Citation :

S. Parthasarathy, Vipinayan P R K, Aravindh Nk, Suriya Vijay M B, Sabarigrivasan J B, Gowind B M, R. Thangasankaran, "BORROW BOOKSY: An AI Powered Community Based Book Sharing Application," International Journal of Computer & Organization Trends (IJCOT), vol. 16, no. 1, pp. 1-7, 2026. Crossref, https://doi.org/10.14445/22492593/IJCOT-V16I1P301

Abstract

Access to physical books within residential communities and small-scale libraries is often constrained by manual coordination, fragmented record maintenance, and limited digital visibility. This paper presents BORROW BOOKSY, a community-based mobile application designed to support peer-to-peer book sharing among residents of gated communities while simultaneously providing digital access to library-maintained book records. The system enables users to list owned books, browse community and library collections, and directly coordinate borrowing through a monitored workflow. Administrative oversight is enforced through a two-level structure consisting of a system-level super administrator and community-level managerial administrators. Additionally, AI-assisted book scanning is integrated to extract bibliographic metadata and assist in the preliminary identification of potentially sensitive content during book uploads. The application was pilot tested under a controlled environment as part of an Industrial Research Park (IRP) initiative, demonstrating improved accessibility, transparency, and efficiency in community-based book sharing and library information access.

Keywords

Community Book Sharing, Digital Library Access, Flutter, Firebase, Cloudinary, AI-Assisted Book Scanning.

References

[1] Jay Nanavati et al., “Critical Review and Fine-Tuning Performance of Flutter Applications,” 5^th International Conference on Mobile Computing and Sustainable Informatics, Lalitpur, Nepal, pp. 838-841, 2024.
[CrossRef] [Google Scholar] [Publisher Link]

[2] Zhangu Wang et al., “A Review of Vehicle Detection Techniques for Intelligent Vehicles,” IEEE Transactions on Neural Networks and Learning Systems, vol. 34, no. 8, pp. 3811-3831, 2023.
[CrossRef] [Google Scholar] [Publisher Link]

[3] Md. Shamsujjoha et al., “Developing Mobile Applications via Model Driven Development: A Systematic Literature Review,” Information and Software Technology, vol. 140, 2021.
[CrossRef] [Google Scholar] [Publisher Link]

[4] Ankatwar Gajanan, and Salma Mizna, “Exploring the Mobile App Ecosystem: From Native to Progressive Web Apps and Beyond,” International Advanced Research Journal in Science, Engineering and Technology, vol. 12, no. 5, pp. 453-467, 2025.
[CrossRef] [Publisher Link]

[5] Xiaoshuo Jia, and Zhihui Li, “Research on the Reform of Project based Teaching in Mobile Android Development,” International Journal of Education and Humanities, vol. 21, pp. 285-287, 2025.
[CrossRef] [Publisher Link]

[6] A.V. Sheshadri, and M.N. Sandeep “Android Operating System: Architecture, Application Development, and Emerging Trends,” International Journal of Emerging Technologies and Innovative Research, vol. 7, no. 3, pp. 895-897, 2020.
[Publisher Link]

[7] Mona Erfani Joorabchi, Ali Mesbah, and Philippe Kruchten, “Real Challenges in Mobile App Development,” ACM / IEEE International Symposium on Empirical Software Engineering and Measurement, Baltimore, MD, USA, pp. 15-24, 2013.
[CrossRef] [Google Scholar] [Publisher Link]

[8] Maximilian Schrapel, Thilo Schulz, and Michael Rohs, “Augmenting Public Bookcases to Support Book Sharing,” 22^nd International Conference on Human-Computer Interaction with Mobile Devices and Services, Association for Computing Machinery, pp. 1-11, 2020. 
[CrossRef] [Google Scholar] [Publisher Link]

[9] Sze Chee Koh, “Mobile App for Book Sharing,” Final Year Project, Nanyang Technological University, Singapore, 2022.
[Publisher Link]

[10] Agustan Latif et al., “Book-Share (BS) Apps using the Android System,” IOP Conference Series: Materials Science and Engineering, Makassar, Indonesia, pp. 1-8, 2021.
[CrossRef] [Google Scholar] [Publisher Link]

[11] Md. Jakaria Masud et al., “The Design of an Android-Based Mobile Application for Book Sharing,” Diverse Journal of Computer and Information Sciences, vol. 2, no. 2, pp. 10-14, 2020.
[Google Scholar] [Publisher Link]

[12] Lizeth Ghandi et al., “Mobile Application Development Process: A Practical Experience,” 12^th Iberian Conference on Information Systems and Technologies, Lisbon, Portugal, pp. 1-6, 2017.
[CrossRef] [Google Scholar] [Publisher Link]

[13] Shady Boukhary, and Eduardo Colmenares, “A Clean Approach to Flutter Development through the Flutter Clean Architecture Package,” International Conference on Computational Science and Computational Intelligence, Las Vegas, NV, USA, pp. 1115-1120, 2019.
[CrossRef] [Google Scholar] [Publisher Link]

[14] Swati Sharma et al., “Hybrid Development in Flutter and its Widgits,” International Conference on Cyber Resilience, Dubai, United Arab Emirates, pp. 1-4, 2022.
[CrossRef] [Google Scholar] [Publisher Link]

[15] Shreya A. Bhagat et al., “Review on Mobile Application Development Based on Flutter Platform,” International Journal for Research in Applied Science and Engineering Technology, vol. 10, no. 1, pp. 803-809, 2022.
[CrossRef] [Google Scholar] [Publisher Link]

[16] Guikao Yang, Guangming Fan, and Fengyu Zhou, “Infrared Image Processing System Based on AI and Convolutional Neural Network,” International Conference on Computers, Information Processing and Advanced Education, Ottawa, ON, Canada, pp. 229-234, 2023.
[CrossRef] [Google Scholar] [Publisher Link]

[17] Y.A.L. Alsabahi, Lei Fan, and Xiaoyi Feng, “Image Classification Method in DR Image Based on Transfer Learning,” Eighth International Conference on Image Processing Theory, Tools and Applications, Xi'an, China, pp. 1-4, 2018.
[CrossRef] [Google Scholar] [Publisher Link]

[18] C.S. Manigandaa et al., “Apparel Production Paradigms through a Technological Tapestry of AI Driven Smart Mannequin Automation and Image Processing Precision,” International Conference on Smart Technologies for Sustainable Development Goals, Chennai, Tamil Nadu, India, pp. 1-4, 2024.
[CrossRef] [Google Scholar] [Publisher Link]

[19] Kuthati Shreya et al., “Enhancing Cervical Cancer Diagnosis: Deep Learning and Explainable AI in Multiclass Image Classification,” First International Conference for Women in Computing, Pune, India, pp. 1-6, 2024.
[CrossRef] [Google Scholar] [Publisher Link]