KR101845283B1 - Method for monitoring environment of nonsmoking area - Google Patents

Abstract

The present invention relates to a method for monitoring the environment of a nonsmoking area. The present invention includes a sensor group for generating at least one sensor data that is different from each other, a server for generating environment information by statistically analyzing the sensor data and providing the environment information, and an output device for outputting the environment information. According to the present invention, more accurate environment information can be generated through the accumulation of sensor data and statistical analysis of the sensor data. So, highly reliable environment information can be provided. Further, highly reliable environment information can be generated by changing statistical analysis technique in correspondence with an input parameter. Accordingly, the present invention can selectively provide highly reliable environment information requested by a user. On the other hand, environment information can be used for visualization, enforcement, and the like. So, it is possible to intuitively recognize the environmental condition of an area, and can be used for determining the timing and frequency of enforcement.

Description

METHOD FOR MONITORING ENVIRONMENT OF NONSMOKING AREA

The present invention relates to a smoking cessation environment monitoring method, and more particularly, to a smoking cessation monitoring method for monitoring smoking cessation area using statistical analysis of sensor data.

Smoking can cause harm to secondhand smoke not only to smokers but also to nonsmokers. Smoking is prohibited in public places such as bus stops. If smoking is detected in the smoking area, penalties and penalties are imposed.

However, various monitoring methods and control methods of smoking cessation areas have been attempted, but it is difficult to monitor and control the smoking cessation area in real time due to the lack of citizen participation and lack of enforcement agents due to the disclosure of the declarant.

In addition, since it is simply monitored using only the level of the sensor data, the accuracy is also low.

Therefore, a reliable monitoring technique is required, and it is necessary to provide the control and environmental information based on the monitoring technique.

Korean Patent Publication No. 2010-0116465 (published on November 11, 2010)

SUMMARY OF THE INVENTION The present invention has been made in order to solve the problems of the prior art described above, and it is an object of the present invention to provide a method and apparatus for generating highly reliable environmental information through statistical analysis of sensor data, The present invention also provides a method for monitoring the environment of a smoking cigarette.

According to another aspect of the present invention, there is provided a smoking cesspit environmental monitoring system comprising: a sensor group for generating at least one sensor data different from each other; A server for generating the environment information by changing the statistical technique according to the accumulation amount of the sensor data and the input variable generated in real time, and providing the environment information; And an output device for outputting the environment information.

At this time, the server includes: a sensor data receiving unit for receiving the sensor data transmitted from the sensor group; A data analyzer for generating environmental information by changing a statistical technique according to an accumulation amount of the sensor data and an input variable generated in real time; A storage unit for storing the environment information; And an environment information providing unit for providing the environment information.

Here, the data analyzing unit may include: a cumulative amount determining unit for determining cumulative amount of the sensor data; An input variable determining unit for determining an input variable input in real time; And a statistical processing unit for performing statistical processing while changing an analysis technique from a combination of an accumulation amount of sensor data and an input variable to be generated for each set unit time.

Here, the data analysis unit may include an intermittency determination unit for determining the intermittent period or frequency through statistical analysis; A visualization processing unit for visualizing the statistically analyzed environmental information to generate visual data; And a data sorting and extracting unit for selectively extracting statistical analyzed environment information corresponding to an external request.

Meanwhile, a smoking cessation environment monitoring method of the present invention includes: receiving sensor data from a sensor group, the server being executed by a server; Generating environment information by changing a statistical technique according to an accumulation amount of the sensor data and an input variable generated in real time; And providing the environment information.

At this time, the environment information is used to determine the time and frequency of enforcement by statistical analysis, to generate visual data by visualizing the statistical analyzed environmental information, or to extract the statistical analyzed environmental information in response to an external request .

The input variable may be at least one sensor data generated from a human body sensor, a gas sensor, an illuminance sensor, and a flame sensor.

