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Case Study
Rio de Janeiro: a new underground system for a better mobility
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Innovative monitoring and control technologies for the new Rio underground line, to ensure safety and reliability.
Where: brazil
Where: brazil
Challenge
Rio de Janeiro, in Brasil, is among the busiest cities in the world. The critical issues are mainly caused by the many cars that fill the city streets each day: according to the BBC, in the last 10 years the number of cars has increased by over 40%.
To solve the problem, the local administration made the decision to improve urban transport.
Approach
For the 2016 Olympics, it decided to build Line 4 of the underground, connecting the city centre to Barra da Tijuca, a neighbourhood south of Rio where the sports facilities had been built, but above all, where the majority of commuters live, facing with a daily journey of more than two hours.
The challenge was to build, test and commission the entire work in just two years, coordinating heterogeneous work teams from Austria, Italy, Brazil and Argentina.
We created the telecommunications infrastructure of the entire underground line (with over 12 km and seven stations) and a central control centre, including also: the data network, TETRA system, the SCADA control system, service and emergency phone, information panels, the sound system, the CCTV video surveillance system, access control and ticketing services.
The data network, on which all the other systems depended, was first created; subsequently, and in parallel, we have integrated all the components, using the latest technologies for the monitoring and control of underground transport systems. During the installation and testing phases, we created a simulation platform that analysed a sample of system components. All this, to prevent any errors, unexpected behaviour or integration problems.
Results
Impacts
Technologies
AI & Advanced Analytics
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The power of big data leads services, products and processes to a higher level of "intelligence".
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Case Study
Automatic production of documentation from source code
Use of EngGPT to automatically generate from large amounts of code and video tutorials the documentation needed to maintain the systems
Research Project
MobiSpaces: new Data Spaces for green mobility
MobiSpaces delivers an end-to-end platform that is mobility-aware and optimized, utilizing mobility analytics outcomes to improve the entire data path.
Use Case
ROOTS: "Return to Origins" Traceability System
How to leverage a traceability digital platform that extends beyond real-time tracking, empowering farmers, producers, and retailers to furnish proof of sustainability.
-
Case Study
Automatic production of documentation from source code
Use of EngGPT to automatically generate from large amounts of code and video tutorials the documentation needed to maintain the systems
-
Research Project
MobiSpaces: new Data Spaces for green mobility
MobiSpaces delivers an end-to-end platform that is mobility-aware and optimized, utilizing mobility analytics outcomes to improve the entire data path.
-
Use Case
ROOTS: "Return to Origins" Traceability System
How to leverage a traceability digital platform that extends beyond real-time tracking, empowering farmers, producers, and retailers to furnish proof of sustainability.
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