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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63771
Volume:
10 |
5 |
May 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
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.
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
With the increasing number of student queries related to admissions, fees, scholarships, and placements, educational institutions are finding it difficult to provide timely and accurate responses using conventional methods. EduMitra is an AI-powered chatbot system designed to centralize and automate information dissemination for the Department of Technical Education (DTE). The system leverages Artificial Intelligence (AI) and Natural Language Processing (NLP) using Google’s Gemini API, an advanced multimodal model capable of processing text, voice, and contextual data, to deliver accurate, real-time, and personalized responses. Built with React.js for the frontend, Spring Boot for the backend, and MySQL for structured data management, the chatbot provides categorized information, college and course recommendations, document guidance, and query history tracking. The integration of the Gemini API ensures natural, human-like conversations and intelligent understanding, thereby improving accessibility, reducing administrative workload, and enhancing user satisfaction across all DTE-affiliated institutions.
KEYWORDS
In conclusion, the EduMitra project represents a significant step toward transforming how educational institutions handle communication and information dissemination. By leveraging the advanced capabilities of the Gemini API, the system brings artificial intelligence and natural language processing into the academic domain to create an intelligent, context-aware, and efficient virtual assistant. It centralizes data from multiple DTE-affiliated colleges, ensuring that students, parents, and staff have access to accurate and updated information in real time. The chatbot automates repetitive administrative tasks, such as responding to inquiries about admissions, fees, courses, placements, and scholarships, thereby freeing up staff to focus on more critical operations. Its 24/7 availability ensures consistent support, while its NLP-driven design allows it to understand user intent, personalize responses, and maintain natural, human-like interactions. Through testing and feedback, EduMitra has shown measurable improvements in communication efficiency, response accuracy, and user satisfaction. It not only reduces manual workload and operational delays but also fosters transparency and accessibility across the Department of Technical Education. With further enhancements such as multilingual support, voice interaction, mobile integration, and predictive analytics, EduMitra has the potential to evolve into a comprehensive digital communication ecosystem for educational institutions, aligning with the broader goals of digital transformation and smart governance in India’s education sector.
[1] Chen, L., Zhang, Y., & Li, X. (2022). AI Chatbots in Education: Enhancing Student Support through NLP. International Journal of Educational Technology, 9(3), 120–130. [2] Woolf, B. (2010). Building Intelligent Interactive Tutors. Morgan Kaufmann. [3] Graesser, A., & McNamara, D. (2018). Conversational Agents in Learning Environments. Computers & Education, 164, 104–121. [4] Google AI. (2024). Gemini API Overview. https://ai.google.dev/gemini-api [5] Ministry of Education, Government of India. (2020). National Education Policy 2020. [6] Srivastava, A., & Khatri, R. (2023). AI Adoption in Public Education. Journal of Emerging Technologies in Learning, 12(1), 45–57.
Publication Date
5/23/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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