CN112040398A - Passenger flow volume statistical method based on RSSI fluctuation characteristics - Google Patents
Passenger flow volume statistical method based on RSSI fluctuation characteristics Download PDFInfo
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- CN112040398A CN112040398A CN202010818856.5A CN202010818856A CN112040398A CN 112040398 A CN112040398 A CN 112040398A CN 202010818856 A CN202010818856 A CN 202010818856A CN 112040398 A CN112040398 A CN 112040398A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
- H04W64/006—Locating users or terminals or network equipment for network management purposes, e.g. mobility management with additional information processing, e.g. for direction or speed determination
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention discloses a passenger flow volume statistical method based on RSSI fluctuation characteristics, which comprises a passenger flow volume statistical system, wherein the passenger flow volume statistical system comprises a wireless signal transmitter, a wireless signal receiver and a computing platform, preferably, the wireless signal transmitter is used for periodically transmitting wireless signal broadcast frames, a typical wireless signal transmitter is a low-power-consumption Bluetooth device, preferably, the wireless signal receiver is used for receiving wireless signals transmitted by the wireless signal transmitter, analyzing the wireless signal broadcast frames, extracting information such as received signal strength RSSI values, wireless signal transmitter identifications and the like, and transmitting the information to the computing platform for processing through a network interface. The invention can adopt the low-power consumption Bluetooth equipment during implementation, does not need complex wiring and can realize rapid and low-cost deployment. The human body detection method provided by the invention is less influenced by external environmental factors, and can effectively avoid various false identifications.
Description
Technical Field
The invention relates to the technical field of digital marketing, in particular to a passenger flow volume statistical method based on RSSI fluctuation characteristics.
Background
In recent years, a digital marketing technology driven by big data, cloud computing and AI technology becomes an important means for intelligent and digital transformation from an off-line store, and the passenger flow rate refers to the number of people who get in and out of a business place in unit time, directly reflects the popularity of the business place, is one of the most important indexes in the digital marketing technology, and how to accurately and efficiently acquire the passenger flow rate data becomes one of the key problems to be solved in the digital marketing field.
In addition to the traditional manual counting statistical method, the currently common automated passenger flow statistical techniques include: an infrared induction statistical method, a WiFi probe statistical method and a video analysis statistical method.
The infrared induction statistical method realizes passenger flow volume counting by detecting the blocking effect of human body blocking on the infrared inductor, is simple to realize and has lower cost, but has poorer statistical accuracy because the infrared light is easily interfered by external factors; further, this method cannot determine whether a customer is in or out of a store, and it is difficult to satisfy the need for comprehensive passenger flow analysis.
The WiFi probe method indirectly counts the number of people by detecting the MAC address of the mobile equipment carried by a customer, and can also distinguish the customer from the store by utilizing the change of the received signal intensity.
The video statistical method is that a camera is installed in a store, the collected video is analyzed, and passenger flow volume is counted by utilizing a mobile detection or human face human shape recognition technology, so that the method is high in accuracy, the passenger flow video is visual and visible, in order to realize accurate passenger flow statistics, the video statistical method has higher requirements on installation and deployment of the camera, and the environmental illumination condition can influence the accuracy of the passenger flow statistics; moreover, this method requires capturing of a portrait or a human figure, with the risk of privacy violation.
Disclosure of Invention
The invention aims to provide a passenger flow volume statistical method based on RSSI fluctuation characteristics, which has the advantages of high precision and no invasion to privacy and solves the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a passenger flow volume statistical method based on RSSI fluctuation characteristics comprises a passenger flow volume statistical system, wherein the passenger flow volume statistical system comprises a wireless signal transmitter, a wireless signal receiver and a computing platform.
Preferably, the wireless signal transmitter is operable to periodically transmit a broadcast frame of a wireless signal, and a typical wireless signal transmitter is a bluetooth low energy device.
