CN102736607A - Living security health remote monitoring system based on data integration - Google Patents
Living security health remote monitoring system based on data integration Download PDFInfo
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Abstract
The invention discloses a living security health remote monitoring system based on data integration and relates to a living security health remote monitoring system which is assembled on an intelligent wheelchair. Aiming at the living environment at which the intelligent wheelchair is used, the living security health remote monitoring system is used for determining monitoring factors of environment security and human body health, selecting a wireless sensor network based on the ZigBee technology according to the characteristics of each monitoring factor, carrying out environment security and human body health index monitoring, and alarming according to danger information; in order to improve the accuracy of the alarming information, the data integration technology is used while processing the sensor information integrated into the intelligent wheelchair; for three important indexes in the security alarming, a BP (back propagation) neural network method is adopted for data integration treatment; on the basis, the judgment accuracy of the system to dangerous events is improved; the problem of false alarm rate in the security health remote monitoring system is solved; and the purpose of living security health remote monitoring of the intelligent wheelchair is achieved.
Description
Technical field
The present invention relates to multisensor safety and Health monitoring technical field, particularly a kind of household safety and Health remote monitoring method that is assemblied in intelligent wheel chair.
Background technology
Progress along with medical science and social medical system; The mankind have solved a series of puzzlement human diseases gradually; Make the human beings'health level obtain large increase, human mean lifetime prolongs gradually, and the problem of an aging population of entire society becomes increasingly conspicuous thereupon; Along with social senilization's process is accelerated; And reasons such as disease, disaster, traffic hazard cause the increase of physical disabilities' quantity of damage, and the elderly and physical disabilities raising that quality of life and health supervision are required, as the smart machine in the domestic environment; Intelligent wheel chair should also should not possess household safety monitoring in the environment for use and the healthy function of monitoring user only as walking-replacing tool.
The development of household safety and Health monitor system, domestic environment are as the space of people's life, and its security is very important, and fire hazard is the main hazard factor in the domestic environment, in case receive heavy losses because fire falls in breaking out of fire people's lives and properties.
Existing fire alarm system adopts the cable technology single-sensor to carry out the establishment of fire sensor network more.Fire alarm system based on cable technology has been tending towards ripe at present.Yet wire communication mode scalability is poor; It is loaded down with trivial details to connect up; Influence attractive in appearance, and owing to adopt rigid line to connect, circuit easy ageing or suffer burn into damaged by rats, wearing and tearing; And there is deviation in single-sensor to the judgement of fire attribute, so wired alarming system failure incidence and false alarm rate are higher.
Along with the development of wireless sensor network with the number integration technology, with solving wired existing problem of fire alarm system, multi-sensor information fusion is judged from the multiple attribute that fire takes place, and improves the accuracy that fire is judged; Wireless mode has increased dirigibility, the extensibility of system, from improving system performance.
Early stage long distance monitoring technical research, early stage, in order to guard critically ill patient, what most of hospitals adopted is the means of video monitoring, this is the blank of remote medical monitor.Early 1960s subsequently is slower to the tele-medicine activity development of the mid-80, is regarded as first generation tele-medicine.First tele-medicine plan of the U.S. starts from nineteen fifty-nine, at a distance of setting up the closed-circuit television net between two hospitals of 112 miles the mental hygiene service is being provided.
From the later stage eighties, be accompanied by improving constantly of modern communication technology, second generation tele-medicine grows up gradually.In the implementation process of Telemedicine System; With the fastest developing speed is the U.S. and the Western European countries; The communication mode that adopts is communication via satellite and ISDN(Integrated Service Digital Network) mostly, has obtained bigger progress at aspects such as military medicine, telereference, remote medical consultation with specialists, Remote Transmission of Medical Infonnation.
Long-distance education worldwide largest at present, that coverage rate is the widest and tele-medicine network are the tele-medicine networks in the Georgia State, USA education medical system, and this medical education system can carry out multiple communication activity such as wired, wireless and satellite communication.Breathing, body temperature, heart rate and other physiological parameter of US military in order to guard the soldier studied a kind of personal status monitor and has been specifically designed to the use in wartime.
Along with computer science, communication network technology, data fusion technology, theoretical the developing rapidly of motion control; For multiple smart machine in the domestic environment combines together theories technique support is provided, has therefore invented out a kind of novel household safety and Health monitoring system.
