CN114973596A - Individual-living old people monitoring system and method based on federal multi-source data analysis - Google Patents
Individual-living old people monitoring system and method based on federal multi-source data analysis Download PDFInfo
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Abstract
The invention discloses a monitoring system and a monitoring method for the elderly living alone based on federal multi-source data analysis, wherein a controller is used for carrying out power consumption data analysis, water consumption data analysis, indoor video detection analysis and indoor danger alarm analysis; when any one of the analysis data has an alarm condition, the controller controls the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor to improve the monitoring sensitivity; the controller performs power utilization data, water utilization data, indoor video detection and indoor danger alarm analysis again according to data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor after monitoring sensitivity is improved; and the controller predicts the alarm level according to the re-analysis result and starts an alarm scheme according to the alarm level prediction result. The method uses the electric energy and water consumption data from families to judge whether the indoor has abnormal behaviors or not through various data sources.
Description
Technical Field
The invention relates to the technical field of data acquisition and processing, in particular to a monitoring system and a monitoring method for the elderly living alone based on federal multi-source data analysis.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
As the old ages, their mobility and thinking ability are reduced to different degrees, and accidents such as falling down and sudden diseases are easy to happen. Especially for deaf-mute old people, the deaf-mute old people are more prone to some accidents than general old people, and need to attract extra attention. When children and children have full-time work, they do not spend much time in the care of the elderly. The current cost of hiring a full-time caregiver or caregiver is not small and can not be borne by every family. Even for economically-skilled households, caregivers are becoming short-lived as the population becomes more aged.
Most nursing equipment at the present stage is used for detecting the postures of the old, the data source of the method is single, the judgment is easy to make mistakes under certain conditions, and the method has the risk of invading the privacy of the old.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a monitoring system and a monitoring method for the elderly living alone based on the federal multi-source data analysis; the invention combines the idea of federal learning, fixes the data at the local of the detection end for analysis, and only summarizes the judgment result through the network for judgment. Meanwhile, the invention uses the electric energy data and the water consumption data from families and judges whether the indoor has abnormal behaviors or not through various data sources.
In a first aspect, the invention provides a monitoring system for elderly people living alone based on federal multi-source data analysis;
solitary old person monitored control system based on analysis of federal multisource data includes: a controller;
the controller analyzes power utilization data, water utilization data, indoor video detection and analysis and indoor danger alarm according to data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor;
when any one of the analysis data has an alarm condition, the controller controls the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor to improve the monitoring sensitivity;
the controller analyzes the electricity utilization data, the water utilization data, the indoor video detection and analysis and the indoor danger alarm again according to the data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor after the monitoring sensitivity is improved;
and the controller predicts the alarm level according to the re-analysis result and starts an alarm scheme according to the alarm level prediction result.
In a second aspect, the invention provides a method for monitoring solitary old people based on federal multi-source data analysis;
the monitoring method for the elderly living alone based on the federal multi-source data analysis comprises the following steps:
the controller is used for carrying out power utilization data analysis, water consumption data analysis, indoor video detection analysis and indoor danger alarm analysis according to data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor;
when any one of the analysis data has an alarm condition, the controller controls the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor to improve the monitoring sensitivity;
the controller analyzes the electricity consumption data, the water consumption data, the indoor video detection and analysis and the indoor danger alarm again according to the data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor after the monitoring sensitivity is improved;
and the controller predicts the alarm level according to the re-analysis result and starts an alarm scheme according to the alarm level prediction result.
Compared with the prior art, the invention has the beneficial effects that:
compared with the traditional single data source mode, the system analyzes through multiple data sources. The data analysis part of the invention is local, and only the analysis result is uploaded without uploading the original data through the Internet.
The method has rich data sources, can realize the prejudgment and monitoring of various family risks, and can effectively improve the accuracy of risk finding through combined analysis. According to the invention, original data do not need to be uploaded through a network, and privacy information of a user is protected as much as possible through the change of an analysis mode, so that the method is safer to use.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are included to illustrate an exemplary embodiment of the invention and not to limit the invention.
