"Machine Learning", "Knowledge Representation and Reasoning" and "Business Analytics" is recommended.

The main objective of this course is to study in detail all aspects of "smart cities", a concept that refers to the application of Artificial Intelligence and Information and Communication Technologies for the planning, management and provision of services in the cities of the future, through the innovative and disruptive use of data, technologies and available resources, involving citizens, to help solve major challenges of today's big cities such as traffic congestion, environmental pollution, inequality in access to opportunities and reduced quality of life. At the end of the course, the student will know the fundamentals and the most important application areas of AI in the cities of the future and will be able to approach and analyze the deployment of this type of solutions in scenarios that can achieve significant improvements.

1. Artificial Intelligence in the city of the future. 1.1. Technology fundamentals. 1.2. Required infrastructures. 1.3. Application scenarios. 2. Mobility and sustainable transport. 2.1. Analysis and prediction of mobility. 2.2. Alert and response systems to traffic incidents. 2.3. Optimization of transport networks. 3. Environmental sustainability. 3.1. Pollution analysis and monitoring. 3.2. Efficient waste management. 4. Energy and efficiency. 4.1. Energy consumption models. 4.2. Management and analysis systems for energy efficiency. 5. Smart municipal services. 5.1. Optimization of the quality of administrative services. 5.2. Optimization of the quality of sports, cultural and leisure services. 5.3. Optimization of public safety. 6. Citizen behavior. 6.1. Citizen sensor. 6.2. Citizen participation in social networks and surveys.

Training activities include: - Lecture sessions (AF1), doubt resolution classes (AF3), student presentations (AF7), individual tutorials (AF5) and student's personal work (AF7); oriented to the acquisition of theoretical knowledge (MD1 and MD2) - Laboratory practices and problem classes (AF2), individual tutorials (AF5) and student's personal work (AF7); oriented to the acquisition of practical skills related to the program of the course (MD3) - Development and presentation of a group project (AF6), to be chosen among the different topics covered by the course, oriented to verify that the student is able to develop (design, implement and validate) a computer system equipped with Artificial Intelligence elements that is able to solve specific aspects of smart cities (MD4 and MD5)