Abstract: Technologies for attestation techniques, systems, and methods for determining an individual's movement are provided. The individual's movement is determined by passive indoor positioning technology using channel state information (CSI). A first set of data associated with an impulse or frequency response determined using channel state information (CSI) may be received from a Wireless access point located in proximity to a monitored space. A second set of data may also be received from an Internet of Things (IoT) device located in proximity to the monitored space. The first set of data may be compared to the second set of data. A profile database may be updated to replace the first set of data with the second set of data when the first and second sets of data are different.

Abstract: A wireless motion detection system is provided which uses a sharp band-stop and low-pass filters to reject unwanted low and high frequency components of a signal in the CSI. A gap in the frequency domain is caused by taking the absolute value of the signal when using the absolute value of channel matrix H? for motion detection. A sharp band-stop (notch) filter is used to reject any unwanted signals that have significant components in this gap. A low-pass filter is used to reject all unwanted signal after the motion highest frequency.

Abstract: Systems and methods are provided for human activity analysis and localization using channel state information (CSI). A streamlined data processing and feature extraction approach that addresses concept drifts for time series data is provided. Data obtained from CSI or any other mechanism is used to estimate the wireless channel between two different wireless nodes (e.g., an access point (AP) and an associated station (STA)), and can be used to train a robust system capable of performing room level localization. A phase and magnitude augmented feature space along with a standardization technique that is little affected by drifts is also used.

Abstract: The systems and method proposed herein aim to identify a mobile device or devices worn by an individual or a subject that has entered an area monitored by a passive motion detection system that uses wireless signals to sense motion in the space. The system will collect as much signals as possible from both the devices worn by the individual and from the system performing the passive (device-free) motion detection for identifying the individual or person of interest. The individual or person of interest may be a user of a product or an intruder.

Abstract: Systems and methods for tracking activities of daily living (ADL) of a user are provided. The method monitors data from one or more internet of things (IoT) devices corresponding to one or more ADLs. The method further monitors data from an activity identification module. The data received is related to an ADL and includes one or more steps specific to the ADL. The data related to the ADL is stored in an activity logging database located in a memory and compared to an activity best practices (BP) database. A score that represents a compliance level is calculated based on the compared data. A response that corresponds the compliance level from a response database is executed.

Abstract: A method of utilizing Wi-Fi based passive motion detection to deliver targeted advertising through a smart TV is provided. The system uses an agent in connection with the wireless access point that the Smart TV uses to access the internet to make motion determinations. The CSI data of the access point is analyzed to identify if a user is present, if the user is stationary, the previous location of the user, and the activity the user is currently engaged in. An advertisement may be selected based on a last visited location and activity. Such advertisements may further be delivered to more engaged viewers when the advertiser pays a higher rate.

Abstract: An intelligent entrance detection system is provided where, primarily, any authorized or unauthorized entry to an area of a residential (or small industrial) unit covered by a wireless network is automatically detected from active off-the-shelf devices in that area. After the detection, an identification algorithm is employed to verify if this entry is a legal or illegal action. Based on this verification, either the routine smart home system is activated or a hazardous monitoring period begins to further investigate the suspicious event. If the illegal entrance is confirmed during the hazardous monitoring period, the owner of the property is informed through an intruder alarm protocol. In this invention, all of the analytic and processing steps, including entrance detection, owner identification, and device-free authority verification are designed based on monitoring and quantification of changes in surrounding wireless signals originated by human or object movements within the sensing area.

Abstract: Systems and methods for detecting and monitoring human breathing, respiration, and heart rate using statistics about the wireless channel between two or more connected devices. A user is monitored for identifying patterns in the user's behavior that may allow the system to alert a caregiver to deviations in the user behavior that may be indicative of a potential issue, such as depression. A presence may further detected in a sensing area through the detection of spectral components in the breathing frequency range of comprises user includes transforming phase difference between spatial streams and amplitude of the samples representing frequency response of the channel for any frequency value into frequency domain to perform frequency analysis. Statistical analysis may be performed on the frequency space provided by the transformation. Micro motions may also be detected by detecting presence in a sensing area through the detection of spectral components in the micro motion frequency range.

Abstract: Device-free localization for smart indoor environments within an indoor area covered by wireless networks is detected using active off-the-shelf-devices would be beneficial in a wide range of applications. By exploiting existing wireless communication signals and machine learning techniques in order to automatically detect entrance into the area, and track the location of a moving subject within the sensing area a low cost robust long-term tracking system can be established. A machine learning component is established to minimize the need for user annotation and overcome temporal instabilities via a semi-supervised framework. After establishing a robust base learner mapping wireless signals to different physical locations from a small amount of labeled data; during its lifetime, the learner automatically re-trains when the uncertainty level rises significantly. Additionally, an automatic change-point detection process is employed setting a query for updating the outdated model and the decision boundaries.

Abstract: Technologies for attestation techniques, systems, and methods for determining an individual's movement are provided. The individual's movement is determined by passive indoor positioning technology using channel state information (CSI). A first set of data associated with an impulse or frequency response determined using channel state information (CSI) may be received from a Wireless access point located in proximity to a monitored space. A second set of data may also be received from an Internet of Things (IoT) device located in proximity to the monitored space. The first set of data may be compared to the second set of data. A profile database may be updated to replace the first set of data with the second set of data when the first and second sets of data are different.

