CN104715568A - Big data system and method for family environment monitoring - Google Patents
Big data system and method for family environment monitoring Download PDFInfo
- Publication number
- CN104715568A CN104715568A CN201510101380.2A CN201510101380A CN104715568A CN 104715568 A CN104715568 A CN 104715568A CN 201510101380 A CN201510101380 A CN 201510101380A CN 104715568 A CN104715568 A CN 104715568A
- Authority
- CN
- China
- Prior art keywords
- alarm
- unit
- environment monitoring
- user
- server end
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
Landscapes
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Alarm Systems (AREA)
Abstract
A big data system for family environment monitoring comprises a sensor module used for collecting user information and wirelessly sending the user information to a server end in real time, and the server end used for carrying out intelligent analyzing on the user information collected by the sensor module and providing a danger detecting, alarming and health suggestion and business purchasing auxiliary decision making supporting information. According to the danger detection output, if it is judged that the current action generates danger, an alarming action is generated. When it is detected that the user environment can probably have an adverse effect on the health, a corresponding health suggestion is given. The sensor module is in wireless connection with the server end. The invention further provides a big data method for family environment monitoring.
Description
Technical field
The present invention relates to Internet of Things and large data technique field, particularly a kind of large data system for home environment monitoring and method.
Background technology
Along with the rise of Smart Home, each manufacturer also releases oneself Internet of Things scheme one after another, and this meets the demand of people to more intelligent home equipment and service to a great extent.User is by installing intelligent home device, and its principle realized, after things-internet gateway is disposed, by gateway, environmental monitoring information is sent in the large data platform in high in the clouds, and analysis result is pushed on the mobile phone of client.
Large data due to Internet of Things are emerging field, environmentally a monitoring information, and businessman can identify potential client, and government can formulate policy targetedly, and user by the environmental information of monitoring oneself, can adjust accordingly the healthy behavior of oneself.These application are interesting, practical and closeness to life, but the real user used is few, and main cause is that the large data system of Internet of Things has following 2 restrictions:
1, gateway accessing costly and inconvenient, so the ratio of user is very low.
2, personal information is sent to high in the clouds, thus the leakage of userspersonal information may be caused.
Summary of the invention
In order to overcome above-mentioned the deficiencies in the prior art, the invention provides a kind of large data system for home environment monitoring and method.
For a large data system for home environment monitoring, it comprises as lower module:
Sensor assembly, for gathering user profile, and is sent to server end by user profile real-time radio;
Server end, carries out intellectual analysis for the user profile collected sensor assembly, and provides hazard detection, warning and Health & Fitness Tip, and provides mm Suppliers aid decision making to support information; The output of above-mentioned hazard detection, if it is dangerous to judge that current action produces, then produces actuation of an alarm; When user environment adverse effect issuable to health being detected, provide healthy corresponding suggestion;
Sensor assembly and server end wireless connections.
In the large data system for home environment monitoring of the present invention, described server end comprises rules unit, repository unit, machine learning unit, alarm and processing unit;
Rules unit is for setting the rule of alarm equipment alarm, and the learning rules of machine learning unit;
Repository unit, for collecting healthy general knowledge source, and is sent to processing unit by the healthy general knowledge source of collecting;
Machine learning unit, for learning user's external environment and user behavior, and is sent to rules unit by the result of study;
Alarm for receiving alarm command, and sends warning message according to alarm command and starts actuation of an alarm;
Processing unit, for the user profile of receiving sensor module acquires, receives the rule of the alarm equipment alarm that rules unit sends, and receives the learning outcome that machine unit sends, and receives the healthy general knowledge source of knowledge base transmission; And for processing user profile according to the learning outcome received and health knowledge source, and generate alarm command according to the result of the rule of reporting to the police and process, alarm command is sent to alarm.
In the large data system for home environment monitoring of the present invention, rules unit can high-speed cache and upgrade the rule of alarm equipment alarm, and the learning rules of machine learning unit, and verifies rule compliance and security.
In the large data system for home environment monitoring of the present invention, repository unit is also for the storage in healthy general knowledge source and healthy general knowledge collection and cleaning.
