Abstract: Memory device comprising flash memory and method for controlling a write speed of a bus transmitting data for storage on the flash memory. The flash memory of the memory device comprises a plurality of physical blocks for writing data transmitted over the bus from a host device to the memory device. The writing of data in any one of the plurality of physical blocks is preceded by an erase of the physical block. The memory device also comprises a memory device controller controlling a write speed of the bus. The write speed of the bus defines a transmission rate at which data are transmitted over the bus from the host device to the memory device, for further writing on the flash memory. The control of the write speed of the bus comprises adapting the transmission rate based on a number of physical blocs erased.

Abstract: Method and computing device for inferring a predicted state of a communication channel. The computing device stores a predictive model generated by a neural network training engine. The computing device collects a plurality of data samples representative of operating conditions of the communication channel. The communication channel is associated to a communication interface of the computing device. The communication interface allows an exchange of data between the computing device and at least one remote computing device over the communication channel. Each data sample comprises a measure of the amount of data respectively transmitted and received by the communication interface over the communication channel and a connection status of the communication channel, during a period of time. The computing device further executes a neural network inference engine using the predictive model for inferring the predicted state of the communication channel based on the plurality of data samples.

Abstract: Method and environment controller for validating a predictive model of a neural network. The environment controller receives at least one environmental characteristic value and determines a plurality of input variables. At least one of the plurality of input variables is based on one among the environmental characteristic value(s). The environment controller executes an environment control software module for calculating at least one output variable based on the plurality of input variables. The environment controller transmits the plurality of input variables to a training server executing a neural network training engine using the predictive model; and receives at least one inferred output variable from the training server. Each inferred output variable corresponds to one of the at least one output variable calculated by the environment control software module.

Abstract: Method and environment controller using a neural network for bypassing a legacy environment control software module. The environment controller receives at least one environmental characteristic value and determines a plurality of input variables. At least one of the plurality of input variables is based on one among the at least one environmental characteristic value. The environment controller transmits the plurality of input variables to an inference server executing a neural network inference engine. The environment controller receives at least one inferred output variable from the inference server. The environment controller uses the at least one inferred output variable received from the inference server in place of at least one output variable calculated by the legacy environment control software module based on the plurality of input variables.

Abstract: An improved wearable locator has an ultra-low power RF transceiver, GPS receiver, cellular network RF transceiver, processor, programmable non-volatile memory, LCD display, accelerometer and rechargeable battery. To ensure that the locator is within a perimeter, it can cooperate with a subordinate unit that includes an ultra-low power RF transceiver, processor, power supply, DC charging output, rechargeable battery, visual, audible and tactile enunciators and pushbutton, and can be plugged into an outlet or be unplugged and be mobile. Other wireless units can be used to define a perimeter.

Abstract: Method and computing device for inferring via a neural network environmental data of an area of a building based on visible and thermal images of the area. A predictive model generated by a neural network training engine is stored by the computing device. The computing device determines a visible image of an area based on data received from at least one visible imaging camera. The computing device determines a thermal image of the area based on data received from at least one thermal imaging device. The computing device executes a neural network inference engine, using the predictive model for inferring environmental data based on the visible image and the thermal image. The inferred environmental data comprise geometric characteristic(s) of the area, an occupancy of the area, a human activity in the area, temperature value(s) for the area, and luminosity value(s) for the area.

Abstract: 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.

Abstract: Inference server and environment controller for inferring via a neural network one or more commands for controlling an appliance. The environment controller determines at least one room characteristic. The environment controller receives at least one environmental characteristic value and at least one set point. The environment controller transmits the at least one environmental characteristic, set point and room characteristic 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 for controlling the appliance. The inference is based on the received at least one environmental characteristic value, at least one set point and at least one room characteristic. The inference server transmits the one or more commands to the environment controller, which forwards the one or more commands to the controlled appliance.

Abstract: Method and environment controller for inferring via a neural network one or more commands for controlling an appliance. A predictive model generated by a neural network training engine is stored by the environment controller. 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). The environment controller receives at least one set point (for example, at least one of a target temperature, target humidity level, and target carbon dioxide level). The environment controller executes a neural network inference engine, which uses the predictive model for inferring the one or more commands for controlling the appliance based on the at least one environmental characteristic value and the at least one set point. The environment controller transmits the one or more commands to the controlled appliance.

Abstract: 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.

Abstract: Method and environment controller for inferring via a neural network one or more commands for controlling an appliance. A predictive model generated by a neural network training engine is stored by the environment controller. The environment controller determines at least one room characteristic. The environment controller receives at least one environmental characteristic value and at least one set point. The environment controller executes a neural network inference engine, which uses the predictive model for inferring the one or more commands for controlling the appliance. The inference is based on the at least one environmental characteristic value, the at least one set point and the at least one room characteristic. The environment controller transmits the one or more commands to the controlled appliance.

