Embodiments described herein provide for system and methods to crowdsource the location of wireless devices and accessories that lack a connection to a wide area network. One embodiment provides for a data processing system configured to perform operations comprising loading a user interface on an electronic device, the user interface to enable the determination of a location of a wireless accessory that is associated with the electronic device, generating a set of public keys included within a signal broadcast by the wireless accessory, the signal broadcast during a first period, sending the set of public keys to a server with a request to return data that corresponds with a public key in the set of public keys, decrypting the location data using a private key associated with the public key, and processing the location data to determine a probable location for the wireless accessory.

A system, method and computer application to log signal egress (leakage signal) readings from a test instrument during a “walkout” mode where the technician and test instrument have left a vehicle and troubleshooting is being performed on foot. A unique troubleshooting and discovery dataset is created and capable of revealing problems not previously discoverable using vehicle mounted test instruments. In addition, the dataset may be used for quality control and other purposes such as e.g., providing a report or mapping of the path the technician used during the troubleshooting process. Augmented reality features may also be displayed on the technician's mobile device to facilitate finding the source of one or more leaks.

A container includes a surface and a first resonance portion. The surface defines a volume of the container, and the first resonance portion includes an assembly of three-dimensional (3D) carbon-containing structures printed on the surface of the container using one or more first carbon-based inks. The first resonance portion is configured to indicate a presence of an item within the container by resonating at one or more predetermined frequencies in response to an electromagnetic radiation ping associated with a user device located a distance from the container. In some implementations, the container may include a second resonance portion including an assembly of 3D carbon-containing structures printed on the surface of the container using one or more second carbon-based inks, the one or more second carbon-based inks being different than the one or more first carbon-based inks.

An emergency notification system and method includes a mobile computing device having live transmissible location data and activation means for selectably transmitting an emergency signal, such as at least one touch activatable emergency button provided through a touchscreen display of the mobile computing device. When the user activates an emergency button, GPS location data from a GPS receiver of the mobile computing device may be automatically acquired. A video and/or audio recording may also be generated using a camera of the mobile computing device. The recorded video and location data is automatically transmitted from the mobile computing device to a remote data storage location and to an administrator who may provide emergency assistance to the user.

There are proposed a method for identifying users of a wireless communication device and a system for implementation thereof. The method includes the steps of receiving a MAC address of the device by a subsystem of the system and creating instructions that, when executed, cause the device to launch a subprogram in an application, A user then starts working with the subprogram. A subprogram user identifier or reference thereto is provided in the user's identification subsystem. A reference to the device MAC address associated with the subprogram user identifier is passed to the user identification subsystem, and the user identification subsystem saves the reference to the user identifier and the reference to the device MAC address associated therewith. The proposed method and device allow for simplifying the procedure for identifying the user.

An embodiment relates to a trash collection device comprising a trash receptacle with a unique identification and an opening to receive a class of trash; an identification scanner for recognizing a user; a trash item counter; a fill level sensor; a display configured to interact with the user; a compactor; a solar panel configured to charge a battery; a data communicator configured to communicate date to a cloud storage; a processor configured to generate incentive for the user; wherein the trash collection device is configured to be modular and configurable to connect with another similar trash collection device to enable to collect additional trash class and is configured to interact with each other through a common software. The device, method and system are further used to generate recycling analytics by using the stored data to provide incentives to users and to facilitate planning of downstream operations.

The system comprises a plurality of sensor systems, a counter drone, and a processor. A sensor system of the plurality of sensor systems comprises one or more sensors that are connected to a network. The counter drone is connected to the network. The processor is configured to receive an indication of a potential target from the plurality of sensor systems; generate a fused data set for the potential target, determine whether the potential target comprises the threat drone based at least in part on the fused data set; and in response to determining that the potential target comprises the threat drone, provide counter drone instructions to the counter drone.

Systems, methods, devices, computer readable media, and other various embodiments are described for location management processes in wearable electronic devices. Performance of such devices is improved with reduced time to first fix of location operations in conjunction with low-power operations. In one embodiment, low-power circuitry manages high-speed circuitry and location circuitry to provide location assistance data from the high-speed circuitry to the low-power circuitry automatically on initiation of location fix operations as the high-speed circuitry and location circuitry are booted from low-power states. In some embodiments, the high-speed circuitry is returned to a low-power state prior to completion of a location fix and after capture of content associated with initiation of the location fix. In some embodiments, high-speed circuitry is booted after completion of a location fix to update location data associated with content.

Embodiments described herein provide for system and methods to crowdsource the location of wireless devices and accessories that lack a connection to a wide area network. One embodiment provides for a data processing system configured to perform operations comprising loading a user interface on an electronic device, the user interface to enable the determination of a location of a wireless accessory that is associated with the electronic device, generating a set of public keys included within a signal broadcast by the wireless accessory, the signal broadcast during a first period, sending the set of public keys to a server with a request to return data that corresponds with a public key in the set of public keys, decrypting the location data using a private key associated with the public key, and processing the location data to determine a probable location for the wireless accessory.

Systems, and methods for predicting that a user is located at a labeled place corresponding to a point of interest. A server computer accesses historical data comprising location data, and wireless network data collected from a plurality of client devices of a plurality of users over a period of time. For one or more labeled places, the data points corresponding to one of the users being located at the labeled place are identified. A labeled dataset is generated by tagging the identified data points with a label corresponding to the corresponding labeled place. A machine learning model is trained on the labeled dataset, so that when current location data are receiving from a client device of a user, it is possible to determine, using the trained machine learning model, whether the user is located at one of the one or more labeled places.