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COMPANIES AND STAKEHOLDERS RENEW THEIR CONFIDENCE IN NME: EXHIBITION’S SECOND EDITION BECOMES THE FOCAL POINT IN ITALY FOR DISCUSSIONS ON GREEN PUBLIC TRANSPORT

READ THE PRESS RELEASE
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COMPANIES AND STAKEHOLDERS RENEW THEIR CONFIDENCE IN NME: EXHIBITION’S SECOND EDITION BECOMES THE FOCAL POINT IN ITALY FOR DISCUSSIONS ON GREEN PUBLIC TRANSPORT

READ THE PRESS RELEASE

Artificial intelligence at the service of transport
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Asstra and Uitp take their first steps towards the future. Energy transition and AI are the drivers of innovation. Here are the proposals

Local Public Transport (LPT) is undergoing an unprecedented revolution that seeks to incorporate artificial intelligence to drive sustainability and innovation. Themes that will be at the heart of the Next Mobility Exhibition programme thanks to two conferences, the first organised by Agens under the title 'Big Data: from theory to practice’, and the second, which will be staged under the auspices of Club Italia, entitled “MAAS, artificial intelligence and e-ticketing: where are we in terms of technology development?” On this topic, Asstra recently published a study with ambitious proposals to address the challenges of the energy and digital transition and to maximise the use of AI in the sector. At the centre is the energy transition that is rapidly transforming public transport fleets, raising questions about future corporate and organisational strategies. In this context, the UITP report 'Moving Forward with Artificial Intelligence in Public Transport', by Karine Sbirrazzuoli - Senior Director Knowledge and Innovation UITP, provides valuable insights into AI trends in the sector and its potential applications. The study, which involved over 100 experts from the public transport and IT sectors, analysed the current use of AI in public transport and highlighted its increasingly important role in areas such as customer service, operations, engineering and safety management. In addition, the report identified several common applications of AI in public transport, such as real-time operations management, customer data analysis, predictive maintenance and safety system management.