Video management system
Khafif, Yahya (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024120432869
https://urn.fi/URN:NBN:fi:amk-2024120432869
Tiivistelmä
The main goal of this thesis is to address the limitations of Agnet application when it comes to users’ licenses, to overcome this constraint, a video management system will be created to serve as an intermediary between Agnet and live video streams. This web application will enable Agnet users to manage multiple video streams within the application, without the need of creating new users for external video sources and hence eliminating unnecessary user creation.
The solution proposed will also incorporate an advanced artificial intelligence model for human movement detection. This AI enhancement aims to automate video stream monitoring, thereby improving real time safety measures, this tool will send immediate alerts and provide recorded evidence for subsequent investigations.
The video management system web application will be developed using modern development tools including React.js, Node.js, Python, and leverage Agnet’s SmarTWISP API for alert notifications and data exchange. The methodology encompasses several phases: designing the architecture of the VMS, developing the web application, implementing the movement detection model, and finally integrating everything with Agnet using SmarTWISP API.
This thesis aims to deliver a comprehensive solution that addresses the current limitation of Agnet application but also enhances its functionalities.
The solution proposed will also incorporate an advanced artificial intelligence model for human movement detection. This AI enhancement aims to automate video stream monitoring, thereby improving real time safety measures, this tool will send immediate alerts and provide recorded evidence for subsequent investigations.
The video management system web application will be developed using modern development tools including React.js, Node.js, Python, and leverage Agnet’s SmarTWISP API for alert notifications and data exchange. The methodology encompasses several phases: designing the architecture of the VMS, developing the web application, implementing the movement detection model, and finally integrating everything with Agnet using SmarTWISP API.
This thesis aims to deliver a comprehensive solution that addresses the current limitation of Agnet application but also enhances its functionalities.