Therefore be badly in need of a kind of intelligent height, the household safety and Health remote supervision system that integration is strong based on data fusion.
Summary of the invention
In view of this, technical matters to be solved by this invention provides a kind of intelligent high, the household safety and Health remote supervision system based on data fusion that integration is strong.
The objective of the invention is to realize like this:
Household safety and Health remote supervision system based on data fusion provided by the invention comprises wheelchair, and said wheelchair is provided with sensor device, telegon and information data processor;
Said sensor device is used to obtain environmental information data and health information data and through wireless-transmission network information data is sent to telegon;
Said telegon is used for the information data that the collecting sensor device obtains and is transferred to the information data processor;
Said information data processor is used to handle the information data that receives, and confirms corresponding hazardous location according to the result of information data, and the control wheelchair leaves the hazardous location.
Further, also comprise the communication module that is arranged on the wheelchair, said communication module is connected with the information data processor, and said information data processor determines whether to send result and send alerting signal to remote handset according to the information data result.
Further; Said sensor device comprises environment temperature sensor, combustable gas concentration sensor, smoke transducer, CO concentration sensor, pulse transducer and temperature sensor for human body, and said environment temperature sensor, combustable gas concentration sensor, smoke transducer, CO concentration sensor, pulse transducer and temperature sensor for human body send to information data on the telegon through wireless-transmission network respectively.
Further, the wireless-transmission network of said sensor device adopts the ZigBee wireless sensor network of star-network topological structure.
Further, said communication module adopts the GSM network to realize telecommunication.
Further, said telegon is the ZigBee telegon.
Further; Said information data processor comprises the BP neural metwork training module that is used to train structure BP neural network; The input quantity of said BP neural metwork training module is process normalization treatment temperature, smog and CO concentration data, and the output vector of said BP neural metwork training module comprises naked light, smoldering fire and safe probability.
Further; Said information data processor comprises the Data Fusion module that is used for handling according to the information data that the neural metwork training module is obtained sensor device judgement; Said Data Fusion module comprises local message pretreatment system, neural network emerging system and decision system
Said local message pretreatment system is used for gathering and the pre-service original information data;
Said neural network emerging system is used to extract the characteristic that the local message pretreatment system is exported signal;
Said decision system is used for making a strategic decision according to characteristic information;
Further, the hidden neuron number in the BP neural network is 6 ~ 13 in the said BP neural metwork training module.
Further, said information data processor comprises alarm information processing module and GSM/3G communication module;
Said alarm information processing module is used to handle the data that household safety and Health remote supervision system collects;
Said GSM/3G communication module is used to send household safety and Health information and warning message.
Said remote interaction comprises wireless routing module and long-range PC;
Said wireless routing module is used to connect the internet, uploads the data that household safety and Health monitoring system is gathered;
Said long-range PC is used to receive or store the data that household safety and Health monitoring system is gathered, and sends the remote interaction control command.
The invention has the advantages that: the present invention adopts sensor information to realize through wireless sensor network, has solved the line monitoring system inconvenience, increases the dirigibility and the extensibility of system; Adopted the data fusion technology,, then the detected signal of sensor network has been judged through the BP neural network, controlled communication module according to differentiating the result at last the BP neural network that the training of BP neural network algorithm obtains; It is high to have solved the false alarm rate of intelligent wheel chair in security alerting system, and the problem of mobility difference has reached the purpose of intelligent wheel chair to household safety and health remote monitoring at last.
Other advantage of the present invention, target and characteristic will be set forth in instructions subsequently to a certain extent; And to a certain extent; Based on being conspicuous to those skilled in the art, perhaps can from practice of the present invention, obtain instruction to investigating of hereinafter.Target of the present invention and other advantage can be passed through following instructions, claims, and the structure that is particularly pointed out in the accompanying drawing realizes and obtains.
Description of drawings
In order to make the object of the invention, technical scheme and advantage clearer, will combine accompanying drawing that the present invention is made further detailed description below, wherein:
Fig. 1 is the structural representation based on the household safety and Health remote monitoring method of data fusion;
Fig. 2 is based on data fusion level synoptic diagram in the household safety and Health remote monitoring method of data fusion;
Fig. 3 is based on BP neural network structure figure in the household safety and Health remote monitoring method of data fusion;
Fig. 4 is the training error curve synoptic diagram of BP neural network;
Fig. 5 is the annexation synoptic diagram of each module in the information data processor.