FIG. 1 is a hardware connection framework diagram according to a first embodiment;
fig. 2 is a schematic diagram of a connection of an analysis, detection and early warning model in a controller according to the first embodiment.
Detailed Description
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and it should be understood that the terms "comprises" and "comprising", and any variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiments and features of the embodiments of the present invention may be combined with each other without conflict.
All data are obtained according to the embodiment and are legally applied on the data on the basis of compliance with laws and regulations and user consent.
Example one
The embodiment provides a monitoring system for the elderly living alone based on federal multi-source data analysis;
solitary old person monitored control system based on analysis of federal multisource data includes: a controller;
the controller analyzes power utilization data, water utilization data, indoor video detection and analysis and indoor danger alarm according to data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor;
when any one of the analysis data has an alarm condition, the controller controls the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor to improve the monitoring sensitivity;
the controller analyzes the electricity consumption data, the water consumption data, the indoor video detection and analysis and the indoor danger alarm again according to the data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor after the monitoring sensitivity is improved;
and the controller predicts the alarm level according to the re-analysis result and starts an alarm scheme according to the alarm level prediction result.
Further, as shown in fig. 1, the controller is connected with the electric meter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor respectively.
Further, the ammeter is used for collecting electricity consumption data of the elderly living alone;
the water flow sensor is used for collecting water consumption data of the elderly living alone;
the camera is used for collecting indoor video data of the elderly living alone;
the carbon monoxide sensor is used for collecting the concentration of carbon monoxide in the kitchen of the elderly living alone;
the temperature and humidity sensor is used for collecting temperature data and humidity data of a bedroom of the old people living alone;
the door lock sensor is used for collecting the data of the opening and closing states of the doors of the elderly living alone.
Further, carrying out power utilization data analysis; the method specifically comprises the following steps:
and analyzing the real-time power utilization data acquired by the ammeter by adopting the trained power utilization data analysis model, and outputting a power utilization data analysis result.
Further, the trained electricity consumption data analysis model; the training step comprises:
constructing a first convolutional neural network;
constructing a first training set; the first training set is historical electricity utilization data of all the old people in the whole community with known normal or abnormal labels;
training the first convolution neural network by adopting a first training set to obtain a trained first convolution neural network;
constructing a second training set; the second training set is historical electricity utilization data of the old people to be monitored with known normal or abnormal labels;
training the trained first convolutional neural network by adopting a second training set to obtain a retrained first convolutional neural network; and taking the retrained first convolutional neural network as a trained power utilization data analysis model.
Further, performing water consumption data analysis; the method specifically comprises the following steps:
and analyzing the real-time water consumption data acquired by the water flow sensor by adopting the trained water consumption data analysis model, and outputting a water consumption data analysis result.
Further, the trained water use data analysis model; the training step comprises:
constructing a second convolutional neural network;
constructing a third training set; the third training set is historical water consumption data of all the old people in the whole community with known normal or abnormal labels;
training the second convolutional neural network by adopting a third training set to obtain a trained second convolutional neural network;
constructing a fourth training set; the fourth training set is historical water use data of the old people to be monitored with known normal or abnormal labels;
training the trained second convolutional neural network by adopting a fourth training set to obtain a retrained second convolutional neural network; and taking the retrained second convolutional neural network as a trained water use data analysis model.
Further, the indoor video detection analysis; the method specifically comprises the following steps:
and detecting and analyzing indoor video data collected by a camera installed indoors by adopting the trained indoor video detection model to obtain an indoor video detection and analysis result.
Further, the trained indoor video detection model; the specific training process comprises the following steps:
constructing a third convolutional neural network;
constructing a fifth training set; the fifth training set is historical indoor activity videos of all the old people in the whole community with known normal or abnormal labels;
training the third convolutional neural network by adopting a fifth training set to obtain a trained third convolutional neural network;
constructing a sixth training set; the sixth training set is a historical indoor activity video of the old people to be monitored with known normal or abnormal labels;
training the trained third convolutional neural network by adopting a sixth training set to obtain a retrained third convolutional neural network; and taking the retrained third convolutional neural network as a trained indoor video detection model.
