Accenture has helped the Spanish metro develop and implement a self-learning, artificial intelligence ventilation system that ensures high air quality in its stations
Professional services firm Accenture has taken inspiration from a bee colony to help Metro de Madrid in Spain ensure high air quality in metro stations as well as reduce energy costs for ventilation by a quarter.
It has helped the metro to develop and implement a self-learning artificial intelligence- (AI-) based ventilation system that minimises energy costs and emissions. It has also enabled Metro de Madrid to cut CO2 emissions by 1,800 tons annually.
Accenture will present the system at this year’s Mobile World Congress, which runs 25-28 February in Barcelona.
On average, 2.3 million commuters use Metro de Madrid’s network of 294km of track and 301 stations every day. To help passengers stay cool inside stations, particularly during the hot summer months, Metro de Madrid operates 891 ventilation fans, which were consuming as much as 80 gigawatt hours of energy annually.
The metro’s ventilation experts worked with Accenture Applied Intelligence to develop a system that took inspiration from the coordinated foraging behaviour of a bee colony.
The system deploys an optimisation algorithm that leverages vast amounts of data to explore every possible combination of air temperature, station architecture, train frequency, passenger load and electricity price throughout the day. It uses both historic and simulated data, factoring in outside and below-ground temperatures over the next 72 hours.
Because the algorithm uses machine learning, the system gets better at predicting the optimal balance for each station on the network over time.
“The self-learning ventilation system shows how organisations and society can benefit from intelligent technologies”
“With the help from Accenture, the innovative ventilation system has enabled us to achieve the dual benefits of lower energy costs and a reduced environment impact,” said Isaac Centellas, head of engineering and maintenance division at Metro de Madrid. “Ensuring the comfort of our passengers while being highly energy-efficient and environmentally friendly is a true win-win outcome.”
The system also includes a simulation engine and maintenance module, which allows for, among other things, tracking for failures in the fans’ operation. This enables Metro de Madrid to easily monitor and manage energy consumption, identify and respond to system deficiencies, and proactively conduct equipment maintenance.
Isabel Fernández, managing director for Accenture Applied Intelligence in Spain, said: “Our self-learning ventilation system shows how organisations and society can benefit from intelligent technologies. It’s an important milestone in our work for Metro de Madrid, and we’re excited to present it to the public at this year’s MWC, where applied AI will play a bigger role than ever.”
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