In the large data system for home environment monitoring of the present invention, machine learning unit, also for the study to user behavior and residing environmental history information--namely user behavior and residing environmental history information are classified by different features, and the eigenwert of category tabulate statistics common characteristic, the eigenwert of comparison user behavior and the eigenwert similarity of classification, thus realize the prediction to user behavior.
In the large data system for home environment monitoring of the present invention, alarm, also for the escape to alarm command, sends and replys checking.
The present invention also provides a kind of large data method for home environment monitoring, and it comprises the steps:
S1, gathers user profile by sensor assembly, and user profile real-time radio is sent to server end;
S2, by server end, intellectual analysis is carried out to the user profile that sensor assembly collects, and hazard detection, warning and Health & Fitness Tip are provided, and provide mm Suppliers aid decision making to support information; The output of above-mentioned hazard detection, if it is dangerous to judge that current action produces, then produces actuation of an alarm; When user environment adverse effect issuable to health being detected, provide healthy corresponding suggestion.
The present invention's object of the present invention, the perception of bond networking home equipment (sensor assembly), provides the Intelligent Service of higher level.
Tool has the following advantages: in conjunction with existing internet of things equipment, can provide high-grade intelligent behavior, this behavior expression exists: 1. self study, finds behavior pattern and changing pattern; 2. safety certification, determines that the interoperability behavior of Internet of Things household is safe, and, at the time of emergency, reduce the loss as far as possible, and retain evidence; 3, generate suggestion and intelligent behavior.
Accompanying drawing explanation
Fig. 1 is the structured flowchart of the large data system for home environment monitoring of the invention process;
Fig. 2 is the large data method process flow diagram for home environment monitoring of the invention process.
Embodiment
As shown in Figure 1, a kind of large data system for home environment monitoring, it comprises as lower module:
Sensor assembly 100, for gathering user profile, and is sent to server end 200 by user profile real-time radio.Sensor assembly 100 can comprise the various sensor for monitor user ' surrounding environment and the sensor for obtaining user's self information.
Server end 200, carries out intellectual analysis for the user profile collected sensor assembly 100, and provides hazard detection, warning and Health & Fitness Tip, and provides mm Suppliers aid decision making to support information; The output of above-mentioned hazard detection, if it is dangerous to judge that current action produces, then produces actuation of an alarm; When user environment adverse effect issuable to health being detected, provide healthy corresponding suggestion.Server end 200 can be high performance commerce server, also can be the terminal such as smart mobile phone, panel computer.
Sensor assembly 100 and server end 200 wireless connections.Wireless connections comprise the connected mode such as bluetooth, zigbee, WIFI, 3G, 4G wireless network.
Alternatively, described server end 200 comprises rules unit 10, repository unit 20, machine learning unit 30, alarm 40 and processing unit 50.
The rule that rules unit 10 is reported to the police for setting alarm 40, and the learning rules of machine learning unit 30.
Repository unit 20, for collecting healthy general knowledge source, and is sent to processing unit 50 by the healthy general knowledge source of collecting.Healthy general knowledge source comprises the knowledge sources such as internet, also comprises the content knowledge source such as hospital, research institution.
Machine learning unit 30, for learning user's external environment and user behavior, and is sent to rules unit 10 by the result of study.By machine learning unit 30, can revise the rule inside rules unit 10 in real time, make it more scientific.
Alarm 40 for receiving alarm command, and sends warning message according to alarm command and starts actuation of an alarm.Warning message comprises and giving the alarm, and actuation of an alarm comprises automatic placement of emergency calls, and certainly, the present invention is not limited only to this.
The user profile that processing unit 50 gathers for receiving sensor module 100, the rule that the alarm 40 that reception rules unit 10 sends is reported to the police, receives the learning outcome that machine unit 30 sends, and receives the healthy general knowledge source of knowledge base transmission; And for processing user profile according to the learning outcome received and health knowledge source, and generate alarm command according to the result of the rule of reporting to the police and process, alarm command is sent to alarm 40.
