Home appliance control system with dynamic adjustment of journey time and control method thereof

Abstract

A home appliance control system with dynamic adjustment of journey time is provided. A processing module is utilized to generate a journey time based on a journey distance and a transportation information obtained from a home appliance positioning information and a mobile positioning information. An identification device generates an unlocking time point when a user information matches an identification data. A cloud server calculates and generates an unlocking time based on the unlocking time point and inputs the journey time and the unlocking time into a neural network model to calculate and generate a dynamic adjustment time, so that the processing module corresponds to a selected execution option to generate a control instruction based on the dynamic adjustment time that conforms to the home appliance script, and the cloud server outputs a control signal according to the control instruction, and causes the home appliance device to operate according to the control signal.

Claims

1. A home appliance control system with dynamically adjustable travel time, comprising: a mobile communication device having a script application installed, comprising: a storage module storing a home appliance script and home appliance location information; a positioning module generating mobile positioning information by locating the mobile communication device; and a processing module connected to the storage module and the positioning module to receive the home appliance location information and the mobile positioning information, the processing module running the script application to set the home appliance script and provide an execution option corresponding to the home appliance script, the processing module obtaining a travel distance and traffic information based on the home appliance location information and the mobile positioning information to generate a travel time; and an identification device identifying identification data based on user information corresponding to the mobile communication device, and generating an unlocking time point when the identification device confirms that the user information matches the identification data. A cloud server, connected to the mobile communication device and the identification device, receives the travel time and the unlocking time. The cloud server calculates and generates an unlocking time based on the unlocking time, and inputs the travel time and the unlocking time into a neural network model to calculate and generate a dynamically adjusted time. The processing module receives the dynamically adjusted time and generates a control command based on the selected execution option and the dynamically adjusted time conforming to the home appliance script. The cloud server receives the control command and outputs a control signal based on the control command. At least one home appliance is connected to the cloud server and receives the control signal, and operates according to the control signal. The neural network model includes an input layer, a plurality of hidden layers, and an output layer. The input layer receives the travel time and the unlocking time, and outputs the travel time and the unlocking time to a plurality of nodes in the hidden layers. The hidden layers assign a weight to each node based on a difference between the travel time and the unlocking time. The output layer receives prediction data from the configuration output of the hidden layers, and the cloud server generates the dynamically adjusted time based on the prediction data.

2. A home appliance control system with dynamically adjustable travel time as described in claim 1, wherein, When the hidden layers assign a weight to each node based on the difference between the travel time and the unlocking time, the hidden layer determines the difference with an extreme value based on an anomaly exclusion rule and assigns the node a weight of zero.

3. A home appliance control system with dynamically adjustable travel time as described in claim 2, wherein, The anomaly exclusion rule is based on a plurality of the differences during a training period, and a base interval between the first quartile and the third quartile is calculated based on these differences. A minimum boundary is calculated based on the first quartile - 1.5 × the base interval, and a maximum boundary is calculated based on the third quartile + 1.5 × the base interval. The interval between the minimum boundary and the maximum boundary is used as a judgment interval for the anomaly exclusion rule. When any difference exceeds the judgment interval, the hidden layer determines that it is a difference with the extreme value.

4. A home appliance control system with dynamically adjustable travel time as described in claim 1, wherein, When the hidden layers assign a weight to each node based on the difference between the travel time and the unlocking time, the hidden layer assigns a decrement to the node that does not conform to the user data based on user data.

5. A home appliance control system with dynamic travel time adjustment as described in claim 4, wherein, The user data consists of a plurality of the differences during a training period, an overlapping interval of the differences is determined based on a habit threshold, and the overlapping interval above the habit threshold is taken as the user data.

6. The home appliance control system with dynamic adjustment of travel time as described in claim 1, wherein the home appliance script includes a script condition and an action instruction after the script condition is met.

7. A home appliance control system with dynamically adjustable travel time as described in claim 6, wherein the processing module generates a power consumption assessment value in response to the action instruction of the home appliance script.

8. The home appliance control system with dynamic travel time adjustment as described in claim 1, wherein the traffic information includes vehicle information, road condition information, route information, or a combination thereof.

9. A method for controlling a home appliance with dynamically adjustable travel time, applicable to a home appliance control system with dynamically adjustable travel time as described in any one of claims 1 to 8, comprising: using a positioning module to locate a mobile communication device and generate mobile positioning information; using a processing module to run a scripting application to set a home appliance script and provide an execution option corresponding to the home appliance script; obtaining a travel distance and traffic information based on the home appliance positioning information and the mobile positioning information, thereby generating a travel time; using an identification device to identify identification data based on user information corresponding to the mobile communication device; when the identification device confirms that the user information matches the identification data, the identification device generates an unlocking time point; using a cloud server to calculate and generate an unlocking time based on the unlocking time point; inputting the travel time and the unlocking time into a neural network model to calculate and generate a dynamically adjusted time; using the processing module to generate a control command based on the selected execution option and the dynamically adjusted time matching the home appliance script. The cloud server outputs a control signal based on the control command; and at least one home appliance corresponds to the appliance's location information to operate according to the control signal.

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