The MTG will install acoustic sensors in the city of Pamplona to monitor sound in urban environments.

SENS (Smart Environmental Noise System) is an acoustic sensor that monitors urban environments. Using specialized hardware and artificial intelligence algorithms, it captures and processes sound in real-time to:
 • Measure ambient sound pressure levels (calibrated measurement, not certified).
 • Determine the pleasantness level of the sound environment (pleasantness as per ISO-12913).
 • Assess the amount of activity in the area (eventfulness as per ISO-12913).
 • Identify specific noise sources such as vehicles, people, birds, dogs, and others.

Installing a network of these devices distributed throughout the city allows real-time data collection with essential information to detect areas with high noise levels, identify the sources, and understand how they impact people’s emotional well-being. This information is key to implementing more effective measures to improve the acoustic quality of public spaces.

The system ensures privacy by processing data locally on each sensor, transmitting only predictions to the central server where they are stored. The data is accessible for real-time consultation.

This pilot project will install five sensors in strategic locations across Iruña/Pamplona, selected through mutual agreement, prioritizing areas of interest such as leisure zones, the historic center, and other high-traffic areas. The Pamplona City Council already has ten measurement points throughout the city, covering busy areas and the historic center. The installation of the sensors will begin by mid-March, and the project results are expected to be presented by the end of June 2025.

This initiative will assess the current performance of SENS sensors in a real environment, providing valuable insights into their effectiveness.

SENS has been selected as one of the projects of the Smart Iruña Lab program, an initiative by the Pamplona City Council that promotes a smarter, more technological, and innovative city.

This action is supported by:

Cátedra UPF-BMAT en Inteligencia Articial y Música (TSI-100929-2023-1). Project funded by Secretaría de Estado de Digitalización e Inteligencia Artificial, and Unión Europea-Next Generation EU