Preferably, the wireless signal receiver is configured to receive a wireless signal transmitted by the wireless signal transmitter, parse a wireless signal broadcast frame, extract information such as a received signal strength RSSI value and a wireless signal transmitter identifier, and send the information to the computing platform through the network interface for processing.
Preferably, the computing platform receives the detection information sent by the wireless signal receiver, and executes a passenger flow volume statistical algorithm to obtain a passenger flow volume statistical result.
Preferably, the implementation method of the invention comprises the following steps:
the method comprises the following steps: the method for counting the passenger flow comprises the following steps that 1 wireless signal receiver R is arranged on one side of a customer entrance and exit door of a store, 2 wireless signal transmitters T1 and T2 are arranged on the other side of the customer entrance and exit door of the store, and the execution process of the method for counting the passenger flow is as follows:
(1) t1, T2 periodically transmits wireless signals containing self identification to the surroundings; r receives the wireless signal broadcast frames from T1 and T2, analyzes the RSSI value of the received signal strength and the ID of the transmitting equipment from the broadcast frames, and sends the RSSI value and the ID of the transmitting equipment together with the timestamp information of the signal receiving moment to the computing platform through a network interface.
(2) When a customer passes through the door, due to the blocking effect of the human body on the wireless signals, R detects obvious RSSI value fluctuation, collects the RSSI value fluctuation and sends the RSSI value fluctuation to the computing platform.
Step two: the computing platform stores the received detection information, executes a passenger flow statistical algorithm according to history and newly received ID, RSSI and timestamp information of the transmitting equipment, computes the number of the in-out shops of the customers, and can output the computation result to a display interface in real time for displaying or output externally through a data communication interface.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention can adopt the low-power consumption Bluetooth equipment during implementation, does not need complex wiring and can realize rapid and low-cost deployment.
2. The human body detection method provided by the invention is less influenced by external environmental factors, and can effectively avoid various false identifications.
3. The technical means adopted by the invention does not need to collect any equipment ID or human body characteristics, and has no privacy invasion risk to customers.
Drawings
FIG. 1 is a schematic diagram of the system deployment of the present invention;
FIG. 2 is a flow chart of an embodiment of the present invention;
FIG. 3 is a process for executing a passenger flow statistics algorithm according to an embodiment of the present invention.
In the figure: 1. a passenger flow volume statistical system; 2. a wireless signal transmitter; 3. a wireless signal receiver; 4. a computing platform.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-3, as shown in fig. 1, a passenger flow volume statistical method and system based on RSSI fluctuation characteristics relates to a wireless signal transmitter 2, a wireless signal receiver 3 and a computing platform 4.
The wireless signal emitter 2 is a wireless device which broadcasts the ID information of the wireless signal emitter periodically, the wireless signal emitted by the wireless signal emitter can be detected by the wireless signal receiver 3, a typical wireless signal emitter 2 is a low-power iBeacon device, the iBeacon utilizes the low-power Bluetooth technology, the broadcast frame can be sent to the periphery periodically, and the broadcast frame is identified by three fields, namely UUID (universal unique identifier), Major and Minor.
The wireless signal receiver 3 comprises a wireless signal interception module and a communication interface module, wherein the wireless signal interception module is used for intercepting the broadcast frame from the wireless signal transmitter 2 and analyzing and extracting the information in the broadcast frame; the latter is responsible for establishing a communication connection with the computing platform 4, which may be a WiFi wireless link based on the IEEE 802.11 standard or a wired network connection based on the IEEE 802.3 standard.
When a customer passes between the wireless signal transmitter 2 and the receiver, the wireless signal receiver 3 can detect obvious RSSI fluctuation due to the blocking effect of a human body on wireless signals, which is the basic principle of the invention for detecting the human body, and in order to detect the RSSI fluctuation more sensitively, the wireless transmitter and the receiver are arranged at the same height, and the height is flush with the upper half of the human body, and the value range is 1.1-1.3 meters.