Further, the indoor hazard alarm analysis; the method specifically comprises the following steps:
and detecting and analyzing the kitchen carbon monoxide concentration collected by the carbon monoxide sensor, the bedroom temperature and humidity collected by the temperature and humidity sensor and the door lock opening and closing states corresponding to different time points collected by the door lock sensor by adopting the trained indoor danger alarm model to obtain an indoor danger alarm analysis result.
Further, the trained indoor danger alarm model; the training process comprises the following steps:
constructing a fourth convolutional neural network;
constructing a seventh training set; the seventh training set is the kitchen carbon monoxide concentration, the bedroom temperature and humidity and the door lock opening and closing states corresponding to different time points of all the old people in the whole community with known normal or abnormal labels;
training the fourth convolutional neural network by adopting a seventh training set to obtain a trained fourth convolutional neural network;
constructing an eighth training set; the eighth training set is the kitchen carbon monoxide concentration, the bedroom temperature and humidity and the door lock opening and closing states corresponding to different time points of the old people to be monitored with known normal or abnormal labels;
training the trained fourth convolutional neural network by adopting an eighth training set to obtain a retrained fourth convolutional neural network; and taking the retrained fourth convolutional neural network as a trained indoor danger alarm model.
Further, when any one of the analysis data has an alarm condition, the controller controls the electric meter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor to improve the monitoring sensitivity; and the specific sensitivity improving amplitude is improved according to the preset improving amplitude.
Further, as shown in fig. 2, the controller performs alarm level prediction according to the result of the re-analysis, and starts an alarm scheme according to the alarm level prediction result; the method specifically comprises the following steps:
and inputting the results of the electricity consumption data analysis, the water consumption data analysis, the indoor video detection analysis and the indoor danger alarm analysis into the trained early warning grade classification model, and outputting early warning grades.
Further, the trained early warning grade classification model; the training process comprises the following steps:
constructing a support vector machine classifier;
constructing a ninth training set; the ninth training set is the results of power utilization data analysis, water utilization data analysis, indoor video detection analysis and indoor danger alarm analysis of the known early warning grade classification labels;
and inputting the ninth training set into a support vector machine classifier, training the classifier to obtain a trained support vector machine classifier, and taking the trained support vector machine classifier as a trained early warning grade classification model.
Further, starting an alarm scheme according to the alarm grade prediction result; the method comprises the following steps:
if the grade is 'no risk', no alarm is given;
if the current mobile terminal is in the 'potential risk' level, sending a short message prompt to a mobile terminal of family members of the solitary old people;
if the "at risk" level, the emergency contact is directly called.
The invention mainly uses user electronic box data, user water consumption data, indoor video data, indoor gas data, indoor temperature and humidity data and door and window lock safety detection data.
All data analysis and data collection of the invention are integrated in one device, and when the analysis is carried out, the analysis is carried out locally on the device, and the data does not need to be uploaded through a network.
At system initialization, each analysis model is trained using local machine learning models and user data. All used machine learning models are pre-trained by using general data, and after the machine learning models are deployed to a user family, the machine learning models are trained again so as to be capable of adapting to the specificity of the family habits of the user.
After the emergency contact is confirmed, an emergency call such as 110 or 120 can be dialed through the emergency contact notification module according to the plan and the emergency level.