As described above, according to the smoke monitoring system environmental monitoring system and method according to the present invention, more accurate environmental information can be generated through accumulation of sensor data and statistical analysis thereof, thereby providing highly reliable environmental information. Further, by changing the statistical analysis technique corresponding to the sensor data accumulation amount and input parameters generated in real time, more reliable environmental information can be generated. Therefore, in the present invention, highly reliable environmental information requested by the user can be selectively provided.

On the other hand, environmental information can be used for visualization, interception, and the like, so that it can intuitively recognize the environmental condition of the area, and can be used for determining the timing and frequency of enforcement.

1 is a configuration diagram of a smoking cessation environment monitoring system according to an embodiment of the present invention.
2 is a configuration diagram of a server according to an embodiment of the present invention.
3 is a configuration diagram of a data analysis unit according to an embodiment of the present invention.
4 is a flowchart of a method for monitoring the environment of a smoking area according to an embodiment of the present invention.
5 is a diagram illustrating a display form of a dashboard according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT Hereinafter, the present invention will be described in detail with reference to preferred embodiments of the present invention and the accompanying drawings, wherein like reference numerals refer to like elements.

It is to be understood that when an element is referred to as being "comprising" another element in the description of the invention or in the claims, it is not to be construed as being limited to only that element, And the like.

First, components used in the smoking cessation environment monitoring system of the present invention are as follows.

- Raspberry Pi: A single board PC for development, which collects sensor data in real time from attached sensors and transmits it to the server.

- Human body detection sensor: Detects the presence of human by detecting infrared rays.

- Gas detection sensor: Detects gas components including smoke, etc. and displays the integrated value.

- Illumination detection sensor: It detects the amount of light and performs numerical display function.

- Flame detection sensor: Detects flame and determines the risk of fire.

- Real-time database: Load sensor data received from sensors in real time.

- Cumulative database: Loads sensor data loaded in real-time database on daily, weekly, monthly and yearly basis.

1 is a configuration diagram of a smoking cessation environment monitoring system according to an embodiment of the present invention.

Referring to FIG. 1, the smoking cesspit environmental monitoring system of the present invention includes a sensor group 1 for generating at least one sensor data that is different from each other, a sensor unit 1 for generating environment information by statistically analyzing sensor data, A server 2, and an output device 3 for outputting environmental information.

Here, the sensor group 1 includes a human body detection sensor 11, a gas detection sensor 12, an illumination detection sensor 13, a flame detection sensor 14, and the like. The sensor group 1 may be configured in a raspberry pie. Hereinafter, the sensor group 1 will be referred to as an environmental sensor.

On the other hand, the environmental sensor 1 can be installed together with the output device 3 in a smoking area or the like. Here, the smoking area means a public place such as a bus stop.

As an example, the smoke-free environment monitoring system of the present invention includes Raspberry Pie, which collects data through four environmental sensors 1, sensor data received from a Raspberry Pie via wireless communication such as Wi-Fi, And a web browser for visualizing various environment information based on the environment information transmitted by the cloud server 2 and displaying the environment information on a dashboard or the like as the output device 3 . The present embodiment exemplifies a Wi-Fi wireless communication method by communication between the raspberry pie and the server 2, but it is not limited to a Code Division Multi Access (CDMA), a Time Division Multi Access (TDMA), a Frequency Division Multi Access (FDMA), an Orthogonal Various communication such as Frequency Division Multi Access (SCAN), Single Carrier-FDMA (SCFDMA), Personal Area Network (PAN), Wide Area Network (WAN), Infrared Data Assoication (IrDA) Method can be used.

The computer on which the web browser is operated is a communicable computer device having an internet browser capable of displaying the contents of the web, and may be a personal computer such as a desktop computer or a notebook computer, a mobile phone capable of wireless Internet communication, A cellular phone, a cellular telephone, a cellular phone, a cellular phone, a subscriber unit, a subscriber station, a mobile station, a terminal, a remote station, a personal digital assistant (PDA) Such as a Session Initiation Protocol (SIP) telephone, a wireless local loop (WLL) station, a handheld device having a wireless connection capability, a wireless modem, any device using a wireless connection mechanism, and the like.

