Press Releases
29 Feb 2024
Harnessing the power of Big data and AI
Attendees of the panel discussion, titled "Harnessing the Power of Big Data and Artificial Intelligence”, held on the second day of the UITP MENA Transport Congress and Exhibition 2024, agreed that cutting-edge technologies, including data analytics and AI, are revolutionizing public urban transportation. The impact of data-driven decisions and artificial intelligence on enhancing service provision and improving the experience for public transport users is becoming increasingly clear. Additionally, these technologies are instrumental in redefining urban planning, leading to the development of cities that are more liveable, accessible, and supportive of improved quality of life.
The discussion panel featured Dr. Omaimah Omar Bamasag, Deputy of Transport Enablement at Transport General Authority, Riyadh, KSA; Meera Alshaikh, Director of the Smart Services Department at RTA, Dubai, UAE; Sascha Meyer, CEO of MOIA in Hamburg, Germany; Brian Higbee, Project Director at Trapeze Group APAC, Middle East, Africa, based in Wimborne Minister, England, UK; and Eyad Tayeb, Managing Director for INIT MENA-ANZ region, Dubai, UAE. The session's moderation was handled by Jaspal Singh, Senior Director of Membership and Global Operations at UITP, Toronto, Canada.
"Highlighting the critical role of the transport sector, Saudi Arabia has dedicated a significant segment of its Vision 2030 to it. The goal is to elevate the use of public transport from 1% to 20% and to ensure that 45% of all transportation methods are environmentally friendly by 2030. In terms of embracing Big data and AI, the Kingdom is actively launching projects, having established five specialized platforms for the gathering of transportation data, taxis included. Our focus isn't limited to Big data and AI; we're also deeply invested in cybersecurity, the Internet of Things (IoT), and cloud computing, which are essential for the smooth integration of sophisticated technologies into our public transport systems," Dr. Omaimah Bamasag stated at the outset of her speech. She also took the opportunity to thank Dubai and the RTA for their efforts in organizing this pivotal event.
"Firstly, I'd like to highlight our partnerships with renowned global entities in the fields of Big data and AI. We have forged a collaboration with the United Nations' expert panel, culminating in a cooperative agreement and the joint organization of a seminar in Dubai. This event saw attendance from specialized organizations from various nations, facilitating a rich exchange of expertise in these areas. Additionally, we have a strong strategy in place for data and AI in relation to self-driving vehicles. Our approach includes extensive field testing to thoroughly vet technologies before we commit to them," Meera Alshaikh elaborated.
Sascha Meyer began his speech by praising Dubai, noting its rapid and significant advancements in the public transport sector and its use of world-class technologies to offer unmatched services to its patrons. "Our strategy in Hamburg is adaptable, taking into account the diverse requirements of our clientele in the realm of mass transit. Time is of the essence in our processes, especially concerning the wait times of our customers, and we are dedicated to improving this aspect by leveraging big data and AI," Meyer remarked.
"Valuing our customers' opinions, ideas, and suggestions for service improvements through data is crucial for us, especially since a significant part of this data is derived directly from the customers," Brian Higbee expressed.
Eyad Tayeb emphasized the importance of utilizing data and AI in ticketing to enhance accuracy in monitoring ticketing processes, passenger numbers, daily transactions, and passenger flows within public transportation systems. The use of data and AI is crucial because the public transport sector is influenced by several factors, including weather conditions, events, and other variables, necessitating accurate management of these changes. Tayeb also highlighted the necessity of maintaining and improving data and AI systems to ensure their continuous development and enhancement of their functionality.