AI and Machine Learning Integration for Edge Devices
Project scope
Categories
Cloud technologies Security (cybersecurity and IT security) Information technology Machine learning Artificial intelligenceSkills
nvidia jetson codebase machine learning real time data edge computing tensorflow decision making prototyping artificial intelligenceThe project aims to integrate AI and Machine Learning (ML) models into edge devices to enable real-time data processing and decision-making. This involves researching AI/ML concepts and edge computing, designing and prototyping AI/ML models, and deploying these models on edge devices such as Raspberry Pi or NVIDIA Jetson Nano. The project will allow learners to apply classroom knowledge in AI, ML, and edge computing to a practical scenario, enhancing their understanding of real-time data processing. The team will also gain hands-on experience with tools like TensorFlow Lite and Edge TPU, and will be responsible for training, optimizing, and testing the models for performance and accuracy.
- A fully functional AI/ML model deployed on edge devices.
- A prototype demonstrating real-time data processing and decision-making.
- Comprehensive documentation including the codebase, user manual, and a final report detailing findings and recommendations.
- A presentation summarizing the project goals, process, and outcomes.
Students will have access on a weekly basis to leadership in the company and will have a SPOC to post any questions to.
Supported causes
Industry, innovation and infrastructureAbout the company
Quote Control Ltd. works with small to medium sized enterprise Shippers and Freight Forwarders to reduce errors and streamline communications up front, enabling them to execute the first time.
Our Vision: Is to enable small to medium logistics operators to compete on a global scale by giving them access to technology typically only available to large multinationals.
Our Mission: We are fostering the evolution of logistics with innovative technologies that enhance efficiency, optimize performance, and maximize yield.
We are very early and working on our MVP. We have alot of ideas and want to be able to offer products people can trust with their most confidential information. Right now, we are an open book.
Portals