As described above, the raspberry pie is constituted by a human body sensor 11, a gas sensor 12, an illuminance sensor 13, a flame sensor 14, etc., It transmits it to the cloud server 2.

The human body detection sensor 11 can use a sensor for detecting infrared rays of a human being. When a human body is detected, the sensor data is transmitted to the cloud server 2 when the sensor value becomes 1.

The gas sensor 12 transmits the sensor data to the cloud server 2 when the sensor value becomes a specific value or more in the case of a smoking situation.

The illuminance detection sensor 13 transmits all the sensor data to the cloud server 2 regardless of the sensor value. This value is used to determine whether the sensor data was received day or night.

The flame detection sensor 14 transmits a warning signal to the cloud server 2 to alert the user of the risk if the flame size is detected.

The sensor data transmitted by the environment sensor 1 is loaded on the cloud server 2, and the cloud server 2 can be configured with a real time DB and a cumulative DB. All sensor data is loaded first in the real-time database, and the loaded sensor data is grouped into daily, weekly, monthly, and yearly units, and then stored in the cumulative DB.

Also, the loaded sensor data is transmitted in real time to the dashboard. Dashboards can be divided into real-time dashboards and cumulative dashboards.

The real-time dashboard displays the received sensor data to the web browser as a graph of the area and a graph of the time frame.

The cumulative dashboard displays the sensor data sent to the web browser on a daily, weekly, monthly, or yearly basis. It also displays graphs by region and time. At this time, graphs such as total area average increase / decrease, total area maximum increase / decrease, total area minimum increase / decrease, total time average increase / decrease, total time maximum increase / decrease, and total time minimum increase / decrease are displayed together. Total local statistical rankings and total time statistical rankings can also be output as text.

2 is a configuration diagram of a server according to an embodiment of the present invention.

2, the server 2 of the present invention includes a sensor data receiving unit 21 for receiving sensor data transmitted from the environment sensor 1, a data analyzing unit 21 for statistically analyzing the sensor data, A storage unit 23 for storing environment information, and an environment information providing unit 24 for providing environmental information.

The server 2 configured as described above receives, for example, sensor data transmitted from the environment sensor 1 and converts it into a database. That is, four kinds of environmental sensors 1 in the sensor part sense and judge whether or not to smoke in the smoking area, and then periodically transmit the sensor data to the server 2. The server 2 loads real-time data received from the Raspberry pie. Then, statistical analysis is performed on the database data of the sensor. The environment information is generated through statistical analysis, and the generated environment information is stored. Thereafter, the server 2 transmits environment information in real time to the dashboard. The dashboard reads the data values and displays the regional graphs and time-of-day graphs in the real-time dashboards and cumulative dashboards, the total area average increase / decrease, the total area maximum increase / decrease, the total area minimum increase / decrease, The maximum increase / decrease amount, the total time minimum increase / decrease amount, and the like. Total area statistical rankings and total time statistical rankings are output as text. On the other hand, when environmental information is requested from the outside, environmental information is selectively provided.

3 is a configuration diagram of a data analysis unit according to an embodiment of the present invention.

3, the data analyzing unit 22 of the present invention includes an accumulation amount determining unit 221 for determining an accumulation amount of sensor data, an input variable determining unit 222 for determining an input variable inputted in real time, And a statistical processing unit 223 for performing statistical processing while changing an analysis technique from a combination of an accumulation amount of sensor data and an input variable to be generated for each set unit time.

Here, the accumulation amount determination unit may determine the accumulation amount in units of time, and the input variable determination unit may determine the input variable in units of seconds.

A visualization processing unit 225 for visualizing the statistically analyzed environmental information and generating visual data, and a statistical analysis unit 223 for statistically analyzing the statistics And a data selection / extraction unit 226 for selectively extracting the analyzed environment information.

Meanwhile, the data sorting and extracting unit 226 preferably includes a region management unit (not shown) for managing the sensor data by region.

