Urban projects are the space where people, mobility, public spaces, technology, and ecology converge.
Through urban analytics, simulations, and participatory diagnosis, we create solutions that make cities more human, connected, and adaptable.
NexTCity aims to strengthen NOVA IMS's expertise in urban digital twins to support the smart and sustainable development of cities. The project covers all stages of development—data collection, analysis, visualization, and governance—in collaboration with Universitat Jaume I and KU Leuven.
This project, aligned with the National Strategy for Smart Territories (ENTI) and its reference architecture, aims to develop and implement a Digital Twins (DT) framework to support climate action governance in Portuguese cities.
Smart Port LX is a project focused on the Port of Lisbon with the aim of making it a connected, sustainable, safe, and automated port, based on smart infrastructure and equipment, qualified personnel, and smart management practices to ensure customer satisfaction, environmental protection, and a better quality of life for citizens.
Estrela Pela Felicidade is developing a specific Happiness Indicator for the parish of Estrela, in Lisbon, integrating objective data (geospatial and sociodemographic) with subjective perceptions gathered from the population.
Data for Lisbon Service is a partnership between Lisbon City Council (CML), the Lisbon Higher Institute of Engineering (ISEL), and NOVA IMS, dedicated to improving urban management through data and technology.
The Almada Circular and Smart 2030 project lays the foundations for transforming Almada into a circular, smart, and sustainable city by 2030, accelerating the decarbonization process and reinforcing the municipality's strategic role in this transition.
City Catalyst – Catalyst for Sustainable Cities is geared towards the creation and validation of digital products, processes, and services to support urban management.
Data 4 Oeiras Valley is a smart city initiative that applies descriptive, predictive, and prescriptive analytics to support municipal decision-making with constantly updated analytical evidence.
