KR102069095B1 - System and method for energy efficient WiFi people counter - Google Patents

Abstract

The present invention relates to an energy efficient Wi-Fi personnel counting system and method implemented to count floating populations using WiFi technology having an efficient energy management function, wherein a mobile phone transmits a radio signal for using the Internet; The crowd analysis sensor detects radio signals from cell phones to count people and perform crowd analysis.

Description

Energy efficient WiFi people counting system and method {System and method for energy efficient WiFi people counter}

The technical field of the present invention relates to an energy efficient Wi-Fi personnel counting system and method, and more particularly, to an energy efficient Wi-Fi personnel counting system and method implemented to count a floating population by using WiFi technology having an efficient energy management function.

In order to investigate the floating population information, it is the situation that the investigator is used to survey the floating population by hand, and this is also impossible to accurately investigate when a large number of passengers pass, and although age information is very important factor among floating population information, Since the investigator guesses the age only by looking at the appearance of the passenger, it is not enough to collect accurate age information.

Korean Patent Publication No. 10-2013-0082635 (published Jul. 22, 2013), in connection with a map server, identifies the number of mobile population terminals in a specific space through a means of positioning, and measures the floating population in real time. , You can see the floating population of the desired space, avoid the space with a lot of floating population or find a space with a lot of floating population, and limit the space to the shelves in the store to measure the floating population by shelf Disclosed are a floating population analysis system and a method for identifying a product. According to the disclosed technology, a receiving unit for receiving a signal from the positioning means; A data analyzer for analyzing a floating population of a specific space desired by a user using a map including location information and location information received from a receiver; A storage unit for storing data analyzed by the map and data analysis unit; And a transmitter for transmitting the analysis data of the data analyzer to the user terminal.

Korean Patent Publication No. 10-2013-0015336 (published Feb. 14, 2013) discloses a system, an apparatus, a method, and a terminal therefor for providing commercial information, and provides information about incoming or outgoing calls of one or more terminals from a plurality of base stations. A commercial area information providing apparatus for receiving call traffic information, statisticizing the received call traffic information, calculating floating population information for each region according to the statistical traffic information, and providing the calculated floating population information; A floating population information database for dividing the floating population information on the call traffic information into at least one classification of date, day of the week, time, gender, and age according to subscriber information; And a subscriber information database storing subscriber information of subscribers who make and receive calls or make calls through the terminal. According to the disclosed technology, it is possible to provide a floating population distribution for each region by obtaining the floating population information from the call traffic information of the subscriber in units of a plurality of sectors included in the base station-based cell, the incoming or outgoing call of the subscriber in the mobile communication system Whenever a call occurs, it is possible to extract the floating population by region by collecting subscriber information based on the location information of each subscriber, and by providing the business owners with a distribution of customers for a specific commercial area in the form of maps, It can be used as an analysis data for establishing marketing strategies in stores or newly opened stores.

Crowd Analytics as described above is very important in understanding people's behavior in a non-intrusive way to improve the services provided to citizens (applied in smart cities), consumers in malls (marketed appli- cations), and the like. As application increases, end users of crowd analysis say it is an improved version of the technology. Accordingly, WiFi sensing technology having high commercialization potential has been developed as compared to the conventional technology used for offline real-time floating population analysis.

The conventional personnel counting system as described above has a problem such that the constant power supply is required and the internet is always connected for communication with a server, and thus a large-scale sensor infrastructure such as a smart city is constructed. If this is necessary, high initial infrastructure investment costs (eg, additional costs such as electric work, Internet work, etc.) are required, and there is a problem in that operation and management costs are high when using mobile networks such as 3G and LTE.

In the conventional personnel counting system as described above, when the WiFi detection sensor is used, the user collects data when the smartphone's WiFi is turned on (ie, turned on) or connected to the AP. Since the method is adopted, there is also a problem of providing relatively low counting accuracy. In the case of mobile WiFi detection sensors, data consumption for data transmission, portability for temporary installation, and power consumption for reducing energy-related costs need to be improved.

Korean Patent Publication No. 10-2013-0082635 Korean Patent Publication No. 10-2013-0015336

The problem to be solved by the present invention is to solve the problems or necessity as described above, and to implement an energy-efficient Wi-Fi personnel counting system and method implemented to count the floating population by using the WiFi technology having an efficient energy management function To provide.