Abstract: Systems, and methods for selecting advertisements based on party size and/or engagement are provided. An Internet-connected media display device may be detected as displaying media. An up-to-date party size in a monitored space may be determined based on frequency response data by a wireless access point located close to the space. An up-to-date engagement level may also be determined with respect to each individual in the space based on frequency response data by the wireless access point. An advertisement database may be filtered for a qualifying advertisement based on the identified party size and engagement levels.

Abstract: Systems and methods of using a robot to train the system for motion detection are provided. A simple robot can be put in a room and programmed not to move except in accordance with specific programmed command. Such commands may be sent to the robot regarding movement(s) at a certain rate than could be seen in the response to a channel. A data set may be built over time, where the robot may be programmed to move such that the robot does change at specific times in duration and amount. Such robot motion may also be iterated. The algorithm records the impulse response changes associated with the robot changes and a database may be built based on such recorded and associated changes.

Abstract: Systems and methods for tracking activities of daily living (ADL) of a user are provided. The method monitors data from one or more internet of things (IoT) devices corresponding to one or more ADLs. The method further monitors data from an activity identification module. The data received is related to an ADL and includes one or more steps specific to the ADL. The data related to the ADL is stored in an activity logging database located in a memory and compared to an activity best practices (BP) database. A score that represents a compliance level is calculated based on the compared data. A response that corresponds the compliance level from a response database is executed.

Abstract: Systems and methods for detecting and monitoring human breathing, respiration, and heart rate using statistics about the wireless channel between two or more connected devices. A user is monitored for identifying patterns in the user's behavior that may allow the system to alert a caregiver to deviations in the user behavior that may be indicative of a potential issue, such as depression. A presence may further detected in a sensing area through the detection of spectral components in the breathing frequency range of comprises user includes transforming phase difference between spatial streams and amplitude of the samples representing frequency response of the channel for any frequency value into frequency domain to perform frequency analysis. Statistical analysis may be performed on the frequency space provided by the transformation. Micro motions may also be detected by detecting presence in a sensing area through the detection of spectral components in the micro motion frequency range.

Abstract: A method of utilizing Wi-Fi based passive motion detection to deliver targeted advertising through a smart TV is provided. The system uses an agent in connection with the wireless access point that the Smart TV uses to access the internet to make motion determinations. The CSI data of the access point is analyzed to identify if a user is present, if the user is stationary, the previous location of the user, and the activity the user is currently engaged in. An advertisement may be selected based on a last visited location and activity. Such advertisements may further be delivered to more engaged viewers when the advertiser pays a higher rate.

Abstract: Device-free localization for smart indoor environments within an indoor area covered by wireless networks is detected using active off-the-shelf-devices would be beneficial in a wide range of applications. By exploiting existing wireless communication signals and machine learning techniques in order to automatically detect entrance into the area, and track the location of a moving subject within the sensing area a low cost robust long-term tracking system can be established. A machine learning component is established to minimize the need for user annotation and overcome temporal instabilities via a semi-supervised framework. After establishing a robust base learner mapping wireless signals to different physical locations from a small amount of labeled data; during its lifetime, the learner automatically re-trains when the uncertainty level rises significantly. Additionally, an automatic change-point detection process is employed setting a query for updating the outdated model and the decision boundaries.

Abstract: Within several applications the ability to localize an individual within an environment is beneficial. However, existing indoor localization approaches depend upon at least one of two assumptions. First, the subject(s) localization is achieved by localizing a wireless device carried by the subject and second, wireless fingerprints are established for the localization via a site survey being performed before a system can actually localize the subject(s). However, in many application scenarios, neither of the above two assumptions are true, namely that the user is not carrying an active wireless device or that the site has been surveyed. Accordingly, embodiments of the invention provide for subject localization by a dynamic calibration of wireless signals between a receiver and a transmitter, where neither the receiver or transmitter are associated with an electronic device carried or worn by the subject.

Abstract: A wireless signal-based sensing system is provided. The system includes a plurality of devices, each device capable of sending and receiving wireless signals to create a sensing area. The system also includes at least one connection mechanism to enable at least one of the devices to connect to an application, and at least one analytics application for processing measurements of wireless signals obtained from the sensing area.

Abstract: Technologies for attestation techniques, systems, and methods for determining an individual's movement are provided. The individual's movement is determined by passive indoor positioning technology using channel state information (CSI). A first set of data associated with an impulse or frequency response determined using channel state information (CSI) may be received from a Wireless access point located in proximity to a monitored space. A second set of data may also be received from an Internet of Things (IoT) device located in proximity to the monitored space. The first set of data may be compared to the second set of data. A profile database may be updated to replace the first set of data with the second set of data when the first and second sets of data are different.

Abstract: An intelligent entrance detection system is provided where, primarily, any authorized or unauthorized entry to an area of a residential (or small industrial) unit covered by a wireless network is automatically detected from active off-the-shelf devices in that area. After the detection, an identification algorithm is employed to verify if this entry is a legal or illegal action. Based on this verification, either the routine smart home system is activated or a hazardous monitoring period begins to further investigate the suspicious event. If the illegal entrance is confirmed during the hazardous monitoring period, the owner of the property is informed through an intruder alarm protocol. In this invention, all of the analytic and processing steps, including entrance detection, owner identification, and device-free authority verification are designed based on monitoring and quantification of changes in surrounding wireless signals originated by human or object movements within the sensing area.