Enhanced sparrow search algorithm with DV-Hop for high-precision fire sensor localization in underground spaces.

Area of Science:

• Engineering
• Computer Science
• Emergency Response

Background:

• Accurate fire sensor localization is crucial for underground emergency response.
• Traditional methods like DV-Hop exhibit significant localization errors.
• Issues include hop count ambiguity and premature optimization convergence.

Purpose of the Study:

• To develop an improved localization method for underground fire monitoring.
• To address the limitations of existing DV-Hop algorithms.
• To enhance the accuracy and reliability of fire sensor positioning.

Main Methods:

• Proposed an Enhanced Sparrow Search Algorithm with Improved DV-Hop (ESSADV-Hop).
• Implemented a golden ratio-based communication radius division for refined hop count.
• Utilized an enhanced sparrow search algorithm with Gaussian perturbations to avoid local optima.

Main Results:

• ESSADV-Hop reduced average localization error by 55.7% compared to DV-Hop (0.2910 to 0.1288).
• Achieved 11.74%–23.05% higher accuracy than other DV-Hop variants.
• Demonstrated superior performance in complex underground environments.

Conclusions:

• ESSADV-Hop effectively enhances fire sensor localization accuracy in underground settings.
• The proposed method overcomes key limitations of traditional DV-Hop algorithms.
• ESSADV-Hop offers a more reliable solution for critical underground fire monitoring and emergency response.