Smart method of personalized management for electricity appliances.
Publication Date: 2016-Apr-22
The IP.com Prior Art Database
This is an idea based on smart home concept with the big data analysis that can provide a smarter method to control the electricity appliances via the persons' living habit and customizing. It can reduce the waste of electricity and avoid some accidence. The main concept in this mechanism is using big data analysis to analyze the persons living habit and trim up then obtain many series results which can be the driver to control the furniture and electricity appliances. The physiological sensor need to be installed on partial furniture to estimate the human status. And the signal sensor need to be installed on the household appliances to receive and send message between other furniture and electricity appliances. There is an application need to be installed on the terminal devices and the persons can browser the analysis results and reports, beside the persons can formulate the agile plan to manage the household appliances. The all information including customized plans, daily running conditions and the persons' activities will be saved in the big data DB. Notes: the physiological sensor contains Breath sounds sensor, vibrating sensor and pressure sensor, etc.
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Smart method of personalized management for electricity appliances
Smart method of personalized management for electricity appliances. .
Here is described using a sample:
1. The persons create several groups in the application on PC.
1) Set the furniture and electricity appliances in bedroomas Group
1including bed, air-condition, table, charis, computer, etc.
2) Set the furniture and electricity appliances in living roomas Group 2including television, air-condition, table, charis, sofa, etc.
3) Set the furniture and electricity appliances in kitchen
as Group 3including stove, kitchen ventilator, electric cooker, refrigerator,
Device definition (T)
1 G1 stove
2 G1 bed
3 G2 television
4 G1 sleep monitor 5 .. ..
2. The persons' activities and the states of the electricity appliances and furniture will be recorded in the big data DB in real time dynamically.
1) Actual time table:
G3 stove in use 7:00 20 H G3 kitchen ventilator in use 7:00 20 L G1 bed
unused 6:30 50 L G2 air-condition unused 0:00 440 M ..
The status of the furniture and electricity appliances will be recorded in this table in real time dynamically. For example, the stove is in used at 7:00 am, and a new record generated. The duration will be updated every second by plus 1. Once the status is changed to 'unused', a new record will be generated automatically. The risk level will be set via the initial value and updated based on the value in the 'Living habit' table.
2) Living habit table:
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In use 0:00 7:30 450 80%
unused 7:31 12:30 301 85%
G3 stove in use 7:00 7:30 30 91% ..
The usage of the furniture and electricity appliances will be recorded in this table. First time, there will be a record with the name, status, time, duration and accuracy is 1%, if the time and duration are different, there will be a new record generated automatically. Otherwise the accuracy will be updated day by day. The record in this table is a reference baseline and impact the risk level directly (from L to M, from M to H, etc) if the usage of the furniture and electricity appliances is discrepant with the value in the table.
3) Rule table: ID