Data Intelligence: how optimizing data is set to revolutionize the world of transport

Keeping vehicles on the road with a real-time control room

Akkodis has an impressive track record in telematics. Denis Grandjean, Head of Data Intelligence, recalls: “Our customer, a company that designs and manufactures buses for urban and interurban transport, approached us with a major challenge: their contract guarantees a certain level of vehicle availability. If they can't deliver on that, they risk penalties – and their reputation.”

This means keeping the buses in good health and on the road. The first task was to connect to the bus telematics system and collect data to monitor bus activity in real time. “We had to work hand in hand with the customer to understand their data, identify what would be useful and what needed to be put in place. Initially, we developed a real-time chain to collect the data, upgrade it and structure it ready for use. Then we moved on to the enrichment phase: we created indicators and alerts, and finally displayed the results via a user interface,” explains Adelin Bouchet, the team's data scientist.

The Control Room not only retrieves telematic data, but also offers customized indicators powered by Datakkod, a big data and data science platform developed by Akkodis with open-source components and hosted in a sovereign cloud.

The emergence of electric vehicles has brought new challenges, such as how to ensure long battery life. Urban or intercity vehicles, and the wide variety of climatic conditions, have a major impact on batteries. Adelin Bouchet explains: “We receive real-time data from almost five thousand buses running all over Europe - from Norway to Italy - and as far afield as New Caledonia [in the South Pacific] and Africa. To meet our customer's internal reporting needs, we developed dashboards for Power BI [a data visualization software product], their chosen business reporting solution.” The platform is also used externally to automate fleet reports and demonstrate the manufacturer's service quality and compliance with maintenance contracts, which represents a major competitive advantage.

Driving change towards predictive maintenance

Captured data includes indicators on components critical to operating buses, such as the door opening system. A bus with faulty doors, for example, can no longer run. So, it’s essential to develop predictive models based on historical data. This provides customers with the means to prevent breakdowns and plan vehicle maintenance. We are shifting from a reactive or preventive maintenance model to prescriptive maintenance.

Until now, the Control Room has collected and processed huge quantities of data collected in vehicles. The next step could be just as exciting: equipping buses with on-board algorithms, reducing the amount of data stored and, consequently, the system's digital footprint. Hermine Montrouge, the project manager, explains: “We recently submitted a proposal to our client’s sister company for the design of a real-time Control Room. It would provide live feedback on alerts and anomalies and display a true digital twin for each bus. This tool could be further enhanced with machine learning. The final product would generate great publicity for our company and could easily find its way into many other fields.”

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