Optimized VLSI Architectures For AI-Enabled IoT Systems

Author(s)	Bushra Fatima Masih, Mohammed Nomaan
Country	India
Abstract	The integration of AI in IoT has revolutionized industries through the development of intelligent decision-making and automation. However, the deployment of AI is limited by the power, computational capacity, and cost of IoT devices. VLSI architectures help to meet these challenges through compact, low power consumption, and high-performance hardware solutions. This paper focuses on the advancements in VLSI architectures for AI in IoT, low-power design techniques, hardware accelerators, neuromorphic computing, and approximate computing. The challenges, design considerations, and future trends are discussed to present a comprehensive understanding of how VLSI enables efficient and intelligent IoT systems.
Keywords	VLSI Architectures, Artificial Intelligence (AI), Internet of Things (IoT), Low-Power Design, Hardware Accelerators, Application-Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), Neuromorphic Computing, Approximate Computing, Edge AI, Low Power Design Techniques.
Field	Engineering
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-12-31
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.34539
Short DOI	https://doi.org/g82gdx

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research