**Background**
Autonomous buses require onboard computing capable of processing sensor data and responding to events in real time. Vision-based passenger monitoring can require significant computational resources, particularly when multiple camera streams and deep learning models are used.


Edge AI platforms such as the NVIDIA Jetson Nano enable computer vision and machine learning to run directly onboard the vehicle, reducing latency and network requirements. However, limited computing, memory, and power resources create challenges for real-time deployment.


This thesis aims to develop and evaluate an efficient vision-based passenger monitoring pipeline for edge AI hardware. The work will investigate how computer vision and deep learning models can be optimized to achieve a suitable balance between detection accuracy and computational efficiency.


**Work Description**
**The thesis will investigate:**

- Develop and evaluate a real-time passenger-monitoring pipeline on NVIDIA Jetson Nano.
- Investigate model optimization and hardware acceleration using techniques such as quantization, reduced resolution, CUDA, and TensorRT.
- Evaluate accuracy, latency, resource usage, and scalability across different camera configurations and realistic autonomous-bus scenarios.

The work will include model selection, implementation, optimization, and evaluation, with a focus on balancing monitoring performance and real-time computational requirements.


**Qualifications**

- Programming experience in Python or C++ and knowledge of computer vision and machine learning.
- Basic knowledge of deep learning and an interest in autonomous vehicles and edge AI.
- Background in Computer Science, Machine Learning, Engineering Physics, Electrical Engineering, Mechatronics, or equivalent.
- Good knowledge in both Swedish and English, speaking and writing.

**Meritorious:**
Experience with NVIDIA Jetson, CUDA, TensorRT, PyTorch, TensorFlow, OpenCV, ROS2, model optimization, embedded systems, or real-time computer vision.


*Tags: Autonomous Vehicles, Autonomous Bus, Edge AI, NVIDIA Jetson, Computer Vision, Deep Learning, Real-Time AI, Model Optimization, Passenger Monitoring*
To give you the best possible support during your thesis, we’d like you to be able to come to the office connected to the project and spend most of your time working from there.


**Application:**
We look forward to receiving your resume, and preferably, a personal letter in which you explain why you want to write your thesis with Syntronic.


We screen and evaluate applications on an ongoing basis. The thesis project may be filled before the application deadline.