A
Anand Paul
Researcher at Kyungpook National University
Publications - 253
Citations - 5923
Anand Paul is an academic researcher from Kyungpook National University. The author has contributed to research in topics: Big data & The Internet. The author has an hindex of 32, co-authored 233 publications receiving 4205 citations. Previous affiliations of Anand Paul include Hanyang University & National Cheng Kung University.
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Urban planning and building smart cities based on the Internet of Things using Big Data analytics
TL;DR: A combined IoT-based system for smart city development and urban planning using Big Data analytics, consisting of various types of sensor deployment, including smart home sensors, vehicular networking, weather and water sensors, smart parking sensors, and surveillance objects is proposed.
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Exploiting IoT and big data analytics: Defining Smart Digital City using real-time urban data
TL;DR: This paper has established an IoT-based Smart City by using Big Data analytics while harvesting real-time data from the city by using existing smart systems and IoT devices as city data sources to develop the Smart Digital City.
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Smartbuddy: defining human behaviors using big data analytics in social internet of things
TL;DR: This work presents a new concept of SmartBuddy that focuses on the analysis, the ecosystem provided by smart cities, wearable devices, and big data to determine human behaviors as well as human dynamics.
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ECG Signal Preprocessing and SVM Classifier-Based Abnormality Detection in Remote Healthcare Applications
TL;DR: Results indicate that the performance of SVM classifier is better than other machine learning-based classifiers on noise removed feature extracted signal for beat classification.
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Real-Time Big Data Analytical Architecture for Remote Sensing Application
TL;DR: The proposed architecture results in efficiently analyzing real-time remote sensing Big Data using earth observatory system using Hadoop, and has the capability of storing incoming raw data to perform offline analysis on largely stored dumps, when required.