The data analyzer 22 configured as described above statistically analyzes human body sensor data, gas sensor data, illuminance sensor data, and flame sensor data by time. Statistical analysis can be performed by using the environmental information stored in the cumulative database, such as sample survey, data and variables, basic statistical analysis, Kai verification, independence verification, difference verification, variance analysis, covariance analysis, multivariate analysis, Analysis, factor analysis, cluster analysis, survival analysis, discriminant analysis, and multidimensional scaling can be selectively applied. It is preferable that the statistical analysis is continuously changed in accordance with the accumulation amount of the sensor data and the real-time input parameter.

Then, various visual data including text, brightness technique, graph technique, and the like are generated for the statistically analyzed environmental information. The visual data is delivered to the dashboard and displayed. In this embodiment, the time data is generated on the server 2 side, but the time data may be generated on the dashboard. On the other hand, when there is an external request, it is preferable that the statistical analyzed environment information is selectively extracted and provided, and the time data is also transmitted. At this time, it is desirable that the requested environment information is managed for each region so that it can be transmitted in real time.

Hereinafter, a method for monitoring the environment of a smoking area according to the present invention using the system configured as described above will be described.

4 is a flowchart of a method for monitoring the environment of a smoking area according to an embodiment of the present invention.

Referring to FIG. 4, in the environmental sensor 1, human body sensor data, gas sensor data, roughness sensor data, and flame sensor data are generated (S1) and transmitted to the server 2 (S2).

The server 2 statistically analyzes the sensor data to generate environment information (S3), and stores the environment information (S4).

Then, the server 2 transmits the environmental information to the dashboard, which is the output apparatus 3, in real time (S5).

In the dashboard (3), the data values are read and displayed on the real-time dashboard and the cumulative dashboard by region graph and time-of-day graph, total area average increase / decrease, total area maximum increase / decrease, , Total time maximum increase / decrease and total time minimum increase / decrease amount. The total regional statistical ranking and the total time statistical ranking are output as text (S6).

On the other hand, the environmental information is selectively processed by statistical analysis to determine the time and frequency of enforcement, visual data of statistical analyzed environmental information to generate visual data, and selective extraction of statistical analyzed environment information in response to external request (S7).

Here, the process of performing the statistical analysis will be described.

For example, if the gas sensor data stored in the cumulative database is less than 100 per unit time, statistical processing can be performed using the basic statistical analysis technique.

On the other hand, when the gas sensor data stored in the cumulative database is 101 to 200 units per unit time, statistical processing can be performed using the multivariate analysis.

Herein, when the illumination sensor data and the flame sensor data are included as input variables, it can be changed to any one of correlation analysis, regression analysis, factor analysis, cluster analysis, survival analysis, discrimination analysis and multidimensional scaling .

The environment information is generated by changing various statistical techniques corresponding to the accumulation amount of sensor data generated during the set time and input parameters generated in real time.

In this way, the statistical processing is performed while changing the statistical technique model corresponding to the accumulation amount of the sensor data and the input variables generated in real time. Therefore, it is preferable that the statistical technique corresponding to the accumulation amount and the input variable is set and set in advance.

On the other hand, it is preferable that the process of determining the period or frequency of the intermission is performed through the following procedure.

First, in order to generate intermittency data, for example, a three-level level is set. As an example, the gas level is set to 0 to 150 for the first stage, the gas level is set to 151 to 300 for the second stage, and the gas level is set to 301 to 600 for the third stage. That is, the first stage is a state in which a state of quitting is maintained, the second state is a state of being in a state of being quit smoking and the state of being in the boundary of smoking, and the third state is a state of smoking.

At this time, a combination of the illuminance detection sensor 13 and the flame detection sensor 14 is performed at each of the above-mentioned steps. When the change rate of change over the set time is equal to or greater than the set value, A combination of detection sensor data is made. Preferably, even if the illumination sensor data is in a brightness comparable to that of the daytime, if the flame sensor data is equal to or greater than the predetermined value, smoking is surely performed, so intermittency data is generated. When the illumination sensor data is brightness equivalent to night When the flame detection sensor data is less than the set value, the smoking status is not clear, so no intermission data is generated.

