{'fraction_non_alphanumeric': 0.021780909673286355, 'fraction_numerical': 0.0, 'mean_word_length': 5.2730923694779115, '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}}
The Smart-Condo: Optimizing Sensor Placement for Indoor Localization

The Smart-Condo is a hardware/software platform that aims to support and assist an individual in performing a variety of everyday tasks within his/her living space. The key to achieving this goal is being able to recognize the individual's general activities in real-time, without impeding these activities or compromising privacy. Since location and movement constitute meaningful evidence for many everyday tasks (e.g., presence in the bathroom correlates with personal hygiene activities), we are motivated to develop an efficient, accurate, and noninvasive occupant-localization method. To this end, we propose a methodology for planning the deployment of an array of privacy-respecting binary motion sensors. In particular, given the geometric constraints of the deployment space, we generate a model of indoor mobility patterns typical for a single occupant. We then use this model as the basis for a specific optimization problem: maximizing a measure of how well the frequently-visited areas of the living space are covered by a number of sensors, subject to a cardinality constraint on this number. We argue this optimization objective is a good surrogate for maximizing localization accuracy, and prove that it bears exploitable properties that make it receptive to a simple optimization routine. As a result, we obtain sensor configurations with localization accuracy superior to that achievable with the same number of sensors placed manually or randomly in the same environment.