Example two
The embodiment provides a method for monitoring solitary old people based on federal multi-source data analysis;
the monitoring method for the elderly living alone based on the federal multi-source data analysis comprises the following steps:
the controller is used for carrying out power utilization data analysis, water consumption data analysis, indoor video detection analysis and indoor danger alarm analysis according to data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor;
when any one of the analysis data has an alarm condition, the controller controls the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor to improve the monitoring sensitivity;
the controller analyzes the electricity consumption data, the water consumption data, the indoor video detection and analysis and the indoor danger alarm again according to the data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor after the monitoring sensitivity is improved;
and the controller predicts the alarm level according to the re-analysis result and starts an alarm scheme according to the alarm level prediction result.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. Solitary old person monitor system based on analysis of federal multisource data, characterized by includes: a controller;
the controller analyzes power utilization data, water utilization data, indoor video detection and analysis and indoor danger alarm according to data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor;
when any one of the analysis data has an alarm condition, the controller controls the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor to improve the monitoring sensitivity;
the controller analyzes the electricity consumption data, the water consumption data, the indoor video detection and analysis and the indoor danger alarm again according to the data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor after the monitoring sensitivity is improved;
and the controller predicts the alarm level according to the re-analysis result and starts an alarm scheme according to the alarm level prediction result.
2. The system of claim 1, wherein the controller is connected to an electricity meter, a water flow sensor, a camera, a carbon monoxide sensor, a temperature and humidity sensor, and a door lock sensor.
3. The system for monitoring the elderly living alone based on federal multi-source data analysis as claimed in claim 2, wherein said electric meter is configured to collect electricity consumption data of elderly living alone;
the water flow sensor is used for collecting water consumption data of the elderly living alone;
the camera is used for collecting indoor video data of the elderly living alone;
the carbon monoxide sensor is used for collecting the concentration of carbon monoxide in the kitchen of the elderly living alone;
the temperature and humidity sensor is used for collecting temperature data and humidity data of a bedroom of the old people living alone;
the door lock sensor is used for collecting the data of the opening and closing states of the doors of the elderly living alone.
4. The federal multi-source data analysis based monitoring system for elderly people living alone as claimed in claim 1, wherein electricity consumption data analysis is performed; the method specifically comprises the following steps:
analyzing the real-time electricity utilization data collected by the electricity meter by adopting the trained electricity utilization data analysis model, and outputting an electricity utilization data analysis result;
the trained electricity consumption data analysis model; the training step comprises:
constructing a first convolution neural network;
constructing a first training set; the first training set is historical electricity utilization data of all the old people in the whole community with known normal or abnormal labels;
training the first convolution neural network by adopting a first training set to obtain a trained first convolution neural network;
constructing a second training set; the second training set is historical electricity utilization data of the old people to be monitored with known normal or abnormal labels;
training the trained first convolutional neural network by adopting a second training set to obtain a retrained first convolutional neural network; and taking the retrained first convolutional neural network as a trained power utilization data analysis model.
5. The federal multi-source data analysis-based monitoring system for elderly living alone in accordance with claim 1, wherein water use data analysis; the method specifically comprises the following steps:
analyzing the real-time water consumption data acquired by the water flow sensor by adopting the trained water consumption data analysis model, and outputting a water consumption data analysis result;
the trained water use data analysis model; the training step comprises:
constructing a second convolutional neural network;
constructing a third training set; the third training set is historical water consumption data of all the old people in the whole community with known normal or abnormal labels;
training the second convolutional neural network by adopting a third training set to obtain a trained second convolutional neural network;
constructing a fourth training set; the fourth training set is historical water use data of the old people to be monitored with known normal or abnormal labels;
training the trained second convolutional neural network by adopting a fourth training set to obtain a retrained second convolutional neural network; and taking the retrained second convolutional neural network as a trained water use data analysis model.
6. The federal multisource data analysis based solitary elderly care system as claimed in claim 1, wherein said indoor video inspection analysis; the method specifically comprises the following steps:
detecting and analyzing indoor video data collected by a camera installed indoors by adopting a trained indoor video detection model to obtain an indoor video detection and analysis result;
the trained indoor video detection model; the specific training process comprises the following steps:
constructing a third convolutional neural network;
constructing a fifth training set; the fifth training set is historical indoor activity videos of all the old people in the whole community with known normal or abnormal labels;
training the third convolutional neural network by adopting a fifth training set to obtain a trained third convolutional neural network;
constructing a sixth training set; the sixth training set is a historical indoor activity video of the old people to be monitored with known normal or abnormal labels;
training the trained third convolutional neural network by adopting a sixth training set to obtain a retrained third convolutional neural network; and taking the retrained third convolutional neural network as a trained indoor video detection model.
