ARTIFICIAL INTELLIGENCE ANALYSIS OF BIG DATA COLLECTED THROUGH IOT DEVICES
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Keywords: Analysis of IoT Big Data pandas, scikit-learn, TensorFlow, Anomaly Detection, Autoencoders , PySpark.Аннотация
Abstract: The Internet of Things (IoT) has revolutionized data collection by enabling billions of interconnected devices to generate vast amounts of data, often referred to as big data. These devices, ranging from smart sensors in industrial systems to wearable health monitors, produce high-volume, high-velocity, and high-variety data that require advanced analytical techniques for meaningful insights. Artificial Intelligence (AI), with its capabilities in machine learning (ML), deep learning (DL), and predictive analytics, is uniquely suited to process and analyze IoT-generated big data. This article explores the fundamentals of AI-driven analysis of big data from IoT devices, addressing methods, challenges, solutions, and mathematical formulations to quantify performance and efficiency.
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