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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64060
Volume:
10 |
5 |
May 2026
Pages:
1-4
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.
Master's of Computer Applications
Bapuji Institute Of f Engineering And Technology
Master's of Computer Applications
Bapuji Institute Of f Engineering And Technology
The Internship / Industrial Training with Placement Opportunity project is a web-based platform designed to simplify and automate the internship and placement process for students, companies, and universities. The existing system relies on manual methods such as emails, notice boards, and spreadsheets, which leads to inefficiency and lack of transparency. This system provides a centralized platform where students can create profiles, search verified internship opportunities, apply online, and track application status. Companies can post internships, shortlist candidates, and provide feedback, while Training and Placement Officers (TPOs) can verify students and monitor placement activities. The platform improves efficiency, transparency, and communication, helping students transition smoothly from academics to professional careers.
KEYWORDS
This project presented a web-based Internship and Industrial Training with Placement . Opportunity platform designed to simplify and automate the internship and placement process. The proposed system successfully integrates students, recruiters, and Training and Placement Officers (TPOs) into a centralized environment. By replacing manual methods such as emails and spreadsheets, the system improves transparency, reduces administrative workload, and enables real-time application tracking. The verification mechanism ensures authenticity of student profiles and company postings. Overall, the platform effectively bridges the gap between academia and industry and enhances student employability. The system can be further enhanced by incorporating advanced features such as: AI-based internship and job recommendation system Mobile application support for better accessibility Advanced analytics for placement prediction and performance tracking Support for virtual and remote internships Integration with external job portals and learning platforms
1. Sharma, P., & Verma, R. (2018). A Study on the Effectiveness of Industrial Training Programs in Enhancing Employability Skills. International Journal of Management and Applied Science, 4(6), 12–15. 2. Kumar, S., & Gupta, N. (2019). Role of Internship Programs in Bridging the Gap between Academia and Industry. International Journal of Engineering and Advanced Technology (IJEAT), 8(6S3), 110–114. 3. Patel, A., & Joshi, K. (2020). Data-Driven Approach for Managing Industrial Internship and Placement Opportunities. International Journal of Computer Applications, 176(25),22–28. 4. Rao, V., & Singh, M. (2021).Developing a Web-Based Platform for Industrial Training and Placement Management. International Journal of Emerging Technologies in Learning (iJET), 16(10), 45–52. 5. Das, S., & Banerjee, A. (2020). Machine Learning Techniques for Predicting Student Placement Outcomes. International Journal of Innovative Research in Computer and Communication Engineering, 8(9), 6201–6208. 6. Ali, H., & Khan, R. (2021). A Framework for Automating Industrial Internship Allocation Using Web Technologies. International Journal of Advanced Research in Computer Science, 12(3), 78–84. 7. Thomas, L., & George, S. (2019). Analysis of Internship Programs for Skill Development and Employability. Journal of Education and Practice, 10(4), 55–61. 8. Singh, D., & Kaur, P. (2022). Integration of Industry 4.0 Skills into Academic Internship Training Systems. Journal of Technical Education and Training, 14(2), 32–40. 9. Reddy, P., & Nair, A. (2023). Design and Implementation of a Placement Prediction System Using Data Analytics. International Journal of Scientific & Engineering Research, 14(1), 91–96. 10. Gupta, S., & Mehta, R. (2021). Smart Internship and Placement Management System Using Cloud-Based Technologies. International Journal of Computer Science and Information Technology, 13(5), 210–216.
Publication Date
5/26/2026
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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