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公开(公告)号：US11893080B2
公开(公告)日：2024-02-06
申请号：US17174818
申请日：2021-02-12
IPC分类号： G06V20/52 , G06N3/08 , G06F18/211 , G06T7/20 , G06N3/04 , G06V10/147 , G06V40/10 , G06F18/214 , G06V10/774 , G06V10/82
CPC分类号： G06F18/211 , G06F18/214 , G06N3/04 , G06N3/08 , G06T7/20 , G06V10/147 , G06V10/774 , G06V10/82 , G06V20/52 , G06V40/10 , G06T2207/10024 , G06T2207/10048 , G06T2207/20081 , G06T2207/20084 , G06T2207/30196 , G06T2207/30232 , G06T2207/30242
摘要： Method and computing device using a neural network to determine whether or not to process images of an image flow. A predictive model of the neural network is generated and stored at a computing device. The computing device receives (b) an image of the image flow and executes (c) the neural network, using the predictive model for generating an indication of whether or not to process the image based on input(s) of the neural network, the input(s) comprising the image. The computing device determines (d) whether or not to process the image by an image processing module, based on the indication of whether or not to process the image. The image is processed by the image processing module if the determination is positive and not processed if the determination is negative. Steps (b), (c), (d) are repeated for consecutive images of the image flow.
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公开(公告)号：US20230259074A1
公开(公告)日：2023-08-17
申请号：US18072094
申请日：2022-11-30
IPC分类号： G05B13/02 , H04L12/28 , G05B17/02 , G06N3/084 , F24F11/76 , F24F11/30 , F24F11/62 , G06N5/04 , G06N3/08
CPC分类号： G05B13/0265 , H04L12/2816 , H04L12/2823 , G05B17/02 , G06N3/084 , F24F11/76 , F24F11/30 , F24F11/62 , G06N5/04 , H04L12/2825 , G06N3/08 , F24F2120/10
摘要： Inference server and environment controller for inferring one or more commands for controlling an appliance. The environment controller receives at least one environmental characteristic value (for example, at least one of a current temperature, current humidity level, current carbon dioxide level, and current room occupancy) and at least one set point (for example, at least one of a target temperature, target humidity level, and target carbon dioxide level); and forwards them to the inference server. The inference server executes a neural network inference engine using a predictive model (generated by a neural network training engine) for inferring the one or more commands based on the received at least one environmental characteristic value and the received at least one set point; and transmits the one or more commands to the environment controller. The environment controller forwards the one or more commands to the controlled appliance.
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3.发明授权公开(公告)号：US11308793B2
公开(公告)日：2022-04-19
申请号：US16704665
申请日：2019-12-05
发明人： Arthur Chretien , Franck Forestier
摘要： Remote control device and method for controlling interactions between the remote control device and a controlled appliance. The remote control device comprises a BLE interface and a battery for powering the BLE interface. Upon determination of a first condition being met, the remote control device sets the BLE interface in a standby mode where the power supplied by the battery to the BLE interface is limited to a minimal value. Upon determination of a second condition being met, the remote control device transmits one or more BLE advertising signal via the BLE interface. The remote control device receives a connection request from a controlled appliance via the BLE interface, establishes a connection between the remote control device and the controlled appliance through the BLE interface, and exchanges data with the controlled appliance via the BLE communication interface (e.g. transmission of a command for an actuator of the controlled appliance).
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公开(公告)号：US11079134B2
公开(公告)日：2021-08-03
申请号：US16225764
申请日：2018-12-19
发明人： Francois Gervais
IPC分类号： F24F11/63 , F24F11/50 , G06N3/08 , G06N5/04 , F24F110/10
摘要： Computing device and method for inferring via a neural network a two-dimensional temperature mapping of an area. A predictive model is stored by the computing device. The computing device receives a plurality of temperature measurements transmitted by a corresponding plurality of temperature sensors located at a corresponding plurality of locations on a periphery of the area. The computing device executes a neural network inference engine, using the predictive model for inferring outputs based on inputs. The inputs comprise the plurality of temperature measurements. The outputs consist of a plurality of temperature values at a corresponding plurality of zones, the plurality of zones being comprised in a two-dimensional grid mapped on a plane within the area. For instance, the area is a room of a building, the periphery is an interface of a ceiling and walls of the room, and the plane is a horizontal plane within the room.