The computing platform 4 collects the detection information reported by the wireless receiver, executes a passenger flow volume statistical algorithm, and obtains passenger flow volume data, namely the number of the customers going in and out of the shop, wherein the passenger flow volume data can be displayed on a local screen in real time and can also be output outwards through a data communication interface.
As shown in fig. 2, the passenger flow volume statistical method according to the embodiment of the present invention includes the following steps:
S201-S202: the 2 wireless transmitters transmit wireless broadcast frames containing self-identification information to the surroundings at constant power, for example, a typical wireless transmitter is a low-power iBeacon device, and the iBeacon device can be made to transmit the broadcast frames containing self-identification on one or more broadcast channels at set power by a configuration tool.
In the embodiment of the invention, because the distance between the wireless transmitter and the wireless receiver is very close, the transmitting power of the wireless transmitter can be reduced to save power consumption; on the other hand, in order to prevent the customer from missing the detection, the transmission frequency of the broadcast frame should be increased, for example, the transmission frequency may be set to 10 frames per second, that is, the transmission interval time of the broadcast frame is 100 milliseconds.
In order to simplify the description of the flow of the method of the invention, the embodiment of the invention only uses 2 wireless transmitters, and in actual implementation, more wireless transmitters can be deployed according to the field situation to improve the coverage and the measurement accuracy, and the principle provided by the invention is also applicable to the deployment scene with the number of the wireless transmitters more than 2.
S203: the wireless receiver receives broadcast frames transmitted from various wireless transmitters on a plurality of broadcast channels, e.g., for iBeacon devices, of the 40 channels it defines, 37-39 channels, i.e., 2402Mhz, 2428Mhz, 2480Mhz are broadcast channels.
For each received broadcast frame, the wireless receiver analyzes the broadcast frame respectively, and extracts the following information:
(1) RSSI: for a high frequency low power wireless signal such as bluetooth, human body blockage may have a large impact on the RSSI value.
(2) Wireless transmitter identification: the wireless transmitter includes its own identity in the broadcast packet, which is uniquely determined by three fields in the broadcast packet, e.g., for iBeacon devices: UUID, Major, Minor.
(3) Time stamping: the time at which the radio receiver receives the broadcast frame is accurate to milliseconds.
S204: the wireless receiver encapsulates the information extracted from the broadcast frame into data packets, which are sent to the computing platform 4 via the network communication interface.
S205: the computing platform 4 receives the detection information packet from the wireless receiver, stores and executes the passenger flow statistical algorithm after analyzing the detection information packet, and the following describes the execution process of the passenger flow statistical algorithm with reference to fig. 3.
Referring to the deployment diagram of fig. 1, let d1 be the closest distance a customer traverses between 2 wireless transmitters and d2 be the farthest distance a customer traverses between 2 wireless transmitters in meters; let the fastest speed of walking when the customer gets in and out of the store be v1, the slowest speed be v2, the unit is meter/second, define:
Tminand TmaxThe 2 decision thresholds used are required for the present algorithm.
When a customer passes between the wireless transmitter and the receiver, the RSSI value received by the wireless signal receiver 3 has obvious fluctuation, and because a human body mainly consists of moisture, the human body blocking under the condition of straight line short distance can cause the obvious attenuation of the RSSI value, and through experimental tests, the human body blocking can generally cause the attenuation of the RSSI value to be about 5 dBm.
When the RSSI value detected by the radio signal receiver 3 decays 1 time by more than 5dBm, it is recorded as 1 trigger event, the trigger event detected from the radio transmitter 1 is recorded as EV1, and the trigger event detected from the radio transmitter 2 is recorded as EV 2.
As shown in FIG. 3, the algorithm maintains a priority queue with timeout function for EV1 and EV2 events, each type of event enters the queue in sequence according to the occurrence time, and the longest stay time of each event in the queue is TmaxEvents that exceed the threshold are automatically removed.
