• Login
    View Item 
    •   Mak UD Home
    • College of Computing and Information Sciences (CoCIS)
    • School of Computing and Informatics Technology (CIT)
    • School of Computing and Informatics Technology Collection
    • View Item
    •   Mak UD Home
    • College of Computing and Information Sciences (CoCIS)
    • School of Computing and Informatics Technology (CIT)
    • School of Computing and Informatics Technology Collection
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    The Automated Security System (MuseSafe) to safeguard the valuable artifacts housed within the museum, monitor and safeguard museums

    Thumbnail
    View/Open
    Undergraduate Project Report (1.535Mb)
    Date
    2024
    Author
    Ankunda, Andante Rutainama
    Ayesiga, Nobert
    Takuwa, Suzan
    Nahurira, Clintonie
    Metadata
    Show full item record
    Abstract
    This project report details the development and implementation of an automated security system designed specifically for museums, aimed at enhancing the protection of valuable artifacts and exhibits. The motivation for this project stems from the increasing need for advanced security measures in cultural institutions, which house irreplaceable items of historical significance. The system utilizes a combination of state-of-the-art technologies, including infrared sensors, motion detectors, and an integrated surveillance system that employs artificial intelligence for real-time threat detection and analysis. The design process involved a thorough analysis of the museum's layout and specific security needs to ensure comprehensive coverage and functionality. Implementation was carried out in phases, beginning with the installation of hardware components, followed by software development and system integration. The system was tested extensively in a controlled environment to refine its detection algorithms and user interface. In conclusion, the automated security system represents a significant advancement in the protection of cultural assets. It offers museums a scalable, efficient, and cost-effective solution that can be adapted to different environments and needs. Future work will focus on enhancing the system’s machine learning algorithms and expanding its capabilities to include facial recognition and anomaly detection for even greater security.
    URI
    http://hdl.handle.net/20.500.12281/19144
    Collections
    • School of Computing and Informatics Technology Collection

    DSpace 5.8 copyright © Makerere University 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of Mak UDCommunities & CollectionsTitlesAuthorsBy AdvisorBy Issue DateSubjectsBy TypeThis CollectionTitlesAuthorsBy AdvisorBy Issue DateSubjectsBy Type

    My Account

    LoginRegister

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    DSpace 5.8 copyright © Makerere University 
    Contact Us | Send Feedback
    Theme by 
    Atmire NV