Thesis Proposal -Real- Time Vision-Based Passenger Monitoring on Edge AI Hardware for Autonomous Buses
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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.
- Department
- Studenter
- Role
- Examensarbete
- Location
- Linköping
Linköping
Benefits
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Work life balance
Flexible working hours.
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Wellness
Wellness allowance and Benefit (a benefits portal that gives instant access to rewards and discounts).
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Health and insurance
Beneficial pension agreement with personal provisions and insurance. Private health insurance options.
Workplace and culture
Syntronic offers an innovative, collaborative, and inclusive working environment. We believe in the notion “choose a job you love, and you will never have to work a day in your life.” Our team of creative out-of-the-box thinkers consists of motivated engineers from all walks of life with extensive experience.
Ideas, creativity, and new perspectives flow freely in our professional environment. We are convinced that the best results are achieved in an environment where people lift each other up and help each other grow. At Syntronic, we believe that excellence can be achieved when great minds work together.
About Syntronic
Syntronic is a global design house on the frontline of new technology. Our areas of expertise are advanced product and system development, production, and aftermarket services in the telecom, automotive, industrial, and medtech sectors.