How Machine Learning Can Transform the Transportation Industry

1. HOW MACHINE LEARNING CAN TRANSFORM THE TRANSPORTATION INDUSTRY

2. PROVIDE PERSONALIZED PURCHASE SUGGESTIONS FOR CUSTOMERS DURING ONLINE TRANSACTIONS HOW? By collecting and analyzing data from previous transactions, machine learning processes can effectively discover purchasing patterns for each user. For example, a passenger who buys a certain monthly pass could be offered gifts, discounts or upgrade offers. Even as purchasing patterns evolve, these processes continue to learn and evolve as well. Implementing machine learning in this capacity has the potential to improve customer retention and to drive sales of promotions.

3. USE PREDICTIVE ANALYTICS TO MAINTAIN ENGINE HEALTH MORE EFFICIENTLY HOW? Today, the modern train or bus is embedded with technology components that generate continuous data streams. With these data streams, opportunities arise to build failure predictive models or condition-based maintenance using machine learning. The objective of such models is to detect failures before they occur. Unlike the currently scheduled maintenance approach, condition- based maintenance is based on data rather than guesses. After upgrading to the new model, transit companies can expect lower production downtime and improved equipment life.

4. DETECT TRACK DEFECTS WITH IMAGE RECOGNITION AND MATCHING ALGORITHMS HOW? For rail companies, machine learning is a valuable way to study and analyze tracks for defects based on various conditions including metal wear out, thermal expansion issues and erosions due to number of runs. To do this, machine learning processes utilize recognition and matching algorithms. These algorithms analyze images captured by drone cameras to identify patterns. As a result, the algorithm continually learns and improves to create an understanding of which patterns signify track defects. Similar to the maintenance of train and bus components, rail tracks can be maintained using predictive analytics. It takes the guesswork out of routine maintenance to ensures top efficiency.

5. CREATE AN INTERACTIVE JOURNEY FOR PASSENGERS WITH RICH DATA SETS & A MOBILE APP HOW? Mobile apps are a crucial part of any transit business. They enable passengers to make purchases, check schedules and statuses, find nearby stations and attractions and much more. Machine learning ensures front- end features of the app, such as location tracking, notification systems and suggestion features, are backed by rich data sets that continually adjust and improve over time.

6. DEVELOP TARGETED MARKETING CAMPAIGNS. HOW? Another benefit of having rich data sets is that they can help classify and label passengers based on previous transactions and interactions with the transit company. As a result, these classifications can be used to develop targeted marketing campaigns that match passengers with relevant offers. For example, a person who travels frequently from Point A to Point B can be targeted with offers specific to the route. Additionally, any special public event like a music concert or a baseball match can be leveraged to suggest offers to help attendees reach the event.

7. MANAGE CUSTOMER COMPLAINTS HOW? Another benefit of having rich data sets is that they can help classify and label passengers based on previous transactions and interactions with the transit company. As a result, these classifications can be used to develop targeted marketing campaigns that match passengers with relevant offers. For example, a person who travels frequently from Point A to Point B can be targeted with offers specific to the route. Additionally, any special public event like a music concert or a baseball match can be leveraged to suggest offers to help attendees reach the event.

8. F O RM O R ED E T A I L SC L I C KO N : D A T A C O R E S Y S T E M S . C O M / T R A V E L - T R A N S P O R T A T I O N