IoT and Machine Learning Approaches for Supply Chain Optimization in Industry 4.0 Logistics

Abstract

Explores IoT and machine learning approaches for optimizing supply chain operations in Industry 4.0 logistics environments.

This work intersects with research areas including IoT, machine learning, supply chain, Industry 4.0, logistics, optimization, and smart manufacturing. It is part of the broader research portfolio of Nitiraj V. Kulkarni in the domain of peer-reviewed academic publishing.

Keywords & Topics

IoT, machine learning, supply chain, Industry 4.0, logistics, optimization, smart manufacturing

How to Cite

APA

Nitiraj V. Kulkarni et al. (2026). IoT and Machine Learning Approaches for Supply Chain Optimization in Industry 4.0 Logistics. International Conference on Sustainable Innovation with AI and ML, Pages 990–1004, Atlantis Press. Atlantis Press.

IEEE

Nitiraj V. Kulkarni et al., "IoT and Machine Learning Approaches for Supply Chain Optimization in Industry 4.0 Logistics," International Conference on Sustainable Innovation with AI and ML, Pages 990–1004, Atlantis Press, 2026.

BibTeX

@article{2026_iot_ml_supply_chain_industry4,
  title={IoT and Machine Learning Approaches for Supply Chain Optimization in Industry 4.0 Logistics},
  author={Nitiraj V. Kulkarni et al.},
  journal={International Conference on Sustainable Innovation with AI and ML},
  year={2026},
  publisher={Atlantis Press}
}

Identifiers & Links

Last updated: 2026-01-01

About the Author

Nitiraj V. Kulkarni is an AI safety and cybersecurity researcher based in Pune, India, with 35+ peer-reviewed publications, 5 patents, 6 copyright registrations, and 15,000+ open datasets published on Kaggle and Zenodo. He serves as a peer reviewer for 11+ international journals and conferences. Read full profile.