As shown in fig. 3, the customer-entering behavior determination process of the passenger flow statistics algorithm according to the embodiment of the present invention comprises the following steps:
s301: the algorithm module receives the EV2 event from wireless signal transmitter 2.
S302: executing a shop detection process: scan EV1 queue looking for timestamp txRecord of, txThe conditions are satisfied: t ismin＜tx＜Tmax。
S303: and if one or more records meeting the conditions are found in the step S302, judging that a customer entering behavior is detected, adding 1 to a customer entering amount calculator, deleting a matching record from the EV1 queue, and if a plurality of matching records exist in the EV1, deleting the record with the middle timestamp value.
S304: if no record satisfying the condition is found in step S302, the EV2 event and its timestamp are added to the EV2 queue.
Similarly, when the algorithm module receives the EV1 event, decision steps similar to S301-S304 are performed to detect statistics on customer out-of-store behavior.
In summary, the following steps: the RSSI fluctuation feature-based passenger flow volume statistical method utilizes the fluctuation feature caused by the blocking of a wireless signal by a human body, provides a method for judging and counting the behavior of a customer entering and leaving a store, is simple in deployment of the method and the implementation system thereof, and can realize the accurate statistics of the passenger flow volume with lower cost.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (5)
1. A passenger flow volume statistical method based on RSSI fluctuation characteristics comprises a passenger flow volume statistical system (1), and is characterized in that: the passenger flow volume statistical system (1) comprises a wireless signal transmitter (2), a wireless signal receiver (3) and a computing platform (4).
2. The RSSI fluctuation characteristic-based passenger flow volume statistical method according to claim 1, wherein: the function of the wireless signal transmitter (2) is to periodically transmit wireless signal broadcast frames, and a typical wireless signal transmitter (2) is a bluetooth low energy device.
3. The RSSI fluctuation characteristic-based passenger flow volume statistical method according to claim 1, wherein: the wireless signal receiver (3) is used for receiving wireless signals transmitted by the wireless signal transmitter (2), analyzing wireless signal broadcast frames, extracting information such as received signal strength RSSI values and wireless signal transmitter (2) identifications, and sending the information to the computing platform (4) through a network interface for processing.
4. The RSSI fluctuation characteristic-based passenger flow volume statistical method according to claim 1, wherein: the computing platform (4) receives the detection information sent by the wireless signal receiver (3), and executes a passenger flow volume statistical algorithm to obtain a passenger flow volume statistical result.
5. The RSSI fluctuation characteristic-based passenger flow volume statistical method according to claim 1, wherein: the implementation method of the invention comprises the following steps:
the method comprises the following steps: the method is characterized in that 1 wireless signal receiver (3) R is arranged on one side of a customer entrance of a store, 2 wireless signal transmitters (2) T1 and T2 are arranged on the other side of the customer entrance, and the passenger flow statistical method provided by the invention comprises the following steps:
(1) t1, T2 periodically transmits wireless signals containing self identification to the surroundings; r receives wireless signal broadcast frames from T1 and T2, analyzes the RSSI value of the received signal strength and the ID of the transmitting equipment from the broadcast frames, and sends the RSSI value and the ID of the transmitting equipment together with the timestamp information of the signal receiving moment to a computing platform (4) through a network interface;
(2) when a customer passes through the doorway, due to the blocking effect of the human body on the wireless signals, R detects obvious RSSI value fluctuation, collects the fluctuation RSSI value and sends the fluctuation RSSI value to a computing platform (4);
step two: the computing platform (4) stores the received detection information, executes a passenger flow statistical algorithm according to history and newly received information of the ID, RSSI and timestamp of the transmitting equipment, computes the number of the in-out shops of the customers, and outputs the computed result to a display interface in real time or outputs the computed result to the outside through a data communication interface.
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Application publication date: 20201204 |