Building the dashboard to effectively manage network alarms of VNPT's IP broadband network | |
| Author | Nguyen Xuan Nam |
| Call Number | AIT PJPR PMDS no.25-03 |
| Subject(s) | Dashboards (Management information systems) Organizational effectiveness Telecommunication--Management |
| Note | A project report submitted in partial fulfillment of the requirements for the Degree of Professional, Master in Data Science and Artificial Intelligence Applications |
| Publisher | Asian Institute of Technology |
| Abstract | Telecommunication service providers face increasing challenges in managing the large volume of alarms generated by complex broadband networks. In particular, VNPT’s IP Broadband Network requires an efficient mechanism to detect, classify, and resolve alarms in real time to maintain service quality and operational efficiency. This thesis presents the design and development of a real-time alarm management dashboard that enhances fault management processes through improved visibility, automation readiness, and performance monitoring.The proposed system integrates data from three primary sources: the alarm dataset, the network device inventory, and port traffic statistics. Using a rule-based classification framework, alarms are categorized into either automatable or manual, enabling repetitive low-risk faults to be resolved through predefined actions, while critical issues are escalated to operators. The dashboard provides role-based views: operators receive real-time alarm notifications and automation options, while managers access KPI-driven insights. Key performance indicators (KPIs) such as Mean Time to Acknowledge (MTTA), Mean Time to Resolve (MTTR), and Automation Ratio are continuously calculated and displayed, allowing the system to measure and improve operational performance.The research adopts a design science methodology, progressing through problem identification, system design, implementation, evaluation, and refinement.The evaluation demonstrates that the dashboard significantly reduces MTTA and MTTR while increasing the proportion of alarms resolved automatically, thereby improving efficiency and service reliability. By aligning with industry standards (e.g., ITU-T M.3400) and incorporating ethical and security considerations, the proposed dashboard offers a practical, secure, and scalable solution to alarm management challenges in large-scale broadband networks. |
| Year | 2025 |
| Type | Project |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Professional Master in Data Science and Artificial Intelligence Applications (PMDS) |
| Chairperson(s) | Chutiporn Anutariya;Vatcharaporn Esichaikul (Co-chairperson) |
| Examination Committee(s) | Katinee Katchapakirin;Chaklam Silpasuwanchai |
| Degree | Project (M. Sc.) - Asian Institute of Technology, 2025 |