According to one aspect of the present invention, there is provided a means for solving the above problems, a mobile phone for transmitting a radio signal for using the Internet; And a crowd analysis sensor for detecting a wireless signal transmitted from the mobile phone to count the personnel and performing a crowd analysis.

In one embodiment, the mobile phone transmits multiple messages per second while connected to the network, or when the mobile phone is not connected to the network, transmits a wireless signal at a predetermined time unit to search the network, or locates the location detection module. When the service is activated, one or more of the steps is performed by searching for a router by transmitting a radio signal at a predetermined time unit, or randomly changing a MAC address every predetermined time in iOS.

In one embodiment, the mobile phone is characterized by transmitting a radio signal for each channel for using the Internet.

In one embodiment, the crowd analysis sensor, characterized in that it comprises a WiFi scanner that is activated at a predetermined part time.

In one embodiment, the crowd analysis sensor, it is characterized in that to collect the radio signal while changing the channel in the order of 1, 5, 9, 13, 2, 6, 10, 3, 7, 11, 4, 8, 12. It is done.

In one embodiment, the crowd analysis sensor, the data of the MAC address, chip manufacturer, time from the data collected from the mobile phone, characterized in that the overlapped data per unit time in the form of desired data and transmits to the server side do.

In one embodiment, the crowd analysis sensor, characterized by periodically generating a survival signal for identifying the presence of a scanner and transmits to the server side.

In one embodiment, the survival signal is characterized in that it comprises information of temperature, memory usage, CPU usage.

In one embodiment, the crowd analysis sensor is characterized by sampling the software receiver to decode preset WiFi channels per hour and search for WiFi activity.

In one embodiment, the crowd analysis sensor, it characterized in that the multiple detection with a time interval less than a predetermined time from the same mobile phone.

In one embodiment, the crowd analysis sensor, characterized in that for measuring the number of mobile phones activated in a specific time period modified by MAC randomization as the number of persons located in a specific location.

In an embodiment, the crowd analysis sensor may scan a frequency band for a preset time and wait for a preset time.

In one embodiment, when the crowd analysis sensor uses a sampling algorithm to determine a sampling rate or sample rate for optimal performance, the sampling rate or sample rate is reduced than before, when the amount of activity is very small. It is characterized by.

In an embodiment, the crowd analysis sensor may be installed in plural numbers, collect data at each installation location, and select a predetermined number of installation locations according to the data collection result at each installation location.

In one embodiment, the crowd analysis sensor, characterized in that to perform the time-based sampling and data-based sampling when performing the sampling algorithm.

In one embodiment, the crowd analysis sensor, during time based sampling, operates for 'X' seconds and enters sleep mode for 'Y' seconds, or operates for 'X1' seconds and turns off for 'Y1' seconds, It is characterized in that it is turned on for 'X2' seconds until 'Xn', or turned off for 'Yn' seconds and randomly receives random values for 'N' seconds.

In one embodiment, the crowd analysis sensor, in the data-based sampling, characterized in that the decision about 'X' and 'Y' based on the data found during the last N detection rounds.

In one embodiment, the crowd analysis sensor, when detecting that the change significantly compared to the number of previously detected mobile phones during the last time activated, characterized in that the value of 'X' and 'Y' to reduce to 'Z'% do.

In an embodiment, the crowd analysis sensor may determine whether the data unit time preset when the wireless signal is detected elapses, and generate a new unit time data set when the data unit time elapses. .

In one embodiment, the crowd analysis sensor, if the data unit time has not elapsed or after creating a new unit time data set, checks whether the data set MAC address is duplicated, and not the duplicate data set MAC address In this case, the detection information is recorded in the unit time data set.

In one embodiment, the crowd analysis sensor checks whether the total dataset size is greater than or equal to a preset transmission size, and transmits the detection information recorded when the total dataset size is greater than or equal to a preset transmission size to the server side. It features.

In one embodiment, the crowd analysis sensor, the IoT interface unit for receiving a wireless signal transmitted from the mobile phone and delivers the received information; A WiFi wireless module unit for detecting the WiFi signal transmitted from the mobile phone and transmitting sensing information; A controller for counting personnel and performing crowd analysis according to the received information transmitted from the IoT interface unit or the sensing information transmitted from the WiFi wireless module unit; A memory unit for storing programs and data necessary for the controller and storing counting information or crowd analysis information transmitted from the controller; And a power supply unit supplying power according to the control of the controller.

