This repository contains the implementation of an activity recognition system using Conditional Random Fields (CRF) to extract high-level activities from robotic sensor data. The extracted activities can be utilized for event log generation in the context of process mining.
Activity recognition is a critical component of systems that rely on understanding sensor data to infer high-level behaviors. This project focuses on leveraging Conditional Random Fields (CRFs) to model sequential dependencies in sensor data for accurate activity recognition.
The recognized activities are used to generate event logs, which are essential inputs for process mining to analyze robotic systems.
Create a virtual environment
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
Install dependencies
pip install -r requirements.txt