[Example 1]

All the environmental sensors 1 indicate that they are always operating, not only at a specific moment. The human body detection sensor 11 outputs the sensor value 1 when the person's approach is detected in the smoking area where the raspberry pie is installed and outputs 0 when the approach is not detected. When a person approaches the cigarette, the sensor value of the gas detection sensor 12 is 400 or more and normally 100 to 150. Through this, it is judged whether or not the smoker is accessing the smoking area. In the case of the illuminance sensor 13, a relatively high amount of light is detected during the daytime, and a relatively low amount of light is detected during the night time. At this time, when smoking is detected in the smoking area through the human body sensor 11 and the gas sensor 12, all data is transmitted to the cloud server 2 in real time. Also, in case the smoker does not turn off the cigarette properly, the flame sensor 14 detects whether there is a nearby flame. If a flame of a size that is of a fire hazard is detected, the risk is transmitted to the cloud server (2).

[Example 2]

As shown in FIG. 5, the dashboard 3 has a dashboard tab that displays, in real time, a value received from a sensor attached to a raspberry pie as a main user interface. Hereinafter, the real time tap is named. On the map-shaped screen, the distribution difference of the sensor values received from the raspberry pie installed in each region is expressed by color brightness. At this time, the brightness varies from one value to the next, and gradually increases from 1 to the maximum value. The two graphs next to the map are graphs that count the smoking status by time zone. It is measured from 0:00 to 24:00, and it is counted whether or not to smoke in the whole country and it is outputted by time zone. It is expressed in bar graph form and line graph form. If you click on a specific region where the sensor is installed in the map graph, a new map type that displays only the region is displayed on the screen, and details of the map, city, group, and sphere can be output. Depending on the displayed range, the time graph for the next time is also displayed on the graph only for the amount of time in the range. The top of the two tabs on the left is the tab for the currently rendered UI, and the second tab is the cumulative dashboard tab showing cumulative counts for each day. Hereinafter, it is called a cumulative tap. The cumulative graph in the cumulative tab is also expressed in two different criteria according to region and time, and cumulative units can be viewed by clicking the date unit button for each day, week, month, and year. If you click the day button, cumulative graph will be output on a daily basis. If you click the week, month, year button, cumulative graph will be output in week, month and year. You can also specify the date range by yourself. At this time, the map graph and time graph are the same as the real time tab. In addition to the two graphs, a ranked chart is also displayed for the accumulation tab. This is also expressed by region and time zone, and the regional chart displays the region counted from the first to the third rank, which is the most counted by the hour among the currently measured regions. The time chart shows the time from the highest time to the third among all the time counts in the whole country.

In one or more exemplary implementations, the functions presented herein may be implemented in hardware, software, firmware, or a combination thereof. When implemented in software, the functions may be stored on or transmitted via one or more instructions or code on a computer readable medium. Computer-readable media includes computer storage media and communication media including any medium for facilitating transfer of a computer program from one place to another. The storage medium may be any general purpose computer or any available medium that can be accessed by a special purpose computer. By way of example, and not limitation, such computer-readable media can comprise any form of computer readable medium, such as RAM, ROM, EEPROM, CD-ROM or other optical disk storage media, magnetic disk storage media or other magnetic storage devices, But not limited to, a general purpose computer, a special purpose computer, a general purpose processor, or any other medium that can be accessed by a particular processor.

In addition, any connection means may be considered as a computer-readable medium. For example, when software is transmitted over a wireless technology such as a coaxial cable, a fiber optic cable, a twisted pair, a digital subscriber line (DSL), or an infrared radio, and a microwave from a web site, server, or other remote source, Wireless technologies such as cable, fiber optic cable, twisted pair, DSL, or infrared radio, and microwave may be included within the definition of such medium. The discs and discs used here include compact discs (CDs), laser discs, optical discs, DVDs, floppy discs, and Blu-ray discs where disc plays the data magnetically, As shown in FIG. The combinations may also be included within the scope of computer readable media.

