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

Dimensions

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

Full text not available from this repository.

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 > Hardware and Architecture
Divisions: Engineering and Technology > Vinayaka Mission's Kirupananda Variyar Engineering College, Salem > Electrical & Electronics Engineering
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 02 Dec 2025 09:25
URI: https://vmuir.mosys.org/id/eprint/2885

Actions (login required)

View Item
View Item