With over 30 years of experience in designing, manufacturing and maintaining on-board communication and control systems, Televic Rail is a leading, trusted partner for railway operators and train builders worldwide.
Its Passenger Information Systems and Control Systems are high quality, tailor-made solutions that offer the flexibility, user-friendliness and stability that our clients ask for. Our various types of on-board control systems such as our bogie monitoring systems are innovative yet reliable products which are designed specifically for the railway business.
Trains and trams all around the world are equipped with Televic Rail solutions, from New Zealand to Canada, from China to the United States, from India to Belgium, England and France.
Train operators are interested in reliable, yet low-cost, methods to determine whether a specific seat in the train in occupied. This helps to obtain accurate occupancy estimates and to inform the passengers of less-crowded regions in the train. Additionally, if the seat is empty, or luggage is lying on it, the seat can be (re)sold by the operator.
Televic GSP would like to investigate whether a low-cost accelerometer can be used to classify the seat occupancy status. The main assumption is that an occupied seat undergoes different vibrations than an unoccupied seat as the train moves along the track. In correctly classifying these different vibration modes, the seat occupancy status could perhaps be determined.
Following up on an earlier simulation study, the student would use a low-cost device to perform measurements on an actual train and use the collected data to try and discern between (at least) occupied and unoccupied seats. Depending on the expertise and interest of the student, the design of the low-cost device itself can be embedded in the project.
If you are interested in this topic, please also register this on the Televic website at: https://www.televic.com/en/careers/internships-and-students so we can confirm the topic is still available.
- Level: Academic Master/Master
- Specialty: AI/Machine Learning/ Software
- Type of work: Research 25%, Implem. 25%, Experim. 50%
- Location: Televic/University
- Type of activities: Design, Experimenting, Literature study, Programming
- Number of students: 1