A unified presence detection and prediction platform that is privacy aware is described. The platform is receives signals from plural sensor devices that are disposed within a premises. The platform produces profiles of entities based on detected characteristics developed from relatively inexpensive and privacy-aware sensors, i.e., non-video and non-audio sensor devices. The platform using these profiles and sensor signals from relatively inexpensive and privacy-aware sensors determines specific identification and produces historical patterns. Also described are techniques that allow users (persons), when authorized, to control remote devices/systems generally without direct interaction with such systems merely by the systems detecting and in instances predicting the specific presence of an identified individual in a location within the premises.

In a general aspect of the examples described, motion is detected based on bi-directional channel sounding. In an example, a first set of channel information is obtained from a first device. The first set of channel information is based on a first set of wireless signals transmitted from a second device through a space at a first time in a timeframe. A second set of channel information is obtained from the second device. The second set of channel information is based on a second set of wireless signals transmitted from the first device through the space at a second time in the timeframe. The first and second sets of channel information are analyzed to detect a category of motion or a location of detected motion in the space during the timeframe.

In a general aspect, a method is presented for detecting a location of motion using wireless signals that propagate along two or more paths of a wireless communication channel. The method includes storing a set of eigenvectors derived from first motion-sensing data associated with a first time frame. The first motion-sensing data is associated with a first motion-sensing topology of a wireless mesh network. The method also includes obtaining a motion vector based on wireless signals transmitted between access point nodes in the wireless mesh network during a second, subsequent time frame. The wireless mesh network operates in a second, distinct motion-sensing topology during the second time frame. The motion vector is compared with the respective eigen vectors, and a probability vector is generated based on the comparison. A location of the motion of the object during the second time frame is determined based on the probability vector.

In a general aspect, a method is presented for detecting a location of motion using wireless signals in a wireless mesh network that includes leaf nodes. The method includes obtaining motion-sensing data based on wireless signals exchanged on wireless links in a wireless mesh network including a plurality of nodes. The plurality of nodes includes a first access point (AP) node, one or more other AP nodes, and leaf nodes. The method also includes identifying, based on the motion-sensing data, the first AP node as an estimated location of motion of an object. The method additionally includes generating a likelihood data structure comprising likelihood values assigned to respective nodes of the plurality of nodes in response to the first AP node being identified as the estimated location of motion. A location of the motion of the object is determined based on the likelihood data structure.

A moving device which can move autonomously in an environment is provided and includes an image capturing component, a processor, a moving component, and a signal transmitter. The image capturing component captures environmental feature information of the environment during moving process of the moving device. The processor identifies a first location of at least one electronic apparatus in the environment according to the environmental feature information and predetermined feature information corresponding to the at least one electronic apparatus and determines a second location corresponding to the first location according to a remote signal. The moving component causes the moving device to move to the second location. The signal transmitter controlled by the processor. The signal transmitter sends a first signal from the second location to the at least one electronic apparatus to control the operation of the at least one electronic apparatus.

Systems and methods for adjusting a broadcast pattern of an intrusion detector are provided. Such systems and methods can include a microwave sensor of the intrusion detector broadcasting a detection signal into a secured area in the broadcast pattern, a communication module of the intrusion detector wirelessly receiving a signal adjustment command from a remote device, and a processor and executable control software of the intrusion detector parsing the signal adjustment command and instructing a signal adjuster of the intrusion detector to adjust a sensitivity of the microwave sensor or an amplitude of the detection signal to alter the broadcast area of the broadcast pattern based on information contained in the adjustment command.

In a general aspect, a method is presented for detecting a location of motion using wireless signals and topologies of wireless connectivity. The method includes obtaining motion-sensing data from access point (AP) nodes of a wireless mesh network. The motion-sensing data is based on wireless signals transmitted between respective pairs of the AP nodes. The method additionally includes identifying a motion-sensing topology of the wireless mesh network. The motion-sensing topology is based on tags assigned to respective AP nodes, each tag indicating a connected state of a respective AP node. The method further includes generating a probability vector based on the motion-sensing data and the motion-sensing topology. The probability vector includes values that represent probabilities of motion of an object at respective AP nodes. A location of the motion of the object is determined based on the probability vector.

Systems and methods for detecting a presence of a target such as a vehicle, an animal, a person, or another object in a monitored area without the use of sensors, are provided. Multiple RF field anomaly detection nodes may be spaced through the monitored area and connected, such as in a mesh network. The RF field anomaly detection nodes may include radio transceivers that communicate with one another and which monitor a signal strength of received signals. The nodes may compare the signal strengths to expected strength values. As a target enters a portion of the monitored area, the dielectric properties of the target cause at least one signal strength of at least one received signal to change. The RF field anomaly detection nodes may detect this change and trigger a further action or human readable alert corresponding to the presence of the target.

In a general aspect, a method is presented for detecting a location of motion using wireless signals and topologies of wireless connectivity. The method includes obtaining motion-sensing data from access point (AP) nodes of a wireless mesh network. The motion-sensing data is based on wireless signals transmitted between respective pairs of the AP nodes. The method additionally includes identifying a motion-sensing topology of the wireless mesh network. The motion-sensing topology is based on tags assigned to respective AP nodes, each tag indicating a connected state of a respective AP node. The method further includes generating a probability vector based on the motion-sensing data and the motion-sensing topology. The probability vector includes values that represent probabilities of motion of an object at respective AP nodes. A location of the motion of the object is determined based on the probability vector.

The present invention relates to radio frequency based sensing based on multiple communication technologies (476, 486). Radio frequency based sensing is performed by a single-channel communication technology (476) in order to detect sensing events. A single-channel confidence level (470) for detecting a sensing event by performing radio frequency based sensing by the single-channel communication technology (476) is determined. Upon detecting that the single-channel confidence level (470) is above a first single-channel threshold level (474) and below a second single-channel threshold level (472) which is higher than the first single-channel threshold level (474), a multi-channel communication technology (486) for performing radio frequency based sensing is selected based on one or more radio frequency system criteria, and radio frequency based sensing is performed by the multi-channel communication technology (486).