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@article{183281,
        author = {MD. Ushama Shafoyat and Sheyeam husnain and injamamul haque niyaz and ahnaf jubaer saad and Mohummad Shariful Islam},
        title = {A Low-Cost, High-Performance AI-based Night Vision Device for Small Arms: Designed for the Armed Forces},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {3},
        pages = {2136-2150},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=183281},
        abstract = {This study presents the design and implementation of a low-cost object-detecting night vision device based on the Raspberry Pi platform for integration with small arms used by the Armed forces. The system employs an infrared (IR)-sensitive camera module, IR LEDs, and a Raspberry Pi microcomputer to enable image capture and video streaming in low-light and no-light environments. Image processing and real-time video analytics, including motion detection, object tracking, and basic recognition, are performed using Python-based libraries and OpenCV. The compact and energy-efficient configuration enhances its suitability for applications such as remote surveillance, target aiming, monitoring hostile movement, securing restricted areas, and conducting night-time reconnaissance operations. Compared to conventional night vision technologies, the proposed solution offers a lightweight, scalable, and cost-effective alternative. The use of open-source hardware and software ensures accessibility, adaptability to mission-specific requirements, and potential for further development. This work demonstrates the feasibility of employing open-source embedded platforms to create affordable and customizable night vision systems for defense, security, and tactical applications.},
        keywords = {},
        month = {August},
        }