Artificial Intelligence System based Embedded Real-Time System Power Optimization and Adaptability

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Ganesan, Nilamani and Muthumanickam, T. (2022) Artificial Intelligence System based Embedded Real-Time System Power Optimization and Adaptability. In: UNSPECIFIED.

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Abstract

This research investigates power consumption optimization in embedded systems. Challenges in CMOS power consumption and real-time load characteristics are analyzed. Techniques including DMP, DVS/DFS, AVS, and ABB are explored, along with feedback organization and adaptability issues. The study provides insights for improving embedded system energy efficiency in real-time applications. © 2023 Elsevier B.V., All rights reserved.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Science > Artificial Intelligence
Computer Science > Information Systems and Management
Computer Science > Signal Processing
Energy > Energy
Engineering > Control and Optimization
Medicine > Health Informatics
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 02 Dec 2025 09:25
URI: https://ir.vmrfdu.edu.in/id/eprint/2885

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