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Wednesday, 8.05.2024
eGovernment Forschung seit 2001 | eGovernment Research since 2001

Drivers to be assessed using smart device, arm band to avoid accidents, enhance safety

In a first-of-its-kind Tram Driver Monitoring system in the world, Dubai Tram drivers will be assessed in real time using artificial intelligence to prevent accidents and enhance safety of passengers.

With ‘Safety and Environmental Sustainability’ being one of the key strategic goals, Dubai’s Roads and Transport Authority (RTA), in partnership with Keolis MHI and VirtuE Therapy and Research has implemented the third phase of trials of the use of AI Technology to assess Tram Drivers in real time and ensure passenger safety.

“The Tram Driver Monitoring system is the first of its kind in the world,” the authority said on Sunday.

Emotional Data Analysis and Automation (EDAATM) is a generative AI. system based on deep learning models that were provided by a Spanish Firm, OWN Experiences, which has its R and D branch, VirtuE Therapy, and Research, based in the UAE.

How it is done

RTA is working closely with both the provider and the operator of Dubai Tram, Keolis MHI to review and collect the data. The system includes a smart device and an armband to have a multitude of detection classifications such as heart rate, speech patterns, and reaction times to determine driving style, unsafe patterns, deviations, and gestures based on drivers’ profiles.

The solution reduces the potential of human error incidents, by predicting behaviour that can threaten operational safety and trigger a preventive response to prevent incidents, accidents, and near-misses. It will also provide information based on locations – which will help show ‘hot spots of concerns and address viable solutions. The system is always assessing critical areas and processes an adequate response through the embedded individual profiling technology.

Collected data is then processed from both incidents and routine operations to provide a comprehensive understanding of the individuals. It then defines the required profiles to continuously improve the system.

Hassan Al Mutawa, director, Rail Operations, Rail Agency said: “Transportation networks and their assets are widely known as critical infrastructures that require attention to details and special protection. Looking at the potential of human errors and how to mitigate them, Dubai’s RTA uses the latest innovative solutions such as Artificial Intelligence. This is in line with its corporate values – innovation and creativity to support a Digital Dubai. We are currently in the trial phase of this innovative AI solution with our partners to ensure our passenger’s safety. Following a successful trial, we expect to implement it across the Dubai Trams.”

Focus on smart city

Wallace Weatherill, managing director of Keolis-MHI, Dubai Metro and Tram Operator, said: “We are living in a digital era, and we will continue to advance as more artificial intelligence and deep learning applications are being used in everyday processes. The RTA has a core focus supporting the smart city approach in Dubai, with the Dubai Metro, a fully automated driverless rail system, it is no surprise that they are the leaders in the region. Keolis MHI, renowned for working with autonomous public transportation, will continue to work closely with the RTA to explore AI solutions and the Tram Driver Monitoring System is a small step towards a bigger future”.

Elisabet Calomarde, co-founder and chief Data Officer, VirtuE R and D, said: “We are proud to be working in collaboration with Dubai’s RTA and Keolis MHI on this trial. On the back of the collaboration, VirtuE as a branch of Own Experiences Group, looks forward to providing data-driven results to better understand the requirements and tailor a product that will serve the needs. Facilitating greater cooperation to deploying a first-of-its-kind initiative in the world that will cement the Dubai Tram as an innovative and safe form of transportation for Dubai’s world-recognised public transport network”.

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Quelle/Source: Gulf News, 31.10.2022

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