Trajectory optimization for exposure to minimal electromagnetic pollution using genetic algorithms approach: A case study

Low-frequency electromagnetic pollution associated with electricity supplies and electrical appliances creates broad specific challenges. Among them, knowing the values of this in urban areas to prevent long exposure daily life human beings is rising today's information society. This paper presents a comprehensive approach for, first, mapping complete and, second, based on former data, trajectories planning commuting minimal exposure. In first stage, proposed reduces number necessary measurements for mapping, estimating their value by optimizing functional criteria using genetic algorithms (GAs) considering superposition effect different sources. second combination specifically designed search space GA as optimization algorithm makes it possible determine an optimized trajectory that represents balanced solution between distance magnetic fields. The results verify obtaining less error, 1% 2.5%, power lines medium/low voltage (MV/LV) substations, respectively. obtains types (pedestrians, bikers, vehicles), can be integrated into mobile applications. Finally, method was tested actual area Malaga (Spain).