International Journal of Innovative Research in Engineering and Management
Year: 2026, Volume: 13, Issue: 2
First page : ( 125) Last page : ( 134)
Online ISSN : 2350-0557
Khushbu Yadav
, Ekta Rai
, Alok Mishra
DOI: 10.55524/ijirem.2026.13.2.17 |
DOI URL: https://doi.org/10.55524/ijirem.2026.13.2.17
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
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Khushbu Yadav , Ekta Rai, Alok Mishra
The recent development of data-intensive applications using artificial intelligence (AI) has exposed the fundamental flaws in traditional electronic computing designs, including latency, bandwidth constraints, and excessive power consumption. A possible paradigm that blends the adaptability and experience of electronic systems with the speed, parallelism, and minimal loss of photonics is hybrid photonic–electronic structures. With a focus on AI-driven photonic design techniques, this article provides an extensive analysis of next-generation hybrid architectures intended for intelligent embedded systems. We investigate electronic–photonic co-design techniques, silicon photonic integration, photonic neural networks, and system-level designs. Additionally, the use of AI to inverse photonic optimization and design is examined. When compared to traditional systems, its performance studies show notable gains in throughput, latency, and energy economy Future research opportunities for fully scaled photonic computer ecosystems are outlined, along with challenges including integration complexity, conversion overhead, and optical nonlinearity.
M. Tech Scholar, Department of Electronics and Communication Engineering, Rameshwaram Institute of Technology & Management, Lucknow, Uttar Pradesh, India
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