Alternatively, rules unit 10 can high-speed cache and upgrade the rule that alarm 40 reports to the police, and the learning rules of machine learning unit 30, and verifies rule compliance and security.By the present embodiment, can determine that the interbehavior of user operation behavior and various equipment is safe.
Alternatively, repository unit 20 is also for the storage in healthy general knowledge source and healthy general knowledge collection and cleaning.Cleaning is the information removing fault and mistake in healthy general knowledge source.
Alternatively, machine learning unit 30, also for the study to user behavior and residing environmental history information--namely user behavior and residing environmental history information are classified by different features, and the eigenwert of category tabulate statistics common characteristic, the eigenwert of comparison user behavior and the eigenwert similarity of classification, thus realize the prediction to user behavior.
Alternatively, alarm 40, also for the escape to alarm command, sends and replys checking.
As shown in Figure 2, the embodiment of the present invention also provides a kind of large data method for home environment monitoring, and it comprises the steps:
S1, gathers user profile by sensor assembly 100, and user profile real-time radio is sent to server end 200;
S2, the user profile collected by server end 200 pairs of sensor assemblies 100 are carried out intellectual analysis, and are provided hazard detection, warning and Health & Fitness Tip, and provide mm Suppliers aid decision making to support information; The output of above-mentioned hazard detection, if it is dangerous to judge that current action produces, then produces actuation of an alarm; When user environment adverse effect issuable to health being detected, provide healthy corresponding suggestion.
Be understandable that, for the person of ordinary skill of the art, other various corresponding change and distortion can be made by technical conceive according to the present invention, and all these change the protection domain that all should belong to the claims in the present invention with distortion.
Claims (7)
1., for a large data system for home environment monitoring, it is characterized in that, it comprises as lower module:
Sensor assembly, for gathering user profile, and is sent to server end by user profile real-time radio;
Server end, carries out intellectual analysis for the user profile collected sensor assembly, and provides hazard detection, warning and Health & Fitness Tip, and provides mm Suppliers aid decision making to support information; The output of above-mentioned hazard detection, if it is dangerous to judge that current action produces, then produces actuation of an alarm; When user environment adverse effect issuable to health being detected, provide healthy corresponding suggestion;
Sensor assembly and server end wireless connections.
2., as claimed in claim 1 for the large data system of home environment monitoring, it is characterized in that, described server end comprises rules unit, repository unit, machine learning unit, alarm and processing unit;
Rules unit is for setting the rule of alarm equipment alarm, and the learning rules of machine learning unit;
Repository unit, for collecting healthy general knowledge source, and is sent to processing unit by the healthy general knowledge source of collecting;
Machine learning unit, for learning user's external environment and user behavior, and is sent to rules unit by the result of study;
Alarm for receiving alarm command, and sends warning message according to alarm command and starts actuation of an alarm;
Processing unit, for the user profile of receiving sensor module acquires, receives the rule of the alarm equipment alarm that rules unit sends, and receives the learning outcome that machine unit sends, and receives the healthy general knowledge source of knowledge base transmission; And for processing user profile according to the learning outcome received and health knowledge source, and generate alarm command according to the result of the rule of reporting to the police and process, alarm command is sent to alarm.
3. as claimed in claim 1 for the large data system of home environment monitoring, it is characterized in that, rules unit can high-speed cache and upgrade the rule of alarm equipment alarm, and the learning rules of machine learning unit, and verifies rule compliance and security.
4. as claimed in claim 1 for the large data system of home environment monitoring, it is characterized in that, repository unit is also for the storage in healthy general knowledge source and healthy general knowledge collection and cleaning.
5. as claimed in claim 1 for the large data system of home environment monitoring, it is characterized in that, machine learning unit, also for the study to user behavior and residing environmental history information--namely user behavior and residing environmental history information are classified by different features, and the eigenwert of category tabulate statistics common characteristic, the eigenwert of comparison user behavior and the eigenwert similarity of classification, thus realize the prediction to user behavior.
6. as claimed in claim 1 for the large data system of home environment monitoring, it is characterized in that, alarm, also for the escape to alarm command, sends and replys checking.