Embodiment
Below will combine accompanying drawing, the preferred embodiments of the present invention will be carried out detailed description; Should be appreciated that preferred embodiment has been merely explanation the present invention, rather than in order to limit protection scope of the present invention.
Embodiment 1
Based on the household safety and Health monitoring system of data fusion, mainly comprise the various environmental factor monitorings in the family, the function of remote alarms, and the physical signs (pulse, body temperature, blood pressure etc.) that has the user is carried out monitoring function.The purpose of system design is to provide safer for the elderly or physical disabilities, and is comfortable, life style easily, and system comprises that mainly environmental monitoring, physical signs detect and three aspects of security alarm.
Fig. 1 is the structural representation based on the household safety and Health remote monitoring method of data fusion; As shown in the figure: the household safety and Health remote supervision system based on data fusion provided by the invention; Comprise wheelchair, said wheelchair is provided with sensor device, telegon, information data processor and communication module
Said sensor device is used to obtain environmental information data and health information data and through wireless-transmission network information data is sent to telegon; Said sensor device comprises environment temperature sensor, combustable gas concentration sensor, smoke transducer, CO concentration sensor, pulse transducer and temperature sensor for human body, and said environment temperature sensor, combustable gas concentration sensor, smoke transducer, CO concentration sensor, pulse transducer and temperature sensor for human body send to information data on the telegon through wireless-transmission network respectively; Choosing different sensor monitors factors such as pyric factor, antitheft invasion, body temperature pulses respectively.
Said telegon is used for the information data that the collecting sensor device obtains and is transferred to the information data processor;
Said information data processor is used to handle the information data that receives, and confirms corresponding hazardous location according to the result of information data, and the control wheelchair leaves the hazardous location.
Said communication module is connected with the information data processor, and said information data processor determines whether to send result and send alerting signal to remote handset according to the information data result.
The wireless-transmission network of said sensor device adopts the ZigBee wireless sensor network of star-network topological structure.Said communication module adopts the GSM network to realize telecommunication.Said telegon is the ZigBee telegon.
ZigBee wireless sensor network major function in the native system is data acquisition, handles on the information data processor (being PC) of data processing in intelligent wheelchair system, and the telecommunication between system and the user realizes through the GSM network.Total system is made up of wireless sensor node, coordinator node, intelligent wheel chair and GSM data transmission module.The system global structure design comprises; Wireless sensor network adopts the star-network topological structure; The ZigBee child node is gathered infrared monitoring, environment temperature, disaster hidden-trouble, human pulse and body temperature information thereof and is turned back to the ZigBee telegon, then telegon with information transmission to the PC on the intelligent wheel chair.PC carries out handled to data and judges through the BP neural network that trains; Exist if any hazards (as: gas leak, fire alarm, illegal invasion, physical signs are unusual etc.); Communication module will be sent short message through the GSM network and in time reported to the police to family's member's mobile phone; Host computer carries out control operation to intelligent wheel chair simultaneously, makes its flee danger zone through location or navigation, and the wheelchair user is shifted.
Fig. 2 is based on data fusion level synoptic diagram in the household safety and Health remote monitoring method of data fusion; Fig. 3 is based on BP neural network structure figure in the household safety and Health remote monitoring method of data fusion; Fig. 4 is the training error curve synoptic diagram of BP neural network; Fig. 5 is the annexation synoptic diagram of each module in the information data processor; As shown in the figure: be used to train the BP neural metwork training module that makes up the BP neural network provided by the invention comprising based on information data processor described in the household safety and Health remote supervision system of data fusion; The input quantity of said BP neural metwork training module is process normalization treatment temperature, smog and CO concentration data, and the output vector of said BP neural metwork training module comprises naked light, smoldering fire and safe probability.
Said information data processor comprises the Data Fusion module that is used for handling according to the information data that the neural metwork training module is obtained sensor device judgement; Said Data Fusion module comprises local message pretreatment system, neural network emerging system and decision system
Said local message pretreatment system is used for gathering and the pre-service original information data;
Said neural network emerging system is used to extract the characteristic that the local message pretreatment system is exported signal;
Said decision system is used for making a strategic decision according to characteristic information;
Annexation between said BP neural network emerging system and the Data Fusion module is seen Fig. 5.
