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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM61889
Volume:
10 |
4 |
April 2026
Pages:
1-8
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 & Engineering
Government College of Engineering, Chandrapur
Department of Computer Science & Engineering
Government College of Engineering, Chandrapur
Department of Computer Science & Engineering
Government College of Engineering, Chandrapur
Department of Computer Science & Engineering
Government College of Engineering, Chandrapur
Department of Computer Science & Engineering
Government College of Engineering, Chandrapur
Department of Computer Science & Engineering
Government College of Engineering, Chandrapur
Department of Computer Science & Engineering
Government College of Engineering, Chandrapur
Department of Computer Science & Engineering
Government College of Engineering, Chandrapur
Smart Accommodation is a web-based intelligent housing recommendation system designed to assist students in finding suitable rental accommodations efficiently. The system addresses common challenges such as unorganized listings, lack of transparency, and difficulty in comparing options by providing a centralized platform with smart filtering and recommendations. It integrates real-time accommodation data, geospatial analysis, and a recommendation algorithm to suggest personalized housing options based on user preferences like budget, distance from university, safety, and amenities. The system is developed using modern web technologies with a scalable backend and database support. The experimental results show improved recommendation accuracy, fast response time, and high user satisfaction. The platform significantly reduces the time required for manual searching and enhances decision-making for students. Overall, the system provides a reliable, efficient, and user-friendly solution for student accommodation, making the search process smarter and more effective.
KEYWORDS
The project “ Smart Accommodation for Students” successfully addresses one of the most common and challenging problems faced by students—finding suitable accommodation in a new city. With the rapid growth of student migration for education, especially in non-metro cities, traditional methods such as brokers, word-of-mouth references, and manual searching have proven to be inefficient, time-consuming, and often unreliable. This project provides a modern, technology-driven solution that simplifies and enhances the entire accommodation search process. The system introduces a centralized digital platform where students can easily search, filter, and explore accommodation options based on their preferences such as location, budget, and available amenities. By leveraging technologies like React JS for frontend, Java Spring Boot for backend, and PostgreSQL for database management, the platform ensures a smooth, responsive, and efficient user experience. The integration of Cloudinary for media storage further enhances the system by enabling fast and secure handling of property images, making listings more informative and visually appealing. One of the key strengths of the system is its user-centric design, which focuses on simplicity, accessibility, and usability. The separation of modules into Student, Owner, and Admin ensures that each user type can interact with the system efficiently according to their needs. Students benefit from advanced search filters and transparent information, property owners gain better visibility and management tools for their listings, and administrators can monitor and maintain the overall system integrity. The inclusion of a feedback and rating system plays a crucial role in improving transparency and building trust among users. It allows students to make informed decisions based on real experiences shared by others, thereby reducing the chances of fraud and dissatisfaction. Additionally, the integration of AI-based features such as face recognition using Python enhances the security of the platform by verifying user identities and minimizing fake registrations. The system architecture, based on a three-tier design, ensures scalability and flexibility, allowing the platform to expand in the future to support more users and locations. Cloud integration enables remote access and efficient data handling, making the system available anytime and anywhere, which is essential for today’s digital environment. Through proper testing and debugging, the application has been optimized to deliver stable performance with minimal errors. The deployment of the system ensures that it can be accessed through standard web browsers, making it convenient for users without requiring specialized software. Overall, the system significantly reduces the time, effort, and complexity involved in finding student accommodation. It transforms a traditionally manual and uncertain process into a structured, transparent, and efficient digital experience. The project not only benefits students but also provides value to property owners by connecting them directly with potential tenants.
[1] L. Magambo, M. A. Dida, and S. F. Kaijage, “Towards an Online Portal for Locating Students’ Private Rental Accommodation in Tanzania,” 2020. https://dspace.nm-aist.ac.tz/server/api/core/bitstreams/bbda4cb5-683d-46c9-a2c4-6d48689f509e/content [2] S. Matkari, R. Kumbhar, S. Suryawanshi, and S. Ambavade, “Room Finder Application for Students,” 2024. https://d1wqtxts1xzle7.cloudfront.net/122032267/ROOM_FINDER_APPLICATION_FOR_STUDENTS-libre.pdf [3] School of Computer Science and Engineering, Sandip University, “Web-Based Paying Guest Accommodation System,” 2023 https://drive.google.com/file/d/12mPKqTufAF6RXea4qhOQbHzJbs5T8eY [4] C. T. Chye, S. A. Mubin, and N. K. Zainal, “APResidence: Development of Online Student Accommodation Management System for Asia Pacific University,” 2023 https://www.researchgate.net/publication/378405727 [5] J. F. De Paz Santana, “Smart Housing Recommender System, Timisoara, Romania,” 2024..https://drive.google.com/file/d/1LOWBrySduu3j_3Nm2_TuGtkGkybG2M-9
Publication Date
4/30/2026
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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