Described in detail herein are methods and systems for estimating storage capacity of a storage unit disposed in a facility based on echoes detected by microphones. The microphones can detect sounds generated in the warehouse and reflected off the storage unit structures. The microphones detect the intensity of the sounds. The microphones can encode the sounds and the intensity of the sounds in time-varying electrical signals and transmit the time-varying electrical signals to a computing system. The computing system can decode the sounds and the intensity of the sounds from the time-varying electrical signals and estimate storage capacity of a storage unit from which the sounds reflected off of based on the intensity of the sounds.

In general, this disclosure describes location techniques for a mobile device. A mobile device may request permission from a server device to perform a ranging operation. Responsive to receiving an indication of allowance, the mobile device may output a first data packet via a radio signal, which is received by a beacon device that activates an ultrasonic transponder upon receipt of the first data packet. The mobile device then outputs a second data packet via an ultrasonic pulse. The beacon device receives the ultrasonic pulse and outputs a third data packet via a second radio signal that includes information identifying the beacon device. The mobile device calculates a time difference between outputting the ultrasonic pulse and receiving the second radio signal and determines its location based on the third data packet and the time difference.

Techniques for accurate, low-complexity, scalable indoor localization. Low-complexity anchor nodes generate acoustic beacon signals, which are passively detectable by a mobile device, which may be unmodified smartphones operating in an acoustic frequency range. The acoustic beacon signals are modulated via codes in a boundary band of audio and ultrasound frequencies, imperceptible to humans yet detectable via a voice microphone of an unmodified smartphone. An application on the mobile device passively captures the acoustic beacon signals and determines relative distances to the anchor nodes. Localization and distance update techniques, implemented on the mobile device and/or a remote server, determines and updates in real-time the location of the mobile device. The system may be scalable to support any number of mobile devices. Based on the tracked location, the indoor localization system may provide indoor location-based-services (LBS) to the mobile devices, and transmit to the mobile device information relevant to its location.

Techniques for accurate, low-complexity, scalable indoor localization. Low-complexity anchor nodes generate acoustic beacon signals, which are passively detectable by a mobile device, which may be unmodified smartphones operating in an acoustic frequency range. The acoustic beacon signals are modulated via codes in a boundary band of audio and ultrasound frequencies, imperceptible to humans yet detectable via a voice microphone of an unmodified smartphone. An application on the mobile device passively captures the acoustic beacon signals and determines relative distances to the anchor nodes. Localization and distance update techniques, implemented on the mobile device and/or a remote server, determines and updates in real-time the location of the mobile device. The system may be scalable to support any number of mobile devices. Based on the tracked location, the indoor localization system may provide indoor location-based-services (LBS) to the mobile devices, and transmit to the mobile device information relevant to its location.

Systems and methods for identifying device location are provided. The method can include providing, by a mobile computing device, at least a first ultrasonic signal to a first and a second self-organizing beacon device. The method can include receiving, by the mobile computing device, a first radio frequency signal including the location of the first beacon device and a second radio frequency signal including the location of the second beacon device. The method can further include determining a first time-of-flight associated with the first beacon device and a second time-of-flight associated with the second beacon device. The method can include determining a location of the mobile computing device based at least in part on the first time-of-flight, the second time-of-flight, the location of the first beacon device, and the location of the second beacon device.

Disclosed are systems and methods for identifying a user of a smart object inside a moving vehicle and as well as automatic detection and calculation of a time and a location when and where the vehicle has been parked. The systems and methods are capable to enable the identification of the user of an object inside a moving entity based on the orientation of the object to be localized as well as the movement direction of the moving entity.

In one embodiment, a method includes retrieving positions P1, P2 and P3 of a first, second and third attendee position, respectively, P1, P2, P3 being determined based on detecting speech from the first, second and third attendee position, respectively, by a first microphone array of a first collaboration apparatus, retrieving distances D1, D2 and D3 from the first, second and third attendee position, respectively, to a second microphone array of a second collaboration apparatus, D1, D2, D3 being determined based on detecting speech from the first, second and third attendee position, respectively, by the second microphone array, P1 and D1 defining a circle C1 centered at P1 with radius D1, P2 and D2 defining a circle C2 centered at P2 with radius D2, P3 and D3 defining a circle C3 centered at P3 with radius D3, calculating a position P4 based on a proximity of a circumference of C1, C2 and C3.

A positioning system comprising a processing system (7; 9) configured to receive a first position estimate for a mobile device (7), and to receive data representative of an acoustic signal received by the mobile device (7) from one of a plurality of acoustic transmitter units (2, 3, 4, 5). For each of the acoustic transmitter units (2, 3, 4, 5), the processing system (7; 9) determines spatial likelihood data representative of a likelihood of the received acoustic signal having been transmitted by the respective acoustic transmitter unit by comparing a time-of-flight range value with a geometric distance value, representative of a distance between the acoustic transmitter unit and the first position estimate. The processing system (7; 9) processes the spatial likelihood data to identify a subset of the acoustic transmitter units, and processes information relating to the positions of the acoustic transmitter units in the identified subset and/or relating to the acoustic signals transmitted by the acoustic transmitter units in the identified subset, to determine a second position estimate for the mobile device (7).

A positioning system comprising a processing system (7; 9) configured to receive a first position estimate for a mobile device (7), and to receive data representative of an acoustic signal received by the mobile device (7) from one of a plurality of acoustic transmitter units (2, 3, 4, 5). For each of the acoustic transmitter units (2, 3, 4, 5), the processing system (7; 9) determines spatial likelihood data representative of a likelihood of the received acoustic signal having been transmitted by the respective acoustic transmitter unit by comparing a time-of-flight range value with a geometric distance value, representative of a distance between the acoustic transmitter unit and the first position estimate. The processing system (7; 9) processes the spatial likelihood data to identify a subset of the acoustic transmitter units, and processes information relating to the positions of the acoustic transmitter units in the identified subset and/or relating to the acoustic signals transmitted by the acoustic transmitter units in the identified subset, to determine a second position estimate for the mobile device (7).

A computer input system includes a mouse including a housing having an interior surface defining an internal volume and a sensor assembly disposed in the internal volume. A processor is electrically coupled to the sensor assembly and a memory component having electronic instructions stored thereon that, when executed by the processor, causes the processor to determine an orientation of the mouse relative to a hand based on a touch input from the hand detected by the sensor assembly. The mouse can also have a circular array of touch sensors or lights that detect hand position and provide orientation information to the user.