Abstract: Systems and methods provide for improving the accuracy of a location system. The location system can capture partial phase vector data from one or more access points (APs). The location system can capture associated data associated with the partial phase vector data across multiple dimensions, such as identity data of the APs and client devices generating the partial phase vector data and frequency band data, location data, a time and date, and other data associated with the partial phase vector data. The location system can determine correlation data across the multiple dimensions using the first partial phase vector data and the associated data. The location system can a cause of the partial phase vector data based on the correlation data. The location system can perform one or more remediation actions based on the cause of the partial phase vector data.

Abstract: Location-based, context-aware challenge-response authentication may be provided. First, a challenge may be provided to a user. The challenge may be based on a context corresponding to the user. The context corresponding to the user may comprise a location of a device associated with the user within an environment. Next, in response to providing the challenge, a response to the challenge may be received from the user. Then, in response to receiving the response to the challenge, it may be determined that the response is a correct answer to the challenge. In response to determining the response is the correct answer, a privilege may be provided to the user.

Abstract: Location-based, context-aware challenge-response authentication may be provided. First, a challenge may be provided to a user. The challenge may be based on a context corresponding to the user. The context corresponding to the user may comprise a location of a device associated with the user within an environment. Next, in response to providing the challenge, a response to the challenge may be received from the user. Then, in response to receiving the response to the challenge, it may be determined that the response is a correct answer to the challenge. In response to determining the response is the correct answer, a privilege may be provided to the user.

Abstract: Systems and methods provide for improving the accuracy of a location system. The location system can capture partial phase vector data from one or more access points (APs). The location system can capture associated data associated with the partial phase vector data across multiple dimensions, such as identity data of the APs and client devices generating the partial phase vector data and frequency band data, location data, a time and date, and other data associated with the partial phase vector data. The location system can determine correlation data across the multiple dimensions using the first partial phase vector data and the associated data. The location system can a cause of the partial phase vector data based on the correlation data. The location system can perform one or more remediation actions based on the cause of the partial phase vector data.

Abstract: In one embodiment, a device determines that location accuracy performance of an indoor positioning system deployment is below a predefined threshold. The device obtains characteristic data for the indoor positioning system deployment. The device identifies, by using the characteristic data as input to a machine learning model, one or more contributing factors from the characteristic data for the location accuracy performance of the indoor positioning system deployment being below the predefined threshold. The device initiates a remediation action based on the identified one or more contributing factors for the location accuracy performance of the indoor positioning system deployment being below the predefined threshold.

Abstract: In one embodiment, a device determines that location accuracy performance of an indoor positioning system deployment is below a predefined threshold. The device obtains characteristic data for the indoor positioning system deployment. The device identifies, by using the characteristic data as input to a machine learning model, one or more contributing factors from the characteristic data for the location accuracy performance of the indoor positioning system deployment being below the predefined threshold. The device initiates a remediation action based on the identified one or more contributing factors for the location accuracy performance of the indoor positioning system deployment being below the predefined threshold.