RT Journal Article
T1 Trajectory optimization for exposure to minimal electromagnetic pollution using genetic algorithms approach: A case study
A1 Gallego-Martínez, Raúl
A1 Muñoz-Gutiérrez, Francisco Jesús
A1 Rodríguez-Gómez, Alejandro
K1 Algoritmos genéticos
AB Low-frequency electromagnetic pollution associated with electricity supplies and electrical appliances creates broad and specific challenges. Among them, knowing the values of this pollution in urban areas to prevent long exposure in the daily life human beings is rising in today's information society.This paper presents a comprehensive approach for, first, mapping electromagnetic pollution of complete urban areas and, second, based on the former data, the trajectories planning of commuting with minimal electromagnetic exposure.In the first stage, the proposed approach reduces the number of necessary measurements for the pollution mapping, estimating their value by optimizing functional criteria using genetic algorithms (GAs) and considering the superposition effect of different sources.In the second stage, a combination of a specifically designed search space and GA as optimization algorithm makes it possible to determine an optimized trajectory that represents a balanced solution between distance and exposure to magnetic fields.The results verify the obtaining of a complete mapping with less error, between 1% and 2.5%, in power lines and medium/low voltage (MV/LV) substations, respectively. The proposed approach obtains optimized trajectories for different types of commuting (pedestrians, bikers, and vehicles), and it can be integrated into mobile applications.Finally, the method was tested on an actual urban area in Malaga (Spain).
PB Elsevier
YR 2022
FD 2022-11-30
LK https://hdl.handle.net/10630/24889
UL https://hdl.handle.net/10630/24889
LA eng
NO Raúl Gallego-Martínez, Francisco J. Muñoz-Gutiérrez, Alejandro Rodríguez-Gómez, Trajectory optimization for exposure to minimal electromagnetic pollution using genetic algorithms approach: A case study, Expert Systems with Applications, Volume 207, 2022, 118088, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2022.118088
NO Financing for open access position: University of Malaga / CBUA.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 mar 2026