According to another aspect of the present invention, there is provided a means for solving the above problems, comprising: a mobile phone transmitting a radio signal for using the Internet; And a crowd analysis sensor detecting the wireless signal to count the personnel and performing crowd analysis.

Advantageous Effects of the Invention The present invention provides an energy-efficient Wi-Fi personnel counting system and method implemented to count floating populations using WiFi technology with efficient energy management, eliminating the need for constant power and communicating with servers. There is no need to be connected to the Internet at all times, so the initial investment of infrastructure is low even when constructing a large sensor infrastructure, and the operation and management costs are reduced by using the existing WiFi network. Even in the off state (i.e., off), it is possible to detect a high level of radio signal of a finely transmitted mobile phone and provide high count accuracy.

1 is a diagram illustrating an energy efficiency Wi-Fi personnel counting system according to an exemplary embodiment of the present invention.
FIG. 2 is a diagram illustrating WiFi frequency band and channel characteristics detected by the crowd analysis sensor in FIG. 1.
FIG. 3 is a diagram illustrating detection control of a crowd analysis sensor in FIG. 1.
4 is a diagram illustrating a crowd analysis sensor in FIG. 1.
5 is a view illustrating an energy efficiency Wi-Fi head counting method according to an embodiment of the present invention.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art may easily implement the present invention. However, since the description of the present invention is merely an embodiment for structural or functional description, the scope of the present invention should not be construed as being limited by the embodiments described in the text. That is, since the embodiments may be variously modified and may have various forms, the scope of the present invention should be understood to include equivalents for realizing the technical idea. In addition, the objects or effects presented in the present invention does not mean that a specific embodiment should include all or only such effects, the scope of the present invention should not be understood as being limited thereby.

The meaning of the terms described in the present invention will be understood as follows.

Terms such as "first" and "second" are intended to distinguish one component from another component, and the scope of rights should not be limited by these terms. For example, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. When a component is referred to as being "connected" to another component, it should be understood that there may be other components in between, although it may be directly connected to the other component. On the other hand, when a component is said to be "directly connected" to another component, it should be understood that there is no other component in between. On the other hand, other expressions describing the relationship between the components, such as "between" and "immediately between" or "neighboring to" and "directly neighboring", should be interpreted as well.

Singular expressions should be understood to include plural expressions unless the context clearly indicates otherwise, and terms such as "include" or "have" refer to features, numbers, steps, operations, components, parts, or parts thereof described. It is to be understood that the combination is intended to be present and does not exclude in advance the possibility of the presence or addition of one or more other features or numbers, steps, actions, components, parts or combinations thereof.

All terms used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. Generally, the terms defined in the dictionary used are to be interpreted to coincide with the meanings in the context of the related art, and should not be interpreted as having ideal or excessively formal meanings unless clearly defined in the present invention.

An energy efficiency Wi-Fi personnel counting system and method according to an embodiment of the present invention will now be described in detail with reference to the accompanying drawings.

1 is a view illustrating an energy efficiency Wi-Fi personnel counting system according to an embodiment of the present invention, FIG. 2 is a view illustrating WiFi frequency bands and channel characteristics detected by the crowd analysis sensor of FIG. 1, and FIG. It is a figure explaining the detection control of the crowd analysis sensor in FIG.

1 to 3, the energy efficiency Wi-Fi personnel counting system 100 includes a plurality of mobile phones 110, a crowd analytics sensor 120, and a network 130.

The mobile phone 110 transmits a wireless signal (or message) for using the wireless Internet through the network 130 to the network 130 even when the mobile phone 110 is connected or not connected to the network 130.

In one embodiment, mobile phone 110 transmits multiple messages per second while connected to network 130 (eg, with WiFi on), or network 130. ) Is not connected to the network 130 (for example, 10 to 20 seconds) in order to search for the network 130 when WiFi is turned off (for example, WiFi is off). Attempts to search for and transmits a radio signal for searching, or improves or improves the accuracy of the location when the location service of the location detection module provided therein is activated. Attempt to search for routers (e.g. WiFi routers), depending on a number of factors, but send a radio signal for discovery every preset time (e.g. 20 to 60 seconds), or iOS Preset time ( For example, every 50 minutes) (or, it is possible to perform one or more of such that each time it detects a significant change in the environment) to change the MAC address at random.

