A smart metropolis promotes social inclusion through adaptive technologies that go beyond operational efficiency . This research applies Artificial Intelligence (AI) to smart city environments, proposing an accessible navigation system to redesign traditional urban infrastructures as genuinely inclusive spaces. The Guadalajara Zoo serves as a living laboratory to validate these solutions, focusing on children with motor disabilities and functional hearing impairments. The methodology implements Dijkstra's algorithm to calculate optimal, personalized routes, considering granular variables such as distance, slope, pavement type, obstacles, and the user's specific mobility profile. Computational simulation of the model successfully generated consistent itineraries for three accessibility profiles (wheelchairs, crutches, and strollers) within a 60-minute window. The results showed an optimized visit capacity ranging from 4 to 12 points of interest per hour, depending on the depth of the visit and the mode of mobility. In a typical visit scenario (~5 min/stop), the optimized model allowed a child in a pushchair to visit 6 to 7 habitats in one hour. The system personalizes the experience by calculating the distance and total time based on the user's available time and needs, demonstrating an improvement of up to 25% in route efficiency compared to non-adapted routes. These findings validate the model as a scalable solution for inclusive mobility in smart environments. The prototype ensures an autonomous, safe, and enriching experience, positioning AI as a key mediator of spatial justice.