https://ojs.as-pub.com/index.php/IFR/issue/feed 2024-10-15T17:11:25+08:00 Managing Editor editorial_office@as-pub.com Open Journal Systems <p><strong>ISSN: 3029-2220(Online)</strong><br>Information Fusion Research&nbsp;(IFR) is an open-access academic journal. Information fusion is a multi-level and multi-faceted process, which is to detect, combine, correlate, estimate and combine multi-source data to achieve accurate state estimation and identity estimation, as well as complete and timely situation and threat assessment. Multi-fusion technology is the hardware foundation, multi-source information is the processing object of information fusion, and coordination optimization and comprehensive processing are the core of information fusion. Technologies and applied articles related to information fusion are in line with the scope of the journal. Articles with original research and innovations are welcomed, and the types of articles include original research, review, case report, letter, short comment.</p> <p><strong>The article processing charges is $800 per article.</strong></p> https://ojs.as-pub.com/index.php/IFR/article/view/7859 Ritesh SinghKushwaha Abhilash Civi Arman Inamdar Nilambari Patil Prof. RachanaChapte

<p>This paper presents the development and evaluation of an Indoor Navigation Application leveraging Augmented Reality (AR) technology to provide accurate and intuitive navigation within complex indoor environments. The primary objective is to enhance user experience by integrating ARCore, NavMesh, and the A* algorithm to ensure precise localization and efficient pathfinding. The methodology involves creating a comprehensive 3D model of the building using Blender, with QR codes strategically placed throughout the structure to facilitate accurate user localization. Upon scanning a QR code, the system activates the user's camera and employs ARCore for simultaneous localization and mapping (SLAM), aligning the user's position with the 3D model. Real-time navigation is then provided through AR overlays, guiding users along the optimal path determined by the A* algorithm. The evaluation metrics focus on accuracy, usability, efficiency, reliability, and scalability. The system demonstrates high accuracy in positioning, minimal latency in pathfinding, and consistent performance across diverse indoor environments. User feedback indicates a high level of usability, with intuitive interactions and clear visual cues. The modular design of the system ensures scalability and adaptability to various building configurations. In conclusion, the AR indoor navigation system offers a robust solution for indoor navigation, with potential applications in commercial complexes, educational institutions, and healthcare facilities. Future work will focus on enhancing accuracy, optimizing user experience, and integrating advanced AR features and IoT devices.</p>

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