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公开(公告)号：US11037056B2
公开(公告)日：2021-06-15
申请号：US15819818
申请日：2017-11-21
发明人： Francois Gervais
摘要： Computing device and method for inferring a predicted number of data chunks writable on a flash memory before the flash memory wears out. The computing device stores a predictive model generated by a neural network training engine. A processing unit of the computing device executes a neural network inference engine, using the predictive model for inferring the predicted number of data chunks writable on the flash memory before the flash memory wears out based on inputs. The inputs comprise a total number of physical blocks previously erased from the flash memory, a size of the data chunk, and optionally an operating temperature of the flash memory. In a particular aspect, the flash memory is comprised in the computing device, and an action may be taken for preserving a lifespan of the flash memory based at least on the predicted number of data chunks writable on the flash memory.
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公开(公告)号：US20210141540A1
公开(公告)日：2021-05-13
申请号：US17156740
申请日：2021-01-25
发明人： Francois GERVAIS
摘要： Computing device and method for inferring a predicted number of physical blocks erased from a flash memory. The computing device stores a predictive model generated by a neural network training engine. A processing unit of the computing device executes a neural network inference engine, using the predictive model for inferring the predicted number of physical blocks erased from the flash memory based on inputs. The inputs comprise a total number of physical blocks previously erased from the flash memory, an amount of data to be written on the flash memory, and optionally an operating temperature of the flash memory. In a particular aspect, the flash memory is comprised in the computing device, and an action may be taken for preserving a lifespan of the flash memory based at least on the predicted number of physical blocks erased from the flash memory.
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公开(公告)号：US20210026312A1
公开(公告)日：2021-01-28
申请号：US17067060
申请日：2020-10-09
摘要： Inference server and environment controller for inferring one or more commands for controlling an appliance. The environment controller receives at least one environmental characteristic value (for example, at least one of a current temperature, current humidity level, current carbon dioxide level, and current room occupancy) and at least one set point (for example, at least one of a target temperature, target humidity level, and target carbon dioxide level); and forwards them to the inference server. The inference server executes a neural network inference engine using a predictive model (generated by a neural network training engine) for inferring the one or more commands based on the received at least one environmental characteristic value and the received at least one set point; and transmits the one or more commands to the environment controller. The environment controller forwards the one or more commands to the controlled appliance.
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8.发明申请公开(公告)号：US20200158369A1
公开(公告)日：2020-05-21
申请号：US16196062
申请日：2018-11-20
摘要： A method and computing device for inferring an airflow of a controlled appliance operating in an area of a building. The computing device stores a predictive model. The computing device determines a measured airflow of the controlled appliance and a plurality of consecutive temperature measurements in the area. The computing device executes a neural network inference engine using the predictive model for inferring an inferred airflow based on inputs. The inputs comprise the measured airflow and the plurality of consecutive temperature measurements. The inputs may further include at least one of a plurality of consecutive humidity level measurements in the area and a plurality of consecutive carbon dioxide (CO2) level measurements in the area. For instance, the controlled appliance is a Variable Air Volume (VAV) appliance and a K factor of the VAV appliance is calculated based on the inferred airflow.
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公开(公告)号：US20190394731A1
公开(公告)日：2019-12-26
申请号：US16437585
申请日：2019-06-11
发明人： Dominic GAGNON , Xavier ROUSSEAU
摘要： The present method and electronic device are adapted for secured commissioning. A generic password is stored in memory of the electronic device, and a transmission power of the electronic device is set to a reduced transmission power. The electronic device receives a commissioning request including the generic password and a specific password. The generic password is replaced in the memory of the electronic device by the specific password, and the transmission power of the electronic device is increased to full transmission power.
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10.发明申请公开(公告)号：US20190278242A1
公开(公告)日：2019-09-12
申请号：US15914610
申请日：2018-03-07
发明人： Francois GERVAIS
IPC分类号： G05B19/042 , G06N3/08 , G06N5/02 , G06N5/04
摘要： Method and training server for generating a predictive model for the control of an appliance by an environment controller. The predictive model allows a neural network inference engine to infer output(s) based on inputs. The training server receives room characteristic(s), current environmental characteristic value(s), and set point(s) from the environment controller. The training server determines command(s) for controlling the appliance based on the current environmental characteristic value(s), the set point(s) and the room characteristic(s). Each command is executed by the controlled appliance. The training server receives updated environmental characteristic value(s) and determines a reinforcement signal based on the set point(s), the updated environmental characteristic value(s), and a set of rules. The training server executes a neural network training engine to update the predictive model based on: inputs comprising the current environmental characteristic value(s), the set point(s), and the room characteristic(s); output(s) consisting of the command(s); and the reinforcement signal.
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