Integrating Artificial Intelligence and Machine Learning Across IT Domains: Advances in Networking, Security, Finance, IoT, and Energy Systems

Artificial intelligence and machine learning (AI/ML) are reshaping IT infras tructure by enabling intelligent solutions across networking and IoT domains. This paper investigates the application of deep learning for optimizing high traffic network routing [1] and explores machine learning-driven cost optimization strategies in IoT ecosystems [2]. Through comparative analysis, we highlight how these AI/ML approaches deliver significant improvements in performance and operational efficiency. Our findings are contextualized within the broader land scape of AI research, drawing on recent advances in deep learning architectures and their real-world deployments. The study demonstrates that integrating state of-the-art neural networks and predictive analytics can yield up to 30% gains in resource utilization and cost savings. This work offers actionable insights for practitioners aiming to leverage AI/ML for scalable, efficient, and adaptive IT systems.

Authors

Publication Details

Journal
Journal of Emerging Technologies and Innovative Research
Published
2025-01-01
DOI
https://doi.org/10.56975/jetir.v12i5.563233
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrating Artificial Intelligence and Machine Learning Across IT Domains: Advances in Networking, Security, Finance, IoT, and Energy Systems

Arun Kumar Yadav, Neetesh Saxena, Navjot Singh Talwandi, Shubneet Shubneet
Journal of Emerging Technologies and Innovative Research
Blockchain Technology Applications and Security
article

Integrating Artificial Intelligence and Machine Learning Across IT Domains: Advances in Networking, Security, Finance, IoT, and Energy Systems

Arun Kumar Yadav, Neetesh Saxena, Navjot Singh Talwandi, Shubneet Shubneet
article en

Abstract

Artificial intelligence and machine learning (AI/ML) are reshaping IT infras tructure by enabling intelligent solutions across networking and IoT domains. This paper investigates the application of deep learning for optimizing high traffic network routing [1] and explores machine learning-driven cost optimization strategies in IoT ecosystems [2]. Through comparative analysis, we highlight how these AI/ML approaches deliver significant improvements in performance and operational efficiency. Our findings are contextualized within the broader land scape of AI research, drawing on recent advances in deep learning architectures and their real-world deployments. The study demonstrates that integrating state of-the-art neural networks and predictive analytics can yield up to 30% gains in resource utilization and cost savings. This work offers actionable insights for practitioners aiming to leverage AI/ML for scalable, efficient, and adaptive IT systems.

Journal of Emerging Technologies and Innovative ResearchVol. 12(5)
Affordable and clean energy
Openalex Percentile: Top 84%
Blockchain Technology Applications and Security
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Integrating Artificial Intelligence and Machine Learning Across IT Domains: Advances in Networking, Security, Finance, IoT, and Energy Systems — Arun Kumar Yadav, Neetesh Saxena, et al. · Journal of Emerging Technologies and Innovative Research (2025) | TGRS Research Map | TGRS