International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | InObFind-AR: An Augmented Reality Based Indoor Object Finding System |
|---|---|
| ABSTRACT | Indoor object finding is a challenging task in homes, offices, and schools due to complex layouts, cluttered environments, and the absence of GPS support. Users often spend considerable time searching for objects manually, which is inefficient and inconvenient. To address this problem, this paper presents InObFind-AR, an augmented reality based indoor object finding system that provides real-time visual guidance to help users locate items easily. The system captures live camera input from the user’s device and processes it using an object detection model to recognize indoor objects. Once an object is detected, augmented reality overlays such as labels, markers, and navigation cues are displayed directly on the screen, allowing users to visually locate items without relying on external infrastructure. The system follows a modular architecture consisting of frontend interaction, backend processing, machine learning inference, and AR visualization layers, ensuring scalability and ease of maintenance. Experimental evaluation conducted in indoor environments with common objects demonstrated that the system accurately detects objects and provides real-time guidance with minimal delay. The integration of augmented reality significantly reduces search time and enhances user experience, making InObFind-AR a reliable and practical solution for intelligent indoor assistance, with potential for future enhancements such as indoor mapping and wearable AR integration. |
| AUTHOR | V. PRASHANTHI, T. PRADEEP, K. VISHNU Student, Department of Computer Applications, Sri Ramakrishna College of Arts and Science, Coimbatore, India Assistant Professor, Department of Computer Applications, Sri Ramakrishna College of Arts & Science, Coimbatore, India |
| VOLUME | 181 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1402041 |
| pdf/41_InObFind-AR An Augmented Reality Based Indoor Object Finding System.pdf | |
| KEYWORDS | |
| References | [1] Azuma, R. T., 1997, A Survey of Augmented Reality, Presence: Teleoperators and Virtual Environments, Vol. 6, Issue 4, pp. 355–385, https://doi.org/10.1162/pres.1997.6.4.355 [2] Redmon, J.; Farhadi, A., 2018, YOLOv3: An Incremental Improvement, arXiv Preprint, arXiv:1804.02767, https://arxiv.org/abs/1804.02767 [3] Szeliski, R., 2011, Computer Vision: Algorithms and Applications, Springer, New York, USA. [4] Billinghurst, M.; Clark, A.; Lee, G., 2015, A Survey of Augmented Reality, Foundations and Trends in Human–Computer Interaction, Vol. 8, Issue 2–3, pp. 73–272. |
