{'fraction_non_alphanumeric': 0.04012841091492777, 'fraction_numerical': 0.0, 'mean_word_length': 5.704301075268817, '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}}
WiFi Vision: Sensing, Recognition, and Detection With Commodity MIMO-OFDM WiFi

Indoor human sensing, recognition, and detection, as key enablers of building smart environments, such as smart home, smart retail, and smart museum, have gained tremendous attention in recent years. Compared with traditional vision-based and wearable sensor-based solutions, radio-frequency (RF)-based approaches are more desirable with the contactless and nonline-of-sight nature. Among all RF-based approaches, WiFi-based approaches have been the focus of many researchers because of the ubiquitous availability and cost efficiency. In this article, we present a survey of recent advances in WiFi vision problems, i.e., sensing, recognition, and detection by utilizing the channel state information (CSI) of the commodity WiFi devices. We focus on nine key applications of smart environments, including WiFi imaging, vital sign monitoring, human identification, gesture recognition, gait recognition, daily activity recognition, fall detection, human detection, and indoor positioning. Such a survey can help readers have an overall understanding of sensing, recognition, and detection with commodity WiFi, and thus expedite the development of smart environments.