Master Thesis - E-Bike tampering detection using machine learning algorithms

  • Scheelevägen, Lund, Sweden
  • Contract
  • Legal Entity: Robert Bosch AB

Company Description

Welcome to a world, where your ideas lead to something big. Welcome to Bosch!
Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology – with us, you will have the chance to improve quality of life all across the globe. In Lund we develop products for automotive, ebike and IoT, Lund is a software center within Bosch and we are around 180 engineers working with different products for tomorrow´s automotive industry. Welcome to Bosch!

Job Description

Problem statement
If you are interested in shaping the future of connected mobility with a touch of adventure, health oriented products and a focus on sustainability, we at Bosch electronic bike (eBike) systems are excited to offer an inspiring and fun master’s thesis project.

The Bosch Connect Module (BCM) is a system component mounted on the eBike connecting it to the cloud via a cellular modem. The BCM includes advanced sensors and positioning electronics to enable 24/7 monitoring of the bike location and motion. With the help of the BCM the assignment in this project is to detect if the bike has fallen over or has been exposed to repeated strong hits indicating tampering of the bike.

Proposed solution

The focus in this thesis project shall be on developing algorithms for tampering detection. In the team algorithm development has been conducted for other purposes and there is a framework in place for researching, developing, testing and evaluating algorithm ideas.

We propose the following topics to be covered in the thesis:

  • Describe and identify which events that could be considered tampering, e.g. bike fallen over.
  • Research and find suitable algorithms for tampering detection using state of the art techniques such as machine learning and analytical methods for time series data.
  • Identify relevant features for tampering detection based on the available sensors.
  • Conduct field testing to evaluate, verify and validate the algorithms in different real world scenarios.

You will of course have the opportunity to shape the thesis based on your knowledge, skills and discoveries during the project.

Qualifications

Your profile
In order to be successful in the project with think you are:

  • A student in Information Technology, Computer Science, Electronics, Math or Physics.
  • Interested in algorithm development and have some signal processing experience with machine learning knowledge.
  • Experienced with or have at least some knowledge of programming in Matlab, Python, C++ or similar.
  • Self-driven, able to challenge yourself, and gain the experience needed to move the project forward.
  • A person with team spirit, social skills and a curiosity for exploring new technology areas.
  • Proficient in English.

Please note: Only applications from students at a Swedish University are accepted.

Additional Information

Scope of master thesis project
Two students completing 30 credits each (20 weeks) onsite at the Lund office.

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