In one embodiment, the mobile phone 110 receives a response message from a wireless router (or a router) after transmitting a radio signal for using the Internet for each channel 1 to 13, and one of the channels. You can select and perform communication.

The crowd analysis sensor 120 senses a radio signal transmitted from the mobile phone 110 to count people and perform crowd analysis such as dwell time distribution, revisit pattern, and flow.

In an embodiment, the crowd analysis sensor 120 may include a WiFi scanner that is activated only for a part time set in advance for energy efficiency, and senses a wireless signal transmitted from the mobile phone 110 using the WiFi scanner. In this case, for example, 1, 5, 9, 13, 2, 6, etc. in order to change the channel can collect the radio signal. Here, the WiFi frequency band and the channel characteristics, as shown in Figure 2, in the WiFi communication using a frequency band of 2.4 GHz 13 data communication is actually performed, the bandwidth interval with the adjacent channel is 5MHz, There are four channels with 1, 5, 9 and 13 that do not overlap each other.

In an embodiment, the crowd analysis sensor 120 may process information such as MAC address, chip manufacturer, time, etc., from the data collected from the mobile phone 110 using a WiFi scanner into a desired data form per unit time. Can be integrated and sent to a database on the server side.

In one embodiment, the crowd analysis sensor 120, on the server side to periodically output a survival signal (for example, information such as temperature, memory usage, CPU usage, etc.) to determine whether there is an abnormality of the WiFi scanner Can be sent to the database.

In one embodiment, crowd analysis sensor 120 may include a WiFi counter, which samples a software receiver using the WiFi counter to decode WiFi channels (eg, 3 channels per second) and detect WiFi activity. It is possible to perform multiple detections with a time interval smaller than a preset time (for example, about 5 to 30 minutes) from the same mobile phone 110, and also to measure the number of persons located at a specific location. In order to reliably generate the mobile phones 110 using MAC randomization to be counted as one, the number of mobile phones 110 activated in a specific time period modified by MAC randomization may be based on the number.

In one embodiment, the crowd analysis sensor 120, in sampling the software receiver for WiFi channel decoding and WiFi active discovery, scans a frequency band (or spectrum) for a predetermined time (for example, 1 minute). By waiting for a set amount of time (eg 1 minute) and making a smaller sample rate while minimizing inaccuracies, you can reduce the sample rate in the system, ie reduce the sample rate in the system in an efficient direction. have.

In one embodiment, the crowd analysis sensor 120 may include an algorithm (hereinafter, referred to as a “sampling algorithm”) that samples a software receiver for WiFi channel decoding and WiFi active discovery. For optimal performance, the data itself can be used in making decisions about sampling rates (or sample rates), for example, when there is very little activity (e.g. late at night), rather than before. ) Can be reduced.

In an embodiment, the crowd analysis sensor 120 may perform performance analysis on the expected performance of each sampling algorithm for a plurality of sampling algorithms by determining the sampling rate (or sample rate) as described above. In addition, the accuracy of the sampling algorithm may be compared with the reference algorithm by different scenarios.

In one embodiment, the crowd analysis sensor 120 may be installed in a plurality of places, such as shopping malls, shopping streets, convenience stores, etc., and may collect data at each installation place, the total calculated for each installation place And raw data can be collected. In addition, the crowd analysis sensor 120 may select a preset number of installation sites (for example, two locations) according to the data collection result at each installation site when the sampling algorithm is performed, and the total footprint may be determined. When used as a reference result, raw data can be used as input to the sampling algorithm.

In an embodiment, the crowd analysis sensor 120 may perform time-based sampling and data-based sampling when performing a sampling algorithm.

In one embodiment, the crowd analysis sensor 120 may use a time-based sampling algorithm to operate for 'X' seconds and to enter sleep mode for 'Y' seconds, in a time based sampling. Can operate for 'X1' seconds, turn off for 'Y1' seconds, turn on for 'X2' seconds to 'Xn', or turn off for 'Yn' seconds and randomly receive random values for 'N' seconds have. Where X is the sampling time and Y is the off time.

In one embodiment, crowd analysis sensor 120 uses a data-based sampling algorithm, at the time of data-based sampling, based on the data found during the last N detection rounds for 'X' and 'Y'. Decisions can be made, for example, when detecting a significant change compared to the number of mobile phones 110 previously detected during the last activated time, the values of 'X' and 'Y' can be reduced to 'Z'%. In this case, the crowd analysis sensor 120 may consider the number of detections and the change in the number of detections as the main determining variables.

