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Dubai is using artificial intelligence (AI) to assess tram drivers in real-time and ensure passenger safety. The Roads and Transport Authority (RTA) has now implemented the third phase of trials of the technology.
The first of its kind system in the world, Emotional Data Analysis and Automation (EDAATM) is a generative AI system based on deep learning models provided by Spanish Firm OWN Experiences, which has its R&D branch, VirtuE Therapy and Research, based in the UAE.
The RTA is working closely with both the provider and the operator of Dubai Tram, Keolis MHI, to collect and review 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 driver profiles.
The solution reduces the potential of human error incidents by predicting behaviour that can threaten operational safety. It can trigger a preventive response to prevent incidents, accidents, and near-misses.
It will also provide information based on locations – which will help show areas of concern and propose 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 AI.”
Following a successful trial, the technology will be implemented across the Dubai Tram.
Wallace Weatherill, managing director of Keolis-MHI, said: “We are living in a digital era, and we will continue to advance as more AI and deep learning applications are being used in everyday processes.”
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