The project focuses on the design, development and implementation of a system to monitor and
visually display motorcycle lean angle. The system aims to provide additional safety for the
driver of a motorcycle by displaying critical information using LED strips. The idea came from
my personal need and desire to provide more information while driving a motorcycle, more
specifically information about the lean angle of a motorcycle especially in situations like high
speed turns. As a means of transport, motorcycles have a greater potential for excessive lean
angle and loss of contact with the road surface. Therefore, this system is designed to prevent
excessive leaning during driving and to avoid resulting accidents. The system is based on a
sensor that continuously captures lean angle and acceleration data. This data is processed and
filtered by a program I have written to ensure reliability. The values obtained are then visually
displayed via two LED strips, which are positioned so that the right one shows the inclination
in the positive direction (right) and the left one in the negative direction. Depending on the
severity of the lean angle, the LEDs on the strip light up sequentially, with the green LEDs
representing normal lean angle values, the yellow LEDs representing sport lean angles and the
red LEDs representing critical lean angle values which represent potential hazards. The aim
was to develop a system that intuitively shows in real time how much the motorcycle is leaning.
The whole system is controlled by a microcontroller which processes the sensor input and
controls the two LED strips. During the development phase, calibration played a critical role in
establishing a baseline for further tilt angle tracking. A great deal of effort has therefore been
invested in optimising this process so that, regardless of variations in sensor data or external
conditions, operation is always stable and reliable. In addition, the system offers two main
modes of operation, a driving mode and a service mode, which can be selected at the touch of
a button. Each of these determines how the LED strips respond to the pitch data, where the
service mode is much more sensitive as it is designed to be used while servicing and running
diagnostics on a motorcycle, when it is at a stop. During the testing phase the system was
evaluated in a controlled environment as I had to sell my motorcycle during the development
of the project. Despite the constraint, I carried out extensive testing at home on my desk to
simulate the conditions of outdoor use. The strips responded dynamically to the inclination
inputs, and calibration ensured that these inputs were correct. The end result is a robust,
responsive and reliable lean angle monitoring system that provides real-time visual information
to the user to help them avoid dangerous leaning. The project has not only successfully solved
the original problem, but has also enabled the development of technical skills such as sensor
integration and data filtering. With further upgrades, the system could be installed on a
motorcycle for longer testing and eventual commercial use.
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