7., for a large data method for home environment monitoring, it is characterized in that, it comprises the steps:
S1, gathers user profile by sensor assembly, and user profile real-time radio is sent to server end;
S2, by server end, intellectual analysis is carried out to the user profile that sensor assembly collects, and hazard detection, warning and Health & Fitness Tip are provided, and provide mm Suppliers aid decision making to support information; The output of above-mentioned hazard detection, if it is dangerous to judge that current action produces, then produces actuation of an alarm; When user environment adverse effect issuable to health being detected, provide healthy corresponding suggestion.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510101380.2A CN104715568A (en) | 2015-03-07 | 2015-03-07 | Big data system and method for family environment monitoring |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510101380.2A CN104715568A (en) | 2015-03-07 | 2015-03-07 | Big data system and method for family environment monitoring |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104715568A true CN104715568A (en) | 2015-06-17 |
Family
ID=53414856
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510101380.2A Pending CN104715568A (en) | 2015-03-07 | 2015-03-07 | Big data system and method for family environment monitoring |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104715568A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105607508A (en) * | 2016-03-24 | 2016-05-25 | 重庆邮电大学 | Smart home device control method and system based on user behavior analysis |
| CN105938648A (en) * | 2016-06-14 | 2016-09-14 | 夏烬楚 | Household safety integrated management system and method |
| CN106886158A (en) * | 2015-12-15 | 2017-06-23 | 英业达科技有限公司 | Intelligent home is analyzed and suggesting system for wearing and its method |
| CN108845076A (en) * | 2018-04-25 | 2018-11-20 | 北京市电话工程有限公司 | A kind of air-quality monitoring system of cell |
| CN109003414A (en) * | 2018-06-20 | 2018-12-14 | 中译语通科技（青岛）有限公司 | A kind of electronic security system and working method |
| CN109507893A (en) * | 2017-09-14 | 2019-03-22 | 宁波方太厨具有限公司 | A kind of self study alarm control method of smart home device |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1700231A (en) * | 2004-05-21 | 2005-11-23 | 株式会社日立制作所 | Managing system, managing method of organism information and program for management |
| KR20110053107A (en) * | 2009-11-13 | 2011-05-19 | (주)인포빌 | A safe control system for harmful workshop |
| CN202771426U (en) * | 2012-07-18 | 2013-03-06 | 山西创感科技有限公司 | Health monitoring system based on server-client side |
| CN103279687A (en) * | 2013-06-21 | 2013-09-04 | 镇江冈山电子有限公司 | Individualized health service system based on context aware |
| CN103300819A (en) * | 2012-03-15 | 2013-09-18 | 西门子公司 | Learning patient monitoring and intervention system |
| CN103330554A (en) * | 2013-07-18 | 2013-10-02 | 梁亚楠 | Wearable artificial intelligence wireless Internet of Things security system |
| CN103393416A (en) * | 2013-08-23 | 2013-11-20 | 江苏惠通集团有限责任公司 | TV (television) system based physiological index monitoring system and method |
| CN103744411A (en) * | 2014-02-07 | 2014-04-23 | 上海金牌软件开发有限公司 | Control method related to ZigBee technology for realizing smart home |
| CN104040547A (en) * | 2011-12-21 | 2014-09-10 | 皇家飞利浦有限公司 | Method and system to predict physiologic and clinical status changes |
| CN104181893A (en) * | 2014-08-29 | 2014-12-03 | 河南富业建筑装饰有限公司 | Smart home environment system and smart control method |
-
2015
- 2015-03-07 CN CN201510101380.2A patent/CN104715568A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1700231A (en) * | 2004-05-21 | 2005-11-23 | 株式会社日立制作所 | Managing system, managing method of organism information and program for management |
| KR20110053107A (en) * | 2009-11-13 | 2011-05-19 | (주)인포빌 | A safe control system for harmful workshop |
| CN104040547A (en) * | 2011-12-21 | 2014-09-10 | 皇家飞利浦有限公司 | Method and system to predict physiologic and clinical status changes |
| CN103300819A (en) * | 2012-03-15 | 2013-09-18 | 西门子公司 | Learning patient monitoring and intervention system |
| CN202771426U (en) * | 2012-07-18 | 2013-03-06 | 山西创感科技有限公司 | Health monitoring system based on server-client side |