Said information data processor comprises alarm information processing module and GSM/3G communication module;
Said alarm information processing module is used to handle the data that household safety and Health remote supervision system collects;
Said GSM/3G communication module is used to send household safety and Health information and warning message.
Said remote interaction comprises wireless routing module and long-range PC;
Said wireless routing module is used to connect the internet, uploads the data that household safety and Health monitoring system is gathered;
Said long-range PC is used to receive or store the data that household safety and Health monitoring system is gathered, and sends the remote interaction control command.The annexation synoptic diagram of each module in the said information data processor (being PC) is seen Fig. 5.
Embodiment 2
The embodiment of the invention 2 is the neural metwork training module in the information data processor that on the basis of embodiment 1, provides and the embodiment of Data Fusion module, describes in detail as follows.
According to the theory of data fusion, be the data fusion structure that example is explained this system to take fire alarm signal, this data fusion structure is a three-decker: Information Level, characteristic layer and decision-making level.The collection of raw data and pre-service are at Information Level; Characteristic layer is accomplished the data fusion to Information Level output signal, carries out feature extraction; Decision-making level is used to make a strategic decision from the information of characteristic layer fully, and final the realization made a strategic decision.
Select temperature, smog and CO concentration as fire information in the system design, and, choose the network training sample according to Chinese naked light standard SH4 and smoldering fire standard SH1.
The BP neural network is referring to Fig. 3, and u and y are respectively input, output vector, and input quantity is respectively temperature, smog and CO gas; Be output as the differentiation of naked light, smoldering fire and three kinds of situation probability of happening of safety.Node is used for representing each neuron, and whole network is made up of input layer, latent layer and output layer node.According to network demand, latent layer can be for one deck also can be multilayer, and the node of front and back connects through weighing, and its topological diagram is the feedforward network of directed acyclic graph.
The household safety and Health remote monitoring method based on data fusion of present embodiment, the BP network training comprises the steps:
1. latent layer design
An important theorem of BP network can be approached with single BP network that conceals layer for a continuous function in any closed interval, and n ties up the mapping that m ties up because the BP network of three layers (single latent layers) just can be accomplished arbitrarily.
The selection of hidden neuron number is the problem of more complicated in the neural network design process, generally all could confirm that according to designer's experience and a large amount of experiments a complete desirable explanation formula is not expressed.The training requirement of hidden neuron number and whole network, input-output unit number have direct relation.The selection of hidden neuron number is unreasonable will cause the e-learning time long, can't reach Optimal Error, reduce fault freedom, influence that the sample do not seen before can't be discerned, therefore seek best hidden neuron number and be very important through experiment.Formula (2) can be used as the reference formula of selecting best hidden neuron number:
K is a sample number in the formula, n
1Be the hidden neuron number, n is the input block number.If i＞n,
In the formula, m is the output unit number, and n is the input block number, a ∈ [1,10].
3)n
1＝log
2n （3）
In the formula, n is the input block number.
According to top formula, select according to sample data, selecting the hidden neuron number is between 6 ~ 13, through network training study, relatively selects suitable hidden neuron number according to convergence and error.
2. network learning procedure
1) Sample selection: respectively from excel file data1 and data2 with data importing, the corresponding input of data1 sample, data2 is an output sample.
2) then the sample that reads is carried out sample normalization.
3) use tansig and logsig to be transport function; Use traingdx training function; Use different latent layers unit number n to train function and its convergence is compared, through repeatedly relatively when a latent layer unit is 8 during network training, the neural network better astringency; Error ratio is less, and the therefore final stealthy unit number of selecting is 8 to carry out network training.
3. confirm the training function, accomplish network training
Through top experiment relatively, confirm that the hidden neuron number is 8 after, compare the final training function (traingdx) of selecting in convergence to various training functions.
Confirm final network structure such as table 1 according to top step:
Table 1BP neural network is provided with
Training parameter is set:
Training step number between twice reality is 50, and learning rate is 0.05, and momentum factor is 0.9, and the frequency of training maximal value is 12000, surpasses 12000 training and finishes; The minimum performance gradient is 3e-3;
Use training sample to train, the BP neural network is after through 3464 training, and the training error curve of BP neural network is as shown in Figure 4.
4. the neural network after checking is trained
Because sample had passed through the normalization processing before the training function; So when the BP network that use trains, need carry out normalization to experimental data handles; Must carry out prior normalization with function here and handle, the experimental data that can data processing become can be used to predict then; The checking result who obtains is a normalization data, and therefore last simulation result will carry out anti-normalizing with function, and output data at this moment is only needed predicting the outcome.
