Smart CEIM is an open experimentation platform for Smart City services located in the Moncloa Campus of International Excellence in Madrid. It aims to facilitate advanced R&D and training activities done by the University, companies, and public bodies.
The Smart CEIM platform is part of the City of the Future project of Universidad Politécnica de Madrid (UPM).
The Moncloa University Campus
Given its exceptional location, integrated within the metropolitan area of Madrid, the Moncloa Campus has geographic and human characteristics that are sufficiently representative for research and experimentation in Smart City services.
The Campus has around 150 buildings in an area of 5.5 square kilometers, including schools, research centers, and student housing, plus three sport areas and large green spaces. Tens of thousands of cars use the Campus roads every day. The Campus has a good public transport service with two subway lines and thirteen bus lines.
The Smart CEIM Platform has a powerful cloud-based storage and computing infrastructure. It complies with open standards in order to facilitate the deployment of new experiments and services.
This infrastructure provides adequate capacity for the use of Big Data techniques, as well as interfaces for Open Data access.
The demonstration room houses the platform dashboard and offers several large screens for displaying experiment results.
The platform offers an initial set of pilot services, which will be extended with additional services developed in the future.
Currently deployed services include:
- Environmental monitoring. By deploying a network of sensors distributed across the campus, this service allows monitoring various environmental parameters such as temperature, humidity, light intensity, noise, and air quality.
- Monitoring energy consumption. This service allows monitoring and analysis of electricity consumption in campus buildings by using sensors coupled to electrical boxes.
- Analysis of people flows and vehicle flows. This service allows the approximate count of people and vehicles in the campus, as well as the analysis of movement patterns, busiest places, times spent in points of interest, etc.
The implementation of these services has required the installation and configuration of several sensor networks throughout the campus, plus auxiliary power and communication network infrastructures.