Gold Sentinel is seeking to enhance its radar sensor technology by developing AI models capable of accurately monitoring and interpreting human activities. The project aims to leverage radar sensors to detect and classify various human movements and activities in real-time. This initiative will allow learners to apply their knowledge of AI, machine learning, and signal processing to a practical scenario. The primary goal is to create a robust AI model that can differentiate between different activities such as walking, running, sitting, and standing. The project will focus on optimizing the model for accuracy and efficiency, ensuring it can be implemented in real-world applications. Learners will work on data preprocessing, feature extraction, model training, and validation, using datasets provided by Gold Sentinel.

The project will culminate in the development of a functional AI model capable of classifying human activities based on radar sensor data. Deliverables include a comprehensive report detailing the model development process, including data preprocessing techniques, model architecture, and performance metrics. Additionally, a presentation will be prepared to showcase the model's capabilities and potential applications. The final deliverable will be a documented codebase that can be used for further development or integration into existing systems.