The Context Recognition Network (CRN) Toolbox permits fast implementation of activity and context recognition systems. It utilizes parameterizable and reusable software components and provides a broad set of online algorithms for multi-modal sensor input, signal processing, and pattern recognition. It features mechanisms for distributed processing and support for mobile and wearable devices. We present different case studies indicating its merit in industrial projects, as educational tool for students, and processing engine in activity recognition demonstrators. Moreover, we summarize user evaluation results.