Authors:
Ágata Palma
1
;
Pedro Morais
1
and
Ana Alves
1
;
2
Affiliations:
1
Polytechnic University of Coimbra, Rua da Misericórdia, Lagar dos Cortiços, S. Martinho do Bispo, 3045-093 Coimbra, Portugal
;
2
CISUC, LASI, University of Coimbra, Polo II, Pinhal de Marrocos, 3030-290, Coimbra, Portugal
Keyword(s):
GIS, Information Retrieval, Ambient Intelligence, Clustering, Route Recommendation, POIs.
Abstract:
With the rapid advancement of technology in today’s interconnected world, Ambient Intelligence (AmI) emerges as a powerful tool that revolutionizes how we interact with our environments. This article delves into the integration of AmI principles, Python programming, and Geographic Information Systems (GIS) to develop intelligent route recommendation systems for urban exploration. The motivation behind this study lies in the potential of AmI to address challenges in urban navigation, personalized recommendations, and sustainable transportation solutions. The objectives include optimizing travel routes, promoting sustainable transportation options, and enhancing user experiences. This research will contribute to advancing AmI technologies and their practical applications in improving urban living standards and mobility solutions.