Abstract:
The disclosure relates to adaptive advertisements that embedded devices may discover and use to connect to host devices. In particular, host devices may generally transmit multiple advertisements to signal a willingness to host one or more embedded devices, which may selectively process the advertisements to adaptively attach to a particular host device according to properties associated with the host device and/or requirements associated with the embedded devices. Furthermore, the host devices may have overload thresholds that control whether the host devices should be “discoverable” such that the advertisements may be dynamically adjusted (or suspended) according to current load status and connected embedded devices may be redirected to another target host device to shed load when the current load status exceeds the overload threshold.
Abstract:
The disclosure generally relates to mobile payments using proximity-based peer-to-peer (P2P) communication and an intent-to-pay gesture. In particular, a mobile device may detect a distinctive intent-to-pay gesture from one or more signals generated with one or more sensors on the mobile device. For example, the signals may indicate that the mobile device was gestured against a passive target that may resonate to indicate that the intent-to-pay gesture was made. The mobile device may then receive transaction details over a proximal P2P connection in response to detecting the intent-to-pay gesture and send a message over the proximal P2P connection to complete the mobile payment in response to receiving an input confirming the transaction details. Furthermore, the passive target may be constructed to produce a distinct resonant response that can be used to identify the passive target (e.g., using a microphone on the mobile device).
Abstract:
Disclosed are methods and systems for authenticating a key exchange between a first peer device and a second peer device. In an aspect, the first peer device sends federated login credentials of a user and a first identifier to a first federated login provider, receives a first authentication response from the first federated login provider, receives a second authentication response from the second peer device, authenticates the second authentication response with a second federated login provider, sends the first authentication response to the second peer device, receives an acknowledgment from the second peer device indicating that the second peer device has authenticated the first authentication response with the federated login provider, sends an acknowledgment to the second peer device indicating that the first peer device has authenticated the second authentication response, and authenticates the key exchange based on the acknowledgment from the second peer device.
Abstract:
In an embodiment, an apparatus receives report(s) of raw motion data detected in IoT environment, and also receives report(s) indicating user-initiated event(s) detected by a set of IoT devices within the IoT environment. The apparatus scans the raw motion data within a threshold period of time preceding particular detected user-initiated events to identify motion sequence(s) within the IoT environment that occurred during the threshold period of time. Certain motion sequence(s) are correlated with user-initiated event(s) based on a confidence level that the user-initiated event(s) will follow the motion sequence(s). Upon detection of the motion sequence(s) at some later point in time, the correlated event(s) is preemptively triggered without user interaction.
Abstract:
In an embodiment, a connection is established between first and second Internet of Things (IoT) devices. After a determination is made to execute a proximity detection procedure, the second IoT device outputs an audio emission and a data packet at substantially the same time. The first IoT device detects the audio emission via a microphone and receives the data packet. The first IoT device uses correlation information to correlate the detected audio emission with the data packet, whereby the correlation information is contained in the detected audio emission, the data packet or both. The first IoT device uses the correlation between the detected audio emission and the data packet to calculate a distance estimate between the first and second IoT devices.