Those skilled in the art will appreciate that the various illustrative elements, components, logical blocks, modules, and algorithm steps described above may be implemented as electronic hardware, computer software, or combinations thereof. In order to clarify the interchangeability of hardware and software, various illustrative components, blocks, modules and steps have been described in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement these functions in varying ways for each particular application, but such implementation decisions are not necessarily outside the scope of the invention.

The various illustrative logical blocks and modules described in connection with the present disclosure may be implemented or performed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, Or transistor logic, discrete hardware components, or any combination designed to implement the functions described herein. A general purpose processor may be a microprocessor; In an alternative embodiment, such a processor may be an existing processor, controller, microcontroller, or state machine. A processor may be implemented as a combination of computing devices, such as, for example, a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or a combination of such configurations.

For a hardware implementation, the various illustrative logic, logic blocks, and modules of processing units described in connection with the aspects disclosed herein may be implemented with one or more application specific integrated circuits (ASICs), digital signal processors (DSPs) Such as digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), discrete gate or transistor logic, discrete hardware components, general purpose processors, Controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof. The general purpose processor may be a microprocessor, but, in the alternative, it may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices (e.g., a DSP and a microprocessor, a plurality of microprocessors, a combination of one or more microprocessors in conjunction with a DSP core, or any other suitable configuration). Additionally, at least one processor may include one or more modules capable of implementing one or more of the steps and / or operations described herein.

In addition, various aspects or features described herein may be implemented as a method, apparatus, or article of manufacture using standard programming and / or engineering techniques. Moreover, steps and / or operations of a method or algorithm described in connection with the aspects disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. Additionally, in some aspects, steps or acts of a method or algorithm may be present as a machine-readable medium, or as a combination of at least one or any combination of codes or instructions on a computer-readable medium, It can be integrated into computer program stuff. The term article of manufacture as used herein is intended to encompass a computer program accessible from any suitable computer-readable device or medium.

The description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features presented herein.

1: Environmental sensor
2: Server
3: Output device

Claims (7)

delete delete delete A sensor group including a human body sensor, a gas sensor, an illuminance sensor and a flame sensor for generating respective sensor data; A server for generating environmental information by changing a statistical technique according to an accumulation amount of the sensor data and an input variable generated in real time; And an output device for outputting the environment information,
(a) transmitting the human body sensor data, the gas sensor data, the illumination sensor data, and the flame sensor data to a server;
(b) statistical analysis of the sensor data by the server to generate environment information; And
(c) transmitting the environment information to the output device,
The step (b) of generating the environment information by statistically analyzing the sensor data comprises:
The environment information is generated while changing the statistical technique according to the accumulation amount of the sensor data generated during the set time and the input variable generated in real time,
The environment information is used to determine the period or frequency of enforcement by statistical analysis, generate visual data by visualizing the statistically analyzed environmental information, or selectively extract statistical analyzed environmental information in response to an external request,
The data is read from the output device and displayed on a real-time dashboard and a cumulative dashboard by a region graph and a time line graph, a total area average increase / decrease, a total area maximum increase / decrease, A time maximum increase / decrease, or a total time minimum increase / decrease amount, based on a result of the comparison. delete 5. The method of claim 4,
In the step (b) of generating environment information by statistically analyzing the sensor data,
Wherein the combination of the illumination sensor and the flame detection sensor is a combination of the illumination sensor data and the flame detection sensor data when the rate of change during the set time is equal to or greater than a set value. How to monitor. 5. The method of claim 4,
In the step (b) of generating environment information by statistically analyzing the sensor data,
The statistical analysis when the illumination sensor data and the flame sensor data are included as input variables is changed to any one of correlation analysis, regression analysis, factor analysis, cluster analysis, survival analysis, discrimination analysis, and multidimensional scaling Non - smoking area environmental monitoring method.

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