| CN103279687A (en) * | 2013-06-21 | 2013-09-04 | 镇江冈山电子有限公司 | Individualized health service system based on context aware |
| CN103330554A (en) * | 2013-07-18 | 2013-10-02 | 梁亚楠 | Wearable artificial intelligence wireless Internet of Things security system |
| CN103393416A (en) * | 2013-08-23 | 2013-11-20 | 江苏惠通集团有限责任公司 | TV (television) system based physiological index monitoring system and method |
| CN103744411A (en) * | 2014-02-07 | 2014-04-23 | 上海金牌软件开发有限公司 | Control method related to ZigBee technology for realizing smart home |
| CN104181893A (en) * | 2014-08-29 | 2014-12-03 | 河南富业建筑装饰有限公司 | Smart home environment system and smart control method |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106886158A (en) * | 2015-12-15 | 2017-06-23 | 英业达科技有限公司 | Intelligent home is analyzed and suggesting system for wearing and its method |
| CN105607508A (en) * | 2016-03-24 | 2016-05-25 | 重庆邮电大学 | Smart home device control method and system based on user behavior analysis |
| CN105938648A (en) * | 2016-06-14 | 2016-09-14 | 夏烬楚 | Household safety integrated management system and method |
| CN109507893A (en) * | 2017-09-14 | 2019-03-22 | 宁波方太厨具有限公司 | A kind of self study alarm control method of smart home device |
| CN109507893B (en) * | 2017-09-14 | 2021-10-29 | 宁波方太厨具有限公司 | Self-learning alarm control method for intelligent household equipment |
| CN108845076A (en) * | 2018-04-25 | 2018-11-20 | 北京市电话工程有限公司 | A kind of air-quality monitoring system of cell |
| CN109003414A (en) * | 2018-06-20 | 2018-12-14 | 中译语通科技（青岛）有限公司 | A kind of electronic security system and working method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104715568A (en) | Big data system and method for family environment monitoring | |
| KR101695596B1 (en) | Noxious gas monitoring system using mobile terminal | |
| CN104796275B (en) | Abnormal state processing method, system and device | |
| CN111115400B (en) | System and method for detecting elevator maintenance behavior in an elevator hoistway | |
| CN107273263B (en) | Abnormal operation analysis method, application terminal and monitoring server | |
| US10735908B2 (en) | Systems and apparatuses for detecting unmanned aerial vehicle | |
| CN104598369B (en) | The software supervision method and apparatus realized in a mobile device | |
| CN105320701B (en) | Screening technique, device and the terminal of function point test implementation | |
| KR101687477B1 (en) | A Method for Providing Event Occurrence Information Using Big Data and A System for the Same | |
| CN103530562A (en) | Method and device for identifying malicious websites | |
| CN106453767A (en) | Method and device for detecting failure after dropping | |
| US20180174065A1 (en) | Content-Level Anomaly Detection for Heterogeneous Logs | |
| JP6371177B2 (en) | Gateway device, data processing system, and data processing method | |
| CN104363131A (en) | Electric power communication protocol exception detection method based on dynamic extensible finite state | |
| CN113395251B (en) | Machine learning security scene detection method and device | |
| CN103268644A (en) | Communication equipment inspection system | |
| CN105045114B (en) | A kind of information processing method, cloud service platform and information processing system | |
| CN110019626A (en) | A kind of the determination method and relevant apparatus of population distribution information | |
| CN108446207B (en) | Method, device and system for evaluating disaster tolerance capability of computer system | |
| CN114706895A (en) | Emergency event plan recommendation method and device, storage medium and electronic equipment | |
| CN103501487A (en) | Method, device, terminal, server and system for updating classifier | |
| CN115884213A (en) | Resource scheduling method and device and electronic equipment | |
| CN109450853A (en) | Malicious websites determination method, device, terminal and server | |
| CN115617622A (en) | Error occurrence history list and alarm service platform and system supporting same | |
| CN107819761A (en) | Data processing method, device and readable storage medium storing program for executing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20150617 |
|
| RJ01 | Rejection of invention patent application after publication |