Research on fire smoke traceability based on emotional intelligence Jaya algorithm

Abstract

To timely detect fire smoke in the early stages and trace the gas generated, thereby avoiding the loss of human life and property and reducing damage to the ecological environment, this paper proposes a fire smoke tracing method based on the emotional intelligence Jaya algorithm (EIJaya). The algorithm assigns an anthropomorphic mental state to the unmanned aerial vehicle (UAV) in the traceability task to realize its self-evaluation and social evaluation. In the simulation concentration field, the EIJaya algorithm, the basic Jaya algorithm, and the PSO algorithm were used for the verification of the simulation of gas traceability, and the simulation results proved the advantages of the EIJaya algorithm in terms of the success rate and the iteration times. In this paper, the TT UAV was chosen as an experimental tool to utilize the functions of its expansion module fully, and the experimental hardware system was constructed by combining it with the corresponding sensors. The corresponding experimental scene was built in the indoor environment, and the EIJaya algorithm was used to make multiple UAVs cooperate and conduct traceability experiments, which verified the algorithm feasibility in practical applications and proved that the algorithm could quickly and accurately trace the fire smoke.