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Titlebook: IoT Edge Intelligence; Souvik Pal,Claudio Savaglio,Flávia C. Delicato Book 2024 The Editor(s) (if applicable) and The Author(s), under exc

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Unsupervised Time Series Anomaly Detection for Edge Computing Applications: A Reviewection to achieve long-term reliability for time series. This chapter concludes with a discussion of challenges and promising future research directions targeting long-term sensor data anomaly detection.
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Secure, Trusted, Privacy-Protected Data Exchange in an Edge-Cloud Continuum Environmenting concept to facilitate the implementation of digital continuity across Data Spaces, AI/ML/Data pipelines, Digital Twins workflows and digital threads. This chapter will provide an overview of the state of the art on strategies for Digital 4.0 Continuum. Finally, the Horizon Europe RE4DY project a
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Secure Neural Network Inference for Edge Intelligence: Implications of Bandwidth and Energy Constraitraditional security solutions might fail in an IoT setup. In recent years, several cryptographic protocols have been devised for secure neural network inference (SNNI). Secure neural network inference entails the problem of computing the output of a neural network on the client’s input without reve
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Internet of Things in Intelligent Transportation Systemsunicate and share data with other objects, devices, and systems over the Internet. This chapter will examine the function of IoT in ITS. The initial segment will consist of an overview of the IoT platform. The introduction of ITS will follow thereafter. Subsequently, the role of IoT in ITS will be e
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IoT-Driven Analytics and Edge Intelligence in Autonomous Navigation Systemsresearch and application of these technologies. We adopted the Systematic Literature Review (SLR). Forty-eight publications were selected from relevant repositories based on suitable predefined criteria. Findings show that the integration of meaningful analytics into ANS with edge computing capacity
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Edge-AI for Monitoring Air Pollution from Urban Waste Incineration: A Surveyration raises several constraints and challenges. This chapter aims to address existing concerns by reviewing former works on Edge-AI-based urban waste incineration pollution, focusing on the most recent trends and challenges.
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