The present disclosure discloses a fan driving device, and the fan driving device comprises a sensing unit and a processing unit, wherein the sensing unit at least comprises a microwave sensing module; the sensing unit is at least used for sensing whether any human activity exists within the action range based on microwave sensing according to a certain microwave sensing cycle, and outputting a sensing signal to the processing unit periodically; and the processing unit is used for processing the sensing signal, so that the driving device can adaptively control the turn-on and turn-off of the fan and adaptively regulate the working power of the fan. Based on this, a dynamic intelligent fan driving device without a user's turn-on and turn-off action and based on environmental state sensing is realized.

A method of a fan system directing an air stream at a target can include receiving, with a controller, a first image from an image capture sensor and analyzing the first image from the image capture sensor to determine a first location of the target. The method can also include receiving a second image from the image capture sensor and analyzing the second image from the image capture sensor to determine a second location of the target. The method can also include comparing the first location of the target and the second location of the target and sending a signal to a first motor to rotate a housing about a first axis respective to a base to direct an air stream exiting an outlet of a channel at the target.

A network of wireless remote climate sensors in a heating, ventilation, and air conditioning (HVAC) system permits the creation of personalized microclimates within an enclosed space. In addition to collecting temperature and humidity data, the wireless remote climate sensors can detect whether the enclosed space is occupied by a human. Human detection is made possible by optional cameras, microphones, and gas sensors on the wireless remote climate sensors. As the human moves throughout the enclosed space, the HVAC system is able to track the human's movement using the wireless remote climate sensors. The HVAC system may adjust airflow to different portions of the enclosed space based on the human's location. The result is an efficient use of system resources to keep users at their ideal temperature.

An estimation unit estimates a thermal sensation representing how hot or cold a user feels based on an image of the user taken by a camera. A control unit controls an air-conditioning operation of an air conditioner based on an estimation result of the estimation unit so that the thermal sensation falls within a target range, the air conditioner targeting a room in which the user is present. The image shows a motion and/or state of the user representing a hot or cold sensation of the user, and the estimation unit extracts the motion and/or state of the user from the image to estimate the thermal sensation.

An environmental control equipment control apparatus controls an environment of a target space using a plurality of environmental control equipment. The control apparatus includes a receiver and an electronic controller. The receiver may receive state information relating to states of a plurality of subject persons. In this case, the electronic controller controls a plurality of kinds of environmental control equipment such that the state information of the plurality of subject persons received by the state information receiver satisfies a predetermined target state condition. The receiver may receive a second environmental stimulus given to a subject person other than a first environmental stimulus caused by control of the environmental control equipment. In this case, the electronic controller controls the environmental control equipment such that an influence of the second environmental stimulus received by the environmental stimulus receiver on the subject person is cancelled or reduced.

A camera (26) takes an image of at least one user (U1, U2, U3). A room environment information sensor (13) senses room environment information relating to an environment of a room (r1) in which the at least one user (U1, U2, U3) is present. The estimator (66) estimates a drowsiness condition of the at least one user (U1, U2, U3) based on the image of the at least one user (U1, U2, U3) taken by the camera (26) and the room environment information sensed by the room environment information sensor (13).

A heating, ventilation, and air conditioning (HVAC) control device configured to collect event data from the one or more devices and to populate time entries in an occupancy history log with the event data. The event data includes a timestamp indicating a time when an event occurred, a set point temperature value for the HVAC system, and an occupancy status indicating whether a space is occupied. The device is further configured to identify blank time entries in the occupancy history log and to populate the blank time entries by forward filling the occupancy history log using event data from another time entry in the occupancy history log. The device is further configured to output the populated occupancy history log.

An air-conditioning system includes an air-conditioning apparatus, a user-detecting unit detecting, for users, an amount of activity and a position, a storage device storing, for each amount of activity, a group including comfort index distributions each corresponding to each of air-conditioning control patterns of the air-conditioning apparatus, and a controller configured to obtain an air-conditioning control pattern that enables a comfort efficiency to be maximum, by specifying the group corresponding to the amount of activity for each of the users, extracting the comfort indexes corresponding to the position of each of the users from the comfort index distributions in the specified group, and, based on the comfort indexes extracted corresponding to the position of each of the users, calculating the comfort efficiency indicating a comprehensive comfort level of the users for each of the air-conditioning control patterns.

An example method includes capturing images using a camera and detecting a medical device in a first image among the images. A request is transmitted to the medical device. Based on transmitting the request, the example method includes determining that the medical device has output a chirp signal in a second image among the images. Based on the chirp signal, the method includes causing the medical device to perform an action by transmitting a control message to the medical device.

A sleep onset determination method includes: detecting a light-out time that is a time at which illuminance in a room becomes less than or equal to a predetermined value; storing the light-out time detected in the detecting of the light-out time and a time period including the light-out time detected; and determining whether a user fell asleep at a currently detected light-out time, based on the light-out time and the time period stored in the storing of the light-out time.