In an embodiment, as shown in FIG. 3, when the crowd analysis sensor 120 detects a wireless signal transmitted from the mobile phone 110 (S301), the crowd analysis sensor 120 checks whether a preset data unit time has elapsed. If the corresponding data unit time has elapsed, a new unit time data set is generated (S303). If the corresponding data unit time has not elapsed or a new unit time data set is generated, the corresponding data set MAC address is generated. In step S304, if the data set MAC address is duplicated, the process returns to step S301. If the data set MAC address is not duplicated, the detection information is stored in the corresponding unit time data set. Record (S305), and then check whether the total dataset size is greater than or equal to the preset transmission size (S306). If the size is not equal to the transmitted size, the process returns to the above-described step S301. If the total data set size is larger than the preset size, the recorded detection information can be transmitted to the server (S307).

The network 130 connects communication between the plurality of mobile phones 110 and the crowd analysis sensor 120 as a wireless communication network to transmit and receive data or signals to each other.

In an embodiment, the network 130 may be a WiFi network, an IoT network, or the like, and may include a router or a router.

Energy efficiency Wi-Fi personnel counting system 100 having the configuration as described above, by implementing the crowd analysis sensor 120 to count the floating population by using the WiFi technology having an efficient energy management function, the constant power supply It does not need to be connected to the Internet at all times to communicate with the server, which means that the initial infrastructure investment is low even when constructing a large-scale sensor infrastructure, and the operation and management costs using the existing WiFi network are low. Even when WiFi is off, it can detect a high level of radio signal from a cell phone which is sent out finely and can provide high count accuracy.

4 is a diagram illustrating a crowd analysis sensor in FIG. 1.

Referring to FIG. 4, the crowd analysis sensor 120 includes an IoT interface 121, a controller 122, a memory unit 123, a power supply unit 124, a WiFi wireless module unit 125, and a display unit 126. It includes.

The IoT interface 121 connects to an IoT network (for example, IoT WAN, LoRa, Sigfox, etc.), transmits and receives data to and from the control unit 122, and also receives a radio signal transmitted from the mobile phone 110. The reception information is transmitted to the control unit 122.

The controller 122 counts the number of people and dwell time distribution, revisit pattern, flow, etc. according to the received information transmitted from the IoT interface unit 121 or the sensing information transmitted from the WiFi wireless module unit 125. Do the same crowd analysis.

According to an embodiment of the present disclosure, the controller 122 may use a low power consumption chip connected to the IoT network and perform power management that is only activated for a part time set in advance for energy efficiency.

In one embodiment, the control unit 122, WiFi wireless to collect the WiFi signal while changing the channel in the order of 1, 5, 9, 13, 2, 6, 10, 3, 7, 11, 4, 8, 12 The module unit 125 may be controlled.

In one embodiment, the control unit 122, the received information transmitted from the IoT interface unit 121 or the sensing information delivered from the WiFi wireless module unit 125, such as MAC address, chip manufacturer, time, etc. per unit time The duplicated data can be processed and integrated into a desired data form and transmitted to the database on the server side through the IoT interface 121.

In an embodiment, the controller 122 periodically outputs a survival signal (for example, information on temperature, memory usage, CPU usage, etc.) in order to determine whether there is a sensor abnormality, or the IoT interface 121. Can be sent to a database on the server side.

In one embodiment, the controller 122 samples the WiFi wireless module unit 125 to control the WiFi wireless module unit 125 to decode WiFi channels (for example, three channels per second) and search for WiFi activity. In addition, the WiFi wireless module unit 125 may be controlled to perform multiple detections having a time interval smaller than a preset time (for example, about 5 to 30 minutes) from the same mobile phone 110.

In one embodiment, the controller 122 counts the number of mobile phones 110 activated at a specific time period modified by MAC randomization so that the mobile phones 110 using MAC randomization are counted as one, and counts them at a specific location. You can measure the number of people located.

According to an embodiment, the controller 122 may scan the frequency band (or spectrum) for a preset time (for example, 1 minute) and wait for the preset time (for example, 1 minute) of the WiFi wireless module unit 125. By reducing the sample rate in the system, that is, by reducing the sample rate in the system, the sample rate in the system can be reduced in an efficient direction.

