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Paper ID:IJSREM66549

ScholarSense AI: An OCR-Driven Pre-Submission Intelligence System for Government Scholarship Eligibility Assessment, Document Validation, and Multi-Portal Status Interpretation

Stream/Area:

-

Subject:

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Paper ID:

IJSREM66549

Volume:

10 |

8 |

Aug 2026

Pages:

1-9

Publication Frequency:

Monthly (12 issues per year)

DOI
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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.

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Authors

Shalini H R

Shalini H R

School of Computer Application

GM University

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VK

Varun KS

Faculty of Computing and IT

GM University

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Mentors

VK

Varun KS

Faculty of Computing and IT

GM University

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Abstract

India's National Scholarship Portal (NSP) and State Scholarship Portal (SSP) serve over 135 lakh applicants annually, disbursing ₹1825 crore in 2022-23. Despite the scale, eligible students routinely lose scholarships due to five avoidable failure modes: pre-submission document errors, Aadhaar-DBT linkage failures, cryptic portal status codes, missed deadlines, and absence of personalised guidance. We present ScholarSense AI, a web-based OCR-driven scholarship intelligence platform built on React 18, Node.js, Express, and MongoDB. The system implements five modules: a pre-submission document health check engine, a rule-based eligibility matcher for 30+ NSP/SSP schemes, a multi-portal OCR screenshot status analyzer, an automated deadline notification engine (email + WhatsApp), and a RAG-based AI chatbot. Evaluation on 30 synthetic portal screenshots demonstrates 100% portal type detection and 33.3% average status extraction accuracy at 84.9% average OCR confidence. Validation on one real SSP Karnataka screenshot confirmed correct extraction at 84.8% confidence. ScholarSense AI is the first integrated system providing pre-submission OCR intelligence for Indian government scholarship portals, requiring no government API access and deployable on standard college infrastructure.

KEYWORDS

National Scholarship Portal; OCR Document Verification; Scholarship Eligibility Matching; RAG Chatbot; Pre-Submission Intelligence; SSP Karnataka; Multi-Portal Status Analysis; Automated Deadline Notification

Cite This Article

Shalini H R, Varun KS, Varun KS, "ScholarSense AI: An OCR-Driven Pre-Submission Intelligence System for Government Scholarship Eligibility Assessment, Document Validation, and Multi-Portal Status Interpretation," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 8, pp. 1-9, Aug 2026.

Full Article/Conclusion

ScholarSense AI transforms a fragmented, opaque scholarship process into a guided, validated, and proactively monitored experience through OCR, rule-based eligibility matching, RAG-based conversational AI, and multi-channel proactive notification (email + WhatsApp). The system addresses five documented failure modes, requires no government API access, and is the first integrated platform providing pre-submission OCR intelligence for NSP, SSP, PFMS, INSPIRE, and PMSS. Future work: (1) Kannada-language output for SSP Karnataka; (2) region-of-interest OCR for improved SSP accuracy; (3) integration with Samu et al.’s Hyperledger Fabric layer; and (4) disbursement prediction modelling.

References

[1] Shillong Times, "13,719 students lose scholarships due to Aadhaar seeding issues," Apr. 2025. [2] NSP Portal, "NSP AI chatbot response," scholarships.gov.in, accessed Jan. 2025. [3] Comptroller and Auditor General of India, "Performance audit: MahaDBT scholarship schemes, Maharashtra," CAG Report No. 6, 2023. [4] L.C. Samu et al., "Blockchain based intelligent disbursement of scholarships via NSP," IET Blockchain, vol. 4, no. 1, pp. 34–47, 2024. [5] P. Bedi et al., "Smart contract based central sector scheme of scholarship for college and university students," Procedia Computer Science, vol. 171, pp. 790–799, 2020. [6] S. Jadhav, N. Pise, P. Karwa, "Scholar block: blockchain-based CSR scholarship management," in Proc. IEEE ICCI, 2023. [7] R. Smith, "An overview of the Tesseract OCR engine," in Proc. ICDAR, vol. 2, pp. 629–633, 2007. [8] A. Sharma, P. Gupta, "OCR-based educational document processing for Indian board marksheets," Int. J. Comput. Appl., vol. 175, no. 12, 2020. [9] M. Bhatt, S. Desai, "E-governance usability barriers in rural India," Digital Policy, Regulation and Governance, vol. 22, no. 4, 2020. [10] UIDAI, "Aadhaar for direct benefit transfer," uidai.gov.in, 2024.

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Publication Date

8/6/2026

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Double-Blind Peer Review

Review Rounds: 2

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