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Record Nr. |
UNINA9911004815803321 |
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Autore |
Raj Pethuru |
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Titolo |
Streaming Analytics : Concepts, Architectures, Platforms, Use Cases and Applications |
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Pubbl/distr/stampa |
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Piraí : , : Institution of Engineering & Technology, , 2022 |
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©2022 |
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ISBN |
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9781523153381 |
1523153385 |
9781839534171 |
1839534176 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (625 pages) |
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Collana |
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Altri autori (Persone) |
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SurianarayananChellammal |
SeeranganKoteeswaran |
GhineaGeorge |
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Disciplina |
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Soggetti |
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Real-time data processing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Chapter 1: Streaming data processing - an introductionChapter 2: Event processing platforms and streaming databases for event-driven enterprisesChapter 3: A survey on supervised and unsupervised algorithmic techniques to handle streaming Big DataChapter 4: Sentiment analysis on streaming data using parallel computingChapter 5: Fog and edge computing paradigms for emergency vehicle movement in smart cityChapter 6: Real-time stream processing on IoT data for real-world use casesChapter 7: Rapid response system for road accidents using streaming sensor data analyticsChapter 8: Applying streaming analytics methods on edge and fog device clustersChapter 9: Delineating IoT streaming analyticsChapter 10: Describing the IoT data analytics methods and platformsChapter 11: Detection of anomaly over streams using isolation forestChapter 12: Detection of anomaly over streams using big data technologiesChapter 13: Scalable and real-time prediction on streaming data - the role of Kafka and streaming frameworksChapter 14: Object detection techniques for real-time applicationsChapter 15: EdgeIoTics: leveraging |
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edge cloud computing and IoT for intelligent monitoring of logistics container volumesChapter 16: A hybrid streaming analytic model for detection and classification of malware using Artificial Intelligence techniquesChapter 17: Performing streaming analytics on tweets (text and images) dataChapter 18: Machine learning (ML) on the Internet of Things (IoT) streaming data toward real-time insights. |
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Sommario/riassunto |
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In this book, the authors articulate the challenges associated with streaming data and analytics, describe data analytics algorithms and approaches, present edge and fog computing concepts and technologies and show how streaming analytics can be accomplished in edge device clouds. They also delineate several industry use cases. |
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