{'fraction_non_alphanumeric': 0.02680565897244974, 'fraction_numerical': 0.004467609828741623, 'mean_word_length': 5.222222222222222, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Watcher ─ Sharing context information in everyday life

We present the Context Watcher, a mobile application that enables mobile phone users to easily and unobtrusively share personal context data such as their location, heart rate, speed, or view, with their mutual consent. Not only can the data be shared, it can also be used as input for information services, to adapt applications to the context, or to automatically derive daily patterns and situational information, such as ‘meeting with a supervisor’, ‘is a regular visitor’ or ‘having the best condition of all your friends’. The application is built atop of the MobiLife context management framework, a generic approach enabling context discovery, exchange and reasoning. In the context management framework, different entities, context providers, are exposed to and interact via the internet. The context management framework and its principles will be discussed in detail, as well as the different context providers that play a role in the Context Watcher application. The Context Watcher has a large user base of 100+ users, some of which are 24x7 power-users taking the Context Watcher wherever they go, enabling the research on daily patterns and situations to work with real-life data, resulting in powerful algorithms and better understanding of context and context-awareness.