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SPARK: Smart Building Fire Prediction And Risk Analysis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper develops SPARK — a novel algorithm for predicting fire spread in smart buildings. SPARK leverages prior information about the building (e.g., room flammability, structural layout, and occupant distribution) together with real-time multimodal sensing data from static sensors (e.g., temperature sensors, smoke detectors, and embedded structural monitoring devices), dynamic sensors (e.g., drones and robots), and human sensors such as firefighters. By continuously integrating these heterogeneous information streams, SPARK produces a real-time and adaptive prediction of fire spread. Specifically, SPARK classifies rooms into risk zones (e.g., safe, vulnerable, and critical) using a clustering algorithm.

Original languageEnglish (US)
Title of host publicationProceedings - 2025 23rd IEEE International Symposium on Network Computing and Applications, NCA 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages247-254
Number of pages8
ISBN (Electronic)9798331578428
DOIs
StatePublished - 2025
Event23rd IEEE International Symposium on Network Computing and Applications, NCA 2025 - Lisbon, Portugal
Duration: Nov 5 2025 → Nov 7 2025

Publication series

NameProceedings - 2025 23rd IEEE International Symposium on Network Computing and Applications, NCA 2025

Conference

Conference23rd IEEE International Symposium on Network Computing and Applications, NCA 2025
Country/TerritoryPortugal
CityLisbon
Period11/5/25 → 11/7/25

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications

Keywords

  • graph model
  • Sensor data
  • Smart buildings

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