International Journal of Technology and Applied Science

E-ISSN: 2230-9004   •   Impact Factor: 9.914

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 17 Issue 5 (May 2026) Submit your research before the last 3 days of this month to publish your research paper in the current issue.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 17 Issue 5
May 2026

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Scheme Seva: An AI-Powered Government Scheme Management Portal

Author(s) Ms. Narayani Sanjay Ahire, Ms. Dnyaneshwari Harishchandra Sarode, Ms. Kajal Yuvraj Deore, Ms. Rutuja Nitin Patil, Ms. Vaishnavi Manoj Kadam, Prof. Dr. Rajendra Vasantrao Patil
Country India
Abstract The rapid expansion of central and state government welfare schemes has made it increasingly difficult for citizens to identify programs that match their eligibility, needs, and location. Many beneficiaries remain unaware of schemes relevant to them because existing portals are often fragmented, static, and difficult to navigate. To address this gap, this paper presents Scheme Seva, an AI-powered Government Scheme Management Portal designed to simplify scheme discovery through personalization, intelligent assistance, and an accessible user interface. The proposed system uses Natural Language Processing (NLP) and Machine Learning (ML) to analyze user details such as age, income, occupation, gender, and state, and then recommend suitable schemes. A conversational chatbot further assists users by explaining scheme benefits, eligibility conditions, required documents, and application steps in simple language. The portal is developed using a modern web-based architecture to support secure interaction, scalable data handling, and real-time user assistance. The system also includes an admin module for managing scheme information and monitoring user engagement. Preliminary evaluation indicates that the platform improves scheme accessibility, reduces search effort, and provides a more citizen-centric approach to digital governance. The proposed solution supports the vision of inclusive e-governance by making government benefits easier to discover and understand.
Keywords AI Chatbot, Government Scheme Recommendation, Natural Language Processing, Machine Learning, Digital Governance, Citizen-Centric Portal, Scheme Discovery, Web Application
Field Engineering
Published In Volume 17, Issue 5, May 2026
Published On 2026-05-27
View / Download PDF File

Share this



CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJTAS DOI prefix is
10.71097/IJTAS

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 15 Isu 12Cover Page Vol 15 Isu 11Cover Page Vol 15 Isu 10

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJTAS
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us Message on WhatsApp +91-9687-182-185 editor@ijtas.com