Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREMWP49316

Smart supply chain logistics: Integrating AI, IoT, and Big Data for optimized inventory management and demand forecasting

Stream/Area:

-

Subject:

-

Paper ID:

IJSREMWP49316

Volume:

9 |

5 |

May 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Share this article:

Authors

SK

Sunny Kumar

DAKS

Dr. Ashish Kumar Singh

Author Services & Downloads

Full Articles

Abstract

Due to the rise of artificial intelligence, the Internet of Things and big data, supply chain logistics are currently experiencing a major shift. Commonly used supply chain strategies depend on reacting to problems which can lead to inefficiencies, delays and inadequate inventory. This research seeks to understand how combining AI, IoT and Big Data can transform the way supply chain logistics are handled by allowing current visibility, precise forecasts and flexible inventory handling. The researchers analyze secondary sources, including industry reports, scholarly articles and case studies of main companies that have put these technologies to work in their logistics systems. According to the findings, artificial intelligence helps companies use predictive analytics to more reliably rely on sales predictions and arrange inventory restocking more efficiently. Assets, the environment and communication across supply chain nodes can be easily monitored in real time because of IoT. With Big Data analytics, companies can process and study a lot of information to find useful information, catch unusual changes and guide their choices. Because these technologies work together, there is a major boost in the agility, resilience and efficiency of supply chains. Benefits noted are fewer stockouts and overloads, saving on business operations, faster handling of market changes and better satisfaction among clients. Still, the study discusses issues such as high budget requirements, problems in bringing together information, potential security threats and the shortage of qualified staff. The result of this paper suggests that adopting smart supply chain technologies works best when there is a clear plan in place that includes preparing the infrastructure, setting up policies for using data and working together. Those organizations that meet this change achieve better competitiveness and secure stronger, flexible supply chains able to succeed in today’s market.

KEYWORDS

Smart Supply Chain Artificial Intelligence (AI) Internet of Things (IoT) Big Data Analytics

Cite This Article

Sunny Kumar, Dr. Ashish Kumar Singh, "Smart supply chain logistics: Integrating AI, IoT, and Big Data for optimized inventory management and demand forecasting," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 5, May 2025.

Full Article/Conclusion

References

Editorial & Review Transparency

Publication Date

5/31/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

2

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

The authors declare no conflict of interest related to this research work.

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...