Picked at random group data are verified the BP neural network that trains from the standard of Chinese Industrial Standards (CIS) naked light SH4, standard smoldering fire SH1; If being set, probability＞0.7 is the corresponding event generation; Make comparisons according to experimental result and potential result, draw the designing requirement that BP neural network after the training satisfies system.Compare with the single-sensor warning system, can improve the accuracy of warning, reduce false alarm, improved the overall performance of system based on the multi-sensor information fusion of BP nerual network technique.
The above is merely the preferred embodiments of the present invention, is not limited to the present invention, and obviously, those skilled in the art can carry out various changes and modification and not break away from the spirit and scope of the present invention the present invention.Like this, belong within the scope of claim of the present invention and equivalent technologies thereof if of the present invention these are revised with modification, then the present invention also is intended to comprise these changes and modification interior.
Claims (10)
1. based on the household safety and Health remote supervision system of data fusion, comprise wheelchair, it is characterized in that: said wheelchair is provided with sensor device, telegon and information data processor;
Said sensor device is used to obtain environmental information data and health information data and through wireless-transmission network information data is sent to telegon;
Said telegon is used for the information data that the collecting sensor device obtains and is transferred to the information data processor;
Said information data processor is used to handle the information data that receives, and confirms corresponding hazardous location according to the result of information data, and the control wheelchair leaves the hazardous location.
2. the household safety and Health remote supervision system based on data fusion as claimed in claim 1; It is characterized in that: also comprise the communication module that is arranged on the wheelchair; Said communication module is connected with the information data processor, and said information data processor determines whether to send result and send alerting signal to remote handset according to the information data result.
3. the household safety and Health remote supervision system based on data fusion as claimed in claim 2; It is characterized in that: said sensor device comprises environment temperature sensor, combustable gas concentration sensor, smoke transducer, CO concentration sensor, pulse transducer and temperature sensor for human body, and said environment temperature sensor, combustable gas concentration sensor, smoke transducer, CO concentration sensor, pulse transducer and temperature sensor for human body send to information data on the telegon through wireless-transmission network respectively.
4. the household safety and Health remote supervision system based on data fusion as claimed in claim 3 is characterized in that: the wireless-transmission network of said sensor device adopts the ZigBee wireless sensor network of star-network topological structure.
5. the household safety and Health remote supervision system based on data fusion as claimed in claim 4 is characterized in that: said communication module adopts the GSM network to realize telecommunication.
6. the household safety and Health remote supervision system based on data fusion as claimed in claim 5, it is characterized in that: said telegon is the ZigBee telegon.
7. the household safety and Health remote supervision system based on data fusion as claimed in claim 6; It is characterized in that: said information data processor comprises the BP neural metwork training module that is used to train structure BP neural network; The input quantity of said BP neural metwork training module is process normalization treatment temperature, smog and CO concentration data, and the output vector of said BP neural metwork training module comprises naked light, smoldering fire and safe probability.
8. the household safety and Health remote supervision system based on data fusion as claimed in claim 7; It is characterized in that: said information data processor comprises the Data Fusion module that is used for handling according to the information data that BP neural metwork training module is obtained sensor device judgement, and said Data Fusion module comprises local message pretreatment system, neural network emerging system and decision system;
Said local message pretreatment system is used for gathering and the pre-service original information data;
Said neural network emerging system is used to extract the characteristic that the local message pretreatment system is exported signal;
Said decision system is used for making a strategic decision according to characteristic information.
9. the household safety and Health remote supervision system based on data fusion as claimed in claim 8 is characterized in that: the hidden neuron number in the said BP neural metwork training module in the BP neural network is 6 ~ 13.
10. the household safety and Health remote supervision system based on data fusion as claimed in claim 9, it is characterized in that: said information data processor comprises alarm information processing module and GSM/3G communication module;
Said alarm information processing module is used to handle the data that household safety and Health remote supervision system collects;
Said GSM/3G communication module is used to send household safety and Health information and warning message.
Said remote interaction comprises wireless routing module and long-range PC;
Said wireless routing module is used to connect the internet, uploads the data that household safety and Health monitoring system is gathered;
Said long-range PC is used to receive or store the data that household safety and Health monitoring system is gathered, and sends the remote interaction control command.
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