The disclosure relates to a system for generating a status output based on sound emitted by an animal. The system comprising: a client (102), a server (104) and a database (106); the database (106) is accessible (107) by the server (104) and comprises historic sound data pertaining to the animal (302) or animals of the same type as the animal; the client (102) comprising circuitry (110) configured to: detect (202) sound emitted (308, 312) by the animal (302); record (204) the detected sound (308, 312); analyze (206) the recorded sound for detecting whether the sound (308, 312) comprises a specific sound characteristic out of a plurality of possible sound characteristics, wherein the sound characteristic includes at least one of intensity, frequency and duration of the detected sound; transmit (208), in response to detecting that the sound (308, 312) comprises the specific sound characteristic, the recorded sound to a server (104); the server (104) comprises circuitry (122) configured to: receive (210) the recorded sound; classify (212) the recorded sound by comparing one or more sound characteristics of the recorded sound with the historic sound data comprised in the database (106); generate (214) the status output based on the classification of the recorded sound. A method (200) for generating a status output based on sound emitted by an animal is also provided.

In accordance with one or more embodiments herein, a system for monitoring an individual within predetermined facilities 500 in order to determine whether there is a need for setting an alert is provided. The system 100 comprises: a personal module 200 to be worn by the monitored individual, the personal module 200 comprising at least one motion sensor 220; at least one node module 300, with which the personal module 200 is arranged to communicate; a storage means 320; and at least one processing device 210, 310, 160. The at least one processing device 210, 310, 160 may be arranged to: receive sensor data from the at least one motion sensor 220 in the personal module 200; determine whether the received sensor data indicates a specific alert state among a plurality of predetermined alert states, the alert states comprising at least a FALL alert state, to be used if a probable fall has been detected for the monitored individual, and an OUT OF BED alert state, to be used if it has been detected that the monitored individual is probably getting out of bed; determine the distance between the personal module 200 and the at least one node module 300; determine the location of the personal module 200 within the facilities 500 based at least on the determined distance together with information retrieved from the storage means 320 regarding the layout of the facilities 500 within which the monitoring of the individual takes place; and set an alert based at least on whether the received sensor data indicates an alert state and whether the determined location fulfils a predetermined location condition, indicating whether the individual is located in a certain room, such as e.g. the bedroom 530.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for machine learning for home understanding and notification. In one aspect, a method includes obtaining reference videos from a camera within a home, determining from the reference videos that a particular person routinely leaves the home with a particular object at a particular time of day, determining from a sample video from the camera within the home that the particular person appears to be leaving the home without the particular object at the particular time of day, and in response, providing a notification regarding the particular object.

A user, such as an elderly person, may be assisted by an assistance device in his or her caregiving environment that operates in conjunction with one or more server computers. The assistance device may execute a schedule of assistance actions where each assistance action is associated with a time and is executed at that time to assist the user. An assistance action may present an input request to a user, process a voice input of the user, and analyze the voice input to determine that the voice input corresponds to a negative response event, a positive response event, or a non-response event. Based on the categorization of one or more voice inputs as negative response events, positive response events, or non-response events, it may be determined to notify a caregiver of the user, for example where the user has not responded to a number of assistance actions.

The present disclosure is directed to systems and methods avoiding collisions by monitoring the presence and alertness of a person in a vehicle. The alertness of that person may be monitored by identifying actions performed by that person when an automated driving assistant is used in a vehicle. Systems and method consistent with the present disclosure may monitor the alertness of a person that is located in a driving position of a vehicle according to criteria associated with particular individuals or with criteria associated with specific protocols. When a system or method consistent with the present disclosure identifies that a person is not alert, a corrective action may be initiated that reduces likelihood of a collision.

A user, such as an elderly person, may be assisted by an assistance device in his or her caregiving environment that operates in conjunction with one or more server computers. The assistance device may execute a schedule of assistance actions where each assistance action is associated with a time and is executed at that time to assist the user. An assistance action may present an input request to a user, process a voice input of the user, and analyze the voice input to determine that the voice input corresponds to a negative response event, a positive response event, or a non-response event. Based on the categorization of one or more voice inputs as negative response events, positive response events, or non-response events, it may be determined to notify a caregiver of the user, for example where the user has not responded to a number of assistance actions.

In an example, the present invention provides an UWB and FMCW sensor apparatus, with an audio module and inertial motion module. The apparatus has at least three transceiver modules. Each of the transceiver modules has an antenna array to be configured to sense a back scatter of electromagnetic energy from spatial location of a zero degree location in relation to a mid point of the device through a 360 degrees range where each antenna array is configured to sense a 120 degree range. In an example, each of the antenna array has a support member, a plurality of receiving antenna, a receiver integrated circuit coupled to the receiving antenna and configured to receive an incoming rf signal and covert the incoming rf signal into a base band signal, and a plurality of transmitting antenna.

Systems and methods for improved personal monitoring systems and devices include the provision of sensor data from a personal monitoring device to a server system. The sensor device is provided to the server system at a first rate and subsequently analyzed by the server system. If the server system determines that a particular condition is met based on the sensor data the server system transmits a reconfiguration message to the personal monitoring device that causes the personal monitoring device to automatically begin providing data at a second rate. Among other things, the condition resulting in generation and transmission of the reconfiguration message may include a location-based condition (e.g., crossing a geographic boundary), a change in an environmental condition (e.g., temperature or air quality), or a movement-based condition (e.g., an acceleration indicative of a fall or collision).

The present disclosure is directed to systems and methods avoiding collisions by monitoring the presence and alertness of a person in a vehicle. The alertness of that person may be monitored by identifying actions performed by that person when an automated driving assistant is used in a vehicle. Systems and method consistent with the present disclosure may monitor the alertness of a person that is located in a driving position of a vehicle according to criteria associated with particular individuals or with criteria associated with specific protocols. When a system or method consistent with the present disclosure identifies that a person is not alert, a corrective action may be initiated that reduces likelihood of a collision.

In one embodiment, a service receives signal characteristic data indicative of characteristics of wireless signals received by one or more antennas located in a particular area. The service identifies an object in the particular area, based on the received signal characteristic data. The service associates the identified object with an object kinematics model. The service updates the object kinematics model over time by applying Bayesian inference to changes in the signal characteristic data.