Abstract: 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.

Abstract: 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.

Abstract: Method and computing device for inferring an optimal wireless data transfer rate using a neural network. The method comprises storing a predictive model generated by a neural network training engine in a memory of a computing device. The method comprises determining, by a processing unit of the computing device, parameters of a data transfer through a wireless communication interface of the computing device. The method comprises executing, by the processing unit, a neural network inference engine using the predictive model for inferring an optimal data transfer rate based on the parameters of the data transfer through the wireless communication interface. The method comprises configuring the wireless communication interface to operate at the optimal data transfer rate. For example, the computing device consists of an environment control device (ECD). The ECD may consist of an environment controller, a sensor, a controlled appliance, and a relay.

Abstract: Inference server and computing device for inferring an optimal wireless data transfer rate. The computing device determines parameters of a data transfer through a wireless communication interface of the computing device, and transmits the parameters of the data transfer to the inference server. The inference server receives the parameters of the data transfer, executes a neural network inference engine using a predictive model (generated by a neural network training engine) for inferring an optimal data transfer rate based on the parameters of the data transfer, and transmits the optimal data transfer rate to the computing device. The computing device receives the optimal data transfer rate, and configures its wireless communication interface to operate at the optimal data transfer rate. For example, the computing device consists of an environment control device (e.g. an environment controller, a sensor, a controlled appliance, and a relay).

Abstract: Memory device comprising flash memory and method for controlling a write speed of a bus transmitting data for storage on the flash memory. The flash memory of the memory device comprises a plurality of physical blocks for writing data transmitted over the bus from a host device to the memory device. The writing of data in any one of the plurality of physical blocks is preceded by an erase of the physical block. The memory device also comprises a memory device controller controlling a write speed of the bus. The write speed of the bus defines a transmission rate at which data are transmitted over the bus from the host device to the memory device, for further writing on the flash memory. The control of the write speed of the bus comprises adapting the transmission rate based on a number of physical blocs erased.

Abstract: An environment control device (ECD) providing a Wi-Fi hotspot for accessing the Internet. The ECD comprises a communication module with a Wi-Fi hotspot functionality for establishing a Wi-Fi hotspot at the ECD, and a mesh client functionality for communicating over a mesh network. The communication module provides for exchanging environmental data with at least another ECD, over one of the Wi-Fi hotspot or mesh network. It also provides for receiving upstream Internet data from at least one user terminal over the Wi-Fi hotspot, and forwarding the upstream Internet data to another ECD over the mesh network. It further provides for receiving downstream Internet data from another ECD over the mesh network, and forwarding the downstream Internet data to the at least one user terminal over the Wi-Fi hotspot. The ECD providing the Wi-Fi hotspot for accessing the Internet may be a daisy-chained ECD controlled by a master ECD.

Abstract: The present invention relates to methods of detecting differentially expressed protein expression indicative of COPD in a test sample. The detection of circulating levels of proteins within an identified COPD biomarker signature can aid in COPD diagnosis and disease monitoring, as well as in the prediction of responses to therapeutics. Evaluation of the biomarker signatures disclosed, or a subset of biomarkers thereof, provides a level of discrimination not found with individual markers.

Abstract: An improved wearable locator has an ultra-low power RF transceiver, GPS receiver, cellular network RF transceiver, processor, programmable non-volatile memory, LCD display, accelerometer and rechargeable battery. To ensure that the locator is within a perimeter, it can cooperate with a subordinate unit that includes an ultra-low power RF transceiver, processor, power supply, DC charging output, rechargeable battery, visual, audible and tactile enunciators and pushbutton, and can be plugged into an outlet or be unplugged and be mobile. Other wireless units can be used to define a perimeter.

Abstract: An environment control device (ECD) providing a Wi-Fi hotspot for accessing the Internet. The ECD comprises a communication module with a Wi-Fi hotspot functionality for establishing a Wi-Fi hotspot at the ECD, and a mesh client functionality for communicating over a mesh network. The communication module provides for exchanging environmental data with at least another ECD, over one of the Wi-Fi hotspot or mesh network. It also provides for receiving upstream Internet data from at least one user terminal over the Wi-Fi hotspot, and forwarding the upstream Internet data to another ECD over the mesh network. It further provides for receiving downstream Internet data from another ECD over the mesh network, and forwarding the downstream Internet data to the at least one user terminal over the Wi-Fi hotspot. The ECD providing the Wi-Fi hotspot for accessing the Internet may be a daisy-chained ECD controlled by a master ECD.