Abstract
The aim of this research is to develop a technology enabled Unified Emergency Response Platform (UERP) that enhances situational awareness, decision-making, and response efficiency during urban fire emergencies. Traditional systems, such as Hassantuk, are primarily reactive and focus on alarm verification, often leading to delays and limited coordination among stakeholders. To address these challenges, this study proposes an integrated framework that leverages the Internet of Things (IoT), Artificial Intelligence (AI), digital twins, and predictive analytics to enable early fire detection, rapid alarm validation, and optimized incident response. The platform is structured around three key phases: (1) Early detection and prediction through IoT-enabled sensors and predictive models; (2) AI-driven alarm validation, reducing false positives and verification time; and (3) Coordinated incident response supported by real-time dashboards, digital twins, and automated workflows. A comparative analysis of Omniconn and Hassantuk highlights the need for interoperability and proactive intelligence to complement national emergency infrastructure. Data analysis from Omniconn reports and Kaggle fire incident datasets demonstrates that the proposed system can significantly reduce response latency and minimize property damage. The findings contribute to both academic and practical domains by outlining a scalable, data-driven framework that can transform urban fire emergency management into a proactive and resilient ecosystem. Keywords: Smart Cities, Fire Emergency Response, Situational Awareness, IoT, AI, Digital Twin, Knowledge Graph, Predictive Analytics, Wearable Health Monitoring, Adaptive Dashboards, Command and Control Systems, Interoperability, Emergency Dispatch System, Augmented Reality (AR), Sensor Networks, Urban Fire Safety, Urban Emergency Response Platform (UERP)
Publication Date
8-2025
Document Type
Thesis
Student Type
- Please Select One -
Degree Name
Professional Studies (MS)
Department, Program, or Center
Professional Studies
Advisor
Sanjay Modak
Advisor/Committee Member
Philipe Bouvier
Recommended Citation
Syed, Saleem, "Enhancing Remote Operator Situational Awareness Leveraging technology for Improved Decision-Making in Urban Emergency Response" (2025). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/12347
Campus
RIT – Main Campus