In one embodiment, the controller 122 may use the data itself in determining the sampling rate (or sample rate) for optimal performance using a sampling algorithm for low power consumption when detecting wireless signals. For example, if the amount of activity is very low (eg late night), the sampling rate (or sample rate) may be reduced than before.

In an embodiment, the controller 122 may perform performance analysis on the expected performance of each sampling algorithm for a plurality of sampling algorithms by determining a sampling rate (or a sample rate) using the sampling algorithm. The accuracy of the sampling algorithm may be compared with the reference algorithm by different scenarios.

According to an embodiment, the control unit 122 may select a preset number of installation sites (for example, two locations) according to the data collection result at each installation site when the sampling algorithm is performed, and also the entire footprint. When used as a reference result, raw data can be used as input to the sampling algorithm.

According to an embodiment, the controller 122 may perform a sampling algorithm based on time and a sampling algorithm based on data when the sampling algorithm is executed.

In one embodiment, the controller 122, when time-based sampling, the WiFi wireless module unit 125 to operate for 'X' seconds and enter the sleep mode for 'Y' seconds using a time-based sampling algorithm. The WiFi wireless module unit 125 can be controlled to operate, or operate for 'X1' seconds, turn off for 'Y1' seconds, turn on for 'X2' seconds to 'Xn', or turn off for 'Yn' seconds and randomly The WiFi wireless module unit 125 may be controlled to receive a random value for 'N' seconds.

In an embodiment, the controller 122 may make a decision regarding 'X' and 'Y' based on data found during the last N detection rounds, using a data-based sampling algorithm during data-based sampling. For example, if it detects a significant change compared to the number of mobile phones 110 previously detected during the last activated time, the values of 'X' and 'Y' may be reduced to 'Z'%.

According to an embodiment of the present disclosure, the control unit 122 may check whether the preset data unit time has elapsed when receiving the reception information from the IoT interface unit 121 or the sensing information from the WiFi wireless module unit 125. If the corresponding data unit time has elapsed, a new unit time data set can be generated.

According to an embodiment of the present disclosure, when the corresponding data unit time has not elapsed or after generating a new unit time data set, the controller 122 may check whether the corresponding data set MAC address is duplicated, If not, the detection information can be recorded in the unit time data set, and then it can be checked whether the total data set size is larger than the preset transmission size.

According to an embodiment, the controller 122 may transmit the recorded detection information to the server through the IoT interface 121 when the total data set size is larger than or equal to a preset transmission size. Network power consumption can be reduced by adjusting the transmission size. In addition, the controller 122 may compress and transmit the detection information.

Programs and data necessary for the control operation of the memory unit 123 and the control unit 122 are stored, and information (that is, counting information or crowd analysis information) transmitted from the control unit 122 is stored.

The power supply unit 124 supplies power required for each component under the control of the control unit 122.

In one embodiment, the power supply unit 124 may include a small battery or a rechargeable battery.

The WiFi wireless module unit 125 senses the WiFi signal transmitted from the mobile phone 110 and transmits the sensing information to the controller 122.

The display unit 126 displays the control operation and the state of the control unit 122 and the like.

The crowd analysis sensor 120 having the above-described configuration may control the WiFi wireless module unit 125 so that the controller 122 performs detection of WiFi signals transmitted from the mobile phone 110 at low power. In addition, the crowd analysis sensor 120 not only does not have to use the WiFi wireless module unit 125 for long distance data transmitted to the backend (backend), but also can reduce the total power consumption of the system during data transmission. Compressed total coefficients, which are both elements, can consume less data.

5 is a view illustrating an energy efficiency Wi-Fi head counting method according to an embodiment of the present invention.

Referring to FIG. 5, in the mobile phone 110, even when connected to or not connected to the network 130, a wireless signal (or message) for using the wireless Internet through the network 130 may be transmitted to the network 130. (S501).

In transmitting the radio signal (or message) to the network 130 in step S501 described above, the cellular phone 110 may transmit multiple messages per second while being connected to the network 130. When not connected to the network 130, the mobile phone 110 attempts to search the network 130 for a predetermined time (for example, 10 to 20 seconds) to search for the network 130. In this case, a radio signal for searching may be transmitted. When the location service of the location detection module provided therein is activated, the mobile phone 110 attempts to search for a nearby wireless router (for example, a WiFi router) to improve or improve the accuracy of the location. In this case, although it may vary depending on many factors, a radio signal for searching may be transmitted every predetermined time (for example, 20 to 60 seconds). In the case of iOS, the mobile phone 110 may randomly change the MAC address every predetermined time (for example, 50 minutes) (or whenever detecting an important change in the environment). The mobile phone 110 may perform one or more of the above-described operations.

