysis and Computer Information Systems for Optimal Training Load Adjustment;Enhancing ECG Heartbeat Signal Classification Through Multi-Step Preprocessing and Machine Learning Model Optimization;features of data Collection and Software Tool Architecture for Performing Predictive Analysis of Phenomena Leading to Forest Fires;augmenting Reliability in Speaker Recognition Systems Through Low Density Parity Check Codes;an Analytical Study of Text Summarization Techniques;MAPExeCPS: A Platform to Support the Commercial Value and Production Condition of Mud Crabs of the Genus Scylla spp. In the Philippines;ioT Guardian: An intelligent Framework for Multi-Class Intrusion Detection with Machine Learning;Development of an Approach to Analysis and Classification of EMG Signals for Prosthesis Control;high Impedance Surfaces: Unique Properties and Applications;big data analytics Approach with Multiple Text Types: The Case of the Computer Gaming;dynamic Change of Three-Dimensional Soil in Game Simulators;an Approach to Design a Cost-Effective Thermocycler for Polymerase Chain Reaction;ioT Machine Learning-Based Health Compliance Monitoring System;an IoT-Based Mobile Air Pollution Monitoring System;data Allocation and Replication Strategies in Edge computing;structure of Control computing Facilities of data Transmission Networks and Features of Dispatch Algorithm Programs;Enhancing Power Allocation in MIMO-OFDM Systems: Latest Approaches and Algorithms;supercapacitor-Based Power Supply for Embedded System Applications;an Ideal Pulsed Electromagnetic Field Device Based on a Multidimensional Model of Light.

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international IoT, Electronics and Mechatronics conference, IEMTRONICS 2024

International IoT, Electronics and Mechatronics Conference, ...

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international IoT, Electronics and Mechatronics conference, IEMTRONICS 2024

ISBN: (纸本)9789819747832

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Innovative Machine Learning Approaches to Cardiovascular Disease Prediction

Innovative Machine Learning Approaches to Cardiovascular Dis...

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2024 international conference on intelligent computing and Sustainable Innovations in Technology, IC-SIT 2024

作者： Mehedi, Mithila Nishat, Nourin Nahar, Janifer Raasetti, Muniroopesh Shoaib, A.S.M. Ali, Basharat Pabel, Md Amran Hossen Rajshahi University of Engineering and Technology Department of Electrical and Computer Engineering Rajshahi6204 Bangladesh Lamar University Department of Management Information Systems TX United States Louisiana State University Department of Finance United States Lamar University Department of Electrical Engineering TX United States Wright State University Business Analytics and Insights DaytonOH United States

ISBN: (纸本)9798350369175

Cardiovascular diseases (CVDs) are a principal factor in health issues and death throughout the world, introducing extensive challenges to healthcare systems and impacting countless lives. This paper explores the application of various machine learning models to predict and monitor CVDs, leveraging data from wearable sensors and smart health devices. We analysed models featuring Logistic Regression, Support Vector Machines (SVM), Decision Trees, Random Forests, Gradient Boosting, KNearest Neighbors, and Voting Classifiers. Our in-depth examination revealed that most models achieved remarkable accuracy, precision, recall, and F1-scores with the Voting Classifier. These models' high accuracy and straightforward implementation make them suitable for real-world clinical settings, where computational resources may be limited. By enabling early detection and continuous monitoring, these machine learning approaches can personalize healthcare, improve patient outcomes, and reduce healthcare costs. The integration of these advanced technologies promises to enhance cardiovascular disease management, providing timely interventions and better health monitoring, ultimately contributing to reduced incidence and severity of CVDs. © 2024 IEEE.

关键词： Logistic regression

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