Abstract: An approach for the reliable detection of smartphones within vehicles. The cloud instructs two smartphones, which both detect an in-vehicle detection system, to report signals that reflect major sensor events, together with the timing using their respective clocks. By sending local clock timing and time-sensitive beacon content information to the cloud, the offset between the two smartphone clocks may be determined, thereby enhancing the reliability of the in-vehicle detection of the smartphones.

Abstract: The present disclosure relates to an acoustic position determination system that includes a mobile communication device and at least one base transmitter unit. The mobile communication device is configured to identify a peak in the received signal, and to de-convolve the signal with all codes that are relevant to the area in which the signal is received. A joint likelihood that a potential code is correct is formed by determining a likelihood based on a signal parameter such as signal-to-noise ratio and a likelihood based on time-of arrival information.

Abstract: The present disclosure relates to an acoustic position determination system that includes a mobile communication device and at least one base transmitter unit. The mobile communication device is configured to identify a peak in the received signal, and to de-convolve the signal with all codes that are relevant to the area in which the signal is received. A joint likelihood that a potential code is correct is formed by determining a likelihood based on a signal parameter such as signal-to-noise ratio and a likelihood based on time-of arrival information.

Abstract: An approach for the reliable detection of smartphones within vehicles. The cloud instructs two smartphones, which both detect an in-vehicle detection system, to report signals that reflect major sensor events, together with the timing using their respective clocks. By sending local clock timing and time-sensitive beacon content information to the cloud, the offset between the two smartphone clocks may be determined, thereby enhancing the reliability of the in-vehicle detection of the smartphones.

Abstract: The present disclosure relates to an acoustic position determination system that includes a mobile communication device and at least one base transmitter unit. The mobile communication device is configured to identify a peak in the received signal, and to de-convolve the signal with all codes that are relevant to the area in which the signal is received. A joint likelihood that a potential code is correct is formed by determining a likelihood based on a signal parameter such as signal-to-noise ratio and a likelihood based on time-of arrival information.

Abstract: An approach for the reliable detection of smartphones within vehicles. The cloud instructs two smartphones, which both detect an in-vehicle detection system, to report signals that reflect major sensor events, together with the timing using their respective clocks. By sending local clock timing and time-sensitive beacon content information to the cloud, the offset between the two smartphone clocks may be determined, thereby enhancing the reliability of the in-vehicle detection of the smartphones.

Abstract: The present disclosure relates to an acoustic position determination system that includes a mobile communication device and at least one base transmitter unit. The mobile communication device is configured to identify a peak in the received signal, and to de-convolve the signal with all codes that are relevant to the area in which the signal is received. A joint likelihood that a potential code is correct is formed by determining a likelihood based on a signal parameter such as signal-to-noise ratio and a likelihood based on time-of arrival information.

Abstract: The present disclosure relates to an acoustic position determination system that includes a mobile communication device and at least one base transmitter unit. The mobile communication device is configured to identify a peak in the received signal, and to de-convolve the signal with all codes that are relevant to the area in which the signal is received. A joint likelihood that a potential code is correct is formed by determining a likelihood based on a signal parameter such as signal-to-noise ratio and a likelihood based on time-of arrival information.

Abstract: An approach for the reliable detection of smartphones within vehicles. The cloud instructs two smartphones, which both detect an in-vehicle detection system, to report signals that reflect major sensor events, together with the timing using their respective clocks. By sending local clock timing and time-sensitive beacon content information to the cloud, the offset between the two smartphone clocks may be determined, thereby enhancing the reliability of the in-vehicle detection of the smartphones.

Abstract: An approach for product localization is described that includes detecting one or more movement activities of a user in an indoor environment, and determining a respective position for each of the one or more movement activities using a sensor associated with the user. The approach further includes identifying one or more stoppage locations from the detected one or more movement activities, and receiving a list of one or more purchased items purchased by the user in the indoor environment. Finally, the approach further includes correlating at least one of the more purchased items with at least one of the one or more stoppage locations, and predicting the location of the one or more purchased items based on the correlating.

Abstract: The present disclosure relates to an acoustic position determination system that includes a mobile communication device and at least one base transmitter unit. The mobile communication device is configured to identify a peak in the received signal, and to de-convolve the signal with all codes that are relevant to the area in which the signal is received. A joint likelihood that a potential code is correct is formed by determining a likelihood based on a signal parameter such as signal-to-noise ratio and a likelihood based on time-of arrival information.