In transmitting the radio signal (or message) to the network 130 in the above-described step S501, the cellular phone 110 transmits a radio signal for using the Internet for each channel 1 to 13 and then radios the radio signal. A response message may be received from a router (or a router) to select one channel and perform communication.

When the wireless signal (or message) is transmitted to the network 130 in the above-described step S501, the crowd analysis sensor 120 senses the wireless signal transmitted from the mobile phone 110 and counts the number of people (S502). .

In counting the personnel in step S502 described above, the crowd analysis sensor 120 may sense a wireless signal transmitted from the mobile phone 110 using a WiFi scanner. For example, the crowd analysis sensor 120 may collect radio signals while changing channels in order of 1, 5, 9, 13, 2, 6, and the like.

In counting the personnel in step S502 described above, the crowd analysis sensor 120 may sample the software receiver using a WiFi counter to decode WiFi channels (eg, 3 channels per second) and search for WiFi activity. In addition, multiple detections having a time interval smaller than a preset time (for example, about 5 to 30 minutes) from the same mobile phone 110 may be performed together.

In counting the personnel in step S502 described above, the crowd analysis sensor 120, the mobile phone activated in a specific time period modified by MAC randomization in order to be able to count the mobile phone 110 using MAC randomization as one ( The number of 110 may be measured by the number of personnel located at a particular location.

In counting the personnel in step S502 described above, the crowd analysis sensor 120 scans the frequency band (or spectrum) for a preset time (eg, 1 minute) and waits for the preset time (eg, 1 minute). You can do that.

In counting the personnel in step S502 described above, the crowd analysis sensor 120 may use the data itself in determining the sampling rate (or sample rate) for optimal performance using a sampling algorithm. For example, if the amount of activity is very low (eg late night), the sampling rate (or sample rate) may be reduced than before.

In counting the number of persons in step S502 described above, the crowd analysis sensor 120 performs performance on the expected performance of each sampling algorithm for a plurality of sampling algorithms by determining the sampling rate (or sample rate) as described above. Analysis can be performed and the accuracy of the sampling algorithm can also be compared with reference algorithms by different scenarios.

In counting the personnel in step S502 described above, the crowd analysis sensor 120 may collect data at each installation location, where the total and raw data calculated for each installation location may be collected. In addition, the crowd analysis sensor 120 may select a preset number of installation sites (for example, two locations) according to the data collection result at each installation site when the sampling algorithm is performed, and the total footprint may be determined. When used as a reference result, raw data can be used as input to the sampling algorithm.

In counting the number of persons in step S502, the crowd analysis sensor 120 may perform time-based sampling and data-based sampling at the time of performing the sampling algorithm.

In counting the personnel in step S502 described above, the crowd analysis sensor 120, during time-based sampling, operates for 'X' seconds and enters a sleep mode for 'Y' seconds, using a time-based sampling algorithm. Can be turned on, operate for 'X1' seconds, turn off for 'Y1' seconds, turn on for 'X2' seconds to 'Xn', turn off for 'Yn' seconds, and randomly receive random values for 'N' seconds You can do that.

In counting the personnel in step S502 described above, the crowd analysis sensor 120, at the time of data-based sampling, uses a data-based sampling algorithm, based on the data found during the last N detection rounds, 'X' and 'Y'. ', For example, if it detects a significant change relative to the number of mobile phones 110 previously detected during the last time it was activated, the value of' X 'and' Y 'is reduced to' Z '%. Can be.

In counting the personnel in step S502, when the crowd analysis sensor 120 detects a radio signal transmitted from the mobile phone 110, it checks whether the preset data unit time has elapsed, and the corresponding data unit time If a new unit time dataset is created after the elapsed time has elapsed, and if the data unit time has not elapsed or a new unit time data set is created, the data set MAC address is checked for overlap and the corresponding data set is checked. If the MAC address is not duplicated, the detection information can be recorded in the corresponding unit time data set.

After counting the personnel in step S502 described above, the crowd analysis sensor 120 allows to perform crowd analysis such as dwell time distribution, revisit pattern, and flow (S503).