7. The federal multi-source data analysis based solitary elderly care system as defined in claim 1, wherein said indoor hazard alarm analysis; the method specifically comprises the following steps:
detecting and analyzing kitchen carbon monoxide concentration collected by a carbon monoxide sensor, bedroom temperature and humidity collected by a temperature and humidity sensor and door lock opening and closing states corresponding to different time points collected by a door lock sensor by adopting a trained indoor danger alarm model to obtain an indoor danger alarm analysis result;
the trained indoor danger alarm model; the training process comprises the following steps:
constructing a fourth convolutional neural network;
constructing a seventh training set; the seventh training set is the kitchen carbon monoxide concentration, the bedroom temperature and humidity and the door lock opening and closing states corresponding to different time points of all the old people in the whole community with known normal or abnormal labels;
training the fourth convolutional neural network by adopting a seventh training set to obtain a trained fourth convolutional neural network;
constructing an eighth training set; the eighth training set is the kitchen carbon monoxide concentration, the bedroom temperature and humidity and the door lock opening and closing states corresponding to different time points of the old people to be monitored with known normal or abnormal labels;
training the trained fourth convolutional neural network by adopting an eighth training set to obtain a retrained fourth convolutional neural network; and taking the retrained fourth convolutional neural network as a trained indoor danger alarm model.
8. The standalone elderly monitoring system based on federal multisource data analysis as claimed in claim 1, wherein the controller performs alarm level prediction according to the result of the re-analysis, and starts an alarm scheme according to the alarm level prediction result; the method specifically comprises the following steps:
inputting the results of the electricity consumption data analysis, the water consumption data analysis, the indoor video detection analysis and the indoor danger alarm analysis into the trained early warning grade classification model, and outputting early warning grades;
the trained early warning grade classification model; the training process comprises the following steps:
constructing a support vector machine classifier;
constructing a ninth training set; the ninth training set is the results of power utilization data analysis, water utilization data analysis, indoor video detection analysis and indoor danger alarm analysis of the known early warning grade classification labels;
and inputting the ninth training set into a support vector machine classifier, training the classifier to obtain a trained support vector machine classifier, and taking the trained support vector machine classifier as a trained early warning grade classification model.
9. The federal multisource data analysis-based monitoring system for elderly people living alone of claim 1, wherein the alarm scheme is activated based on the alarm level prediction result; the method comprises the following steps:
if the grade is 'no risk', no alarm is given;
if the current mobile terminal is in the 'potential risk' level, sending a short message prompt to a mobile terminal of family members of the solitary old people;
if the "at risk" level, the emergency contact is directly called.
10. The method for monitoring the solitary old people based on the federal multi-source data analysis is characterized by comprising the following steps:
the controller is used for carrying out power utilization data analysis, water consumption data analysis, indoor video detection analysis and indoor danger alarm analysis according to data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor;
when any one of the analysis data has an alarm condition, the controller controls the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor to improve the monitoring sensitivity;
the controller analyzes the electricity consumption data, the water consumption data, the indoor video detection and analysis and the indoor danger alarm again according to the data collected by the ammeter, the water flow sensor, the camera, the carbon monoxide sensor, the temperature and humidity sensor and the door lock sensor after the monitoring sensitivity is improved;
and the controller predicts the alarm level according to the re-analysis result and starts an alarm scheme according to the alarm level prediction result.
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| CN114267153A (en) * | 2021-12-29 | 2022-04-01 | 苏州英鹏信息科技有限公司 | Home safety monitoring management system |
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