In performing the crowd analysis in the above-described step S503, the crowd analysis sensor 120, duplication of information such as MAC address, chip manufacturer, time, etc. per unit time in the data collected from the mobile phone 110 using a WiFi scanner The processed data can be processed and integrated into the desired data format and sent to the database on the server side.

In performing the crowd analysis in the above-described step S503, the crowd analysis sensor 120, the survival signal (for example, temperature, memory usage, CPU usage information, etc.) for identifying the abnormality of the WiFi scanner Can be created periodically and sent to the database on the server side.

In performing the crowd analysis in the above-described step S503, the crowd analysis sensor 120 checks whether the total data set size is greater than or equal to the preset transmission size, and when the total data set size is greater than or equal to the preset transmission size. Recorded detection information can be sent to the server.

As described above, the embodiment of the present invention is not implemented only through the above-described apparatus and / or operation method, but through a program for realizing a function corresponding to the configuration of the embodiment of the present invention, a recording medium on which the program is recorded, and the like. The implementation may be easily implemented by those skilled in the art to which the present disclosure pertains based on the description of the above-described embodiments. Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements of those skilled in the art using the basic concepts of the present invention defined in the following claims are also provided. It belongs to the scope of rights.

100: energy efficient wifi personnel counting system
110: cell phone
120: crowd analysis sensor
121: IoT interface unit
122: control unit
123: memory
124: power supply
125: WiFi wireless module
126: display unit
130: network

Claims (5)

A mobile phone which receives a response message from a wireless router or a router and transmits a radio signal for each channel to use the Internet to select one of the channels and perform communication; And a crowd analysis sensor for detecting a radio signal transmitted from the mobile phone to count the personnel and perform a crowd analysis; The crowd analysis sensor collects the wireless signal while changing channels in a set sequence, and periodically generates a survival signal for identifying a scanner abnormality and transmits it to the server. The survival signal includes a temperature, memory usage, Includes information of CPU usage;
The crowd analysis sensor uses a sampling algorithm to sample a software receiver for WiFi channel decoding and WiFi active discovery to determine a sampling rate or sample rate for optimal performance; Performing time-based sampling and data-based sampling when performing a sampling algorithm; During time-based sampling, either operate for 'X' seconds and enter sleep mode for 'Y' seconds, or operate for 'X1' seconds, turn off for 'Y1' seconds, and turn on for 'X2' seconds to 'Xn' Or, turn off for 'Yn' seconds and randomly receive a random value for 'N' seconds, where X is the sampling time and Y is the Off time; At data-based sampling, the energy efficient Wi-Fi personnel counting system makes decisions regarding 'X' and 'Y' based on data found during the last N detection rounds.
The method of claim 1, wherein the mobile phone,
When connected to a network, multiple messages per second are sent, or when not connected to a network, a wireless signal is sent by a preset time unit to search a network, or when a location service of a location detection module is activated. Energy efficient Wi-Fi counting system, characterized in that it performs one or more of transmitting a radio signal in units of time to search for a router, or randomly changing a MAC address every predetermined time in iOS.
delete The method of claim 1, wherein the crowd analysis sensor,
An energy-efficient Wi-Fi counting system, comprising: a WiFi scanner that is activated at a preset part time.
Transmitting a radio signal for each channel to use the Internet so that the cellular phone receives a response message from a wireless router or a router and selects one of the channels to perform communication; And causing the crowd analysis sensor to detect the radio signal to count personnel and perform crowd analysis; The crowd analysis sensor collects the wireless signal while changing channels in a set sequence, and periodically generates a survival signal for identifying a scanner abnormality and transmits it to the server. The survival signal includes a temperature, memory usage, Includes information of CPU usage;
The crowd analysis sensor uses a sampling algorithm to sample a software receiver for WiFi channel decoding and WiFi active discovery to determine a sampling rate or sample rate for optimal performance; Performing time-based sampling and data-based sampling when performing a sampling algorithm; During time-based sampling, either operate for 'X' seconds and enter sleep mode for 'Y' seconds, or operate for 'X1' seconds, turn off for 'Y1' seconds, and turn on for 'X2' seconds to 'Xn' Or, turn off for 'Yn' seconds and randomly receive a random value for 'N' seconds, where X is the sampling time and Y is the Off time; In data-based sampling, energy efficient Wi-Fi counting method characterized by making decisions regarding 'X' and 'Y' based on data found during the last N detection rounds.

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