Method and system for testing guidance quality of intelligent upright lamp based on Internet of Things

Abstract

The invention discloses a smart column lamp guidance quality test method and system based on the Internet of Things, and relates to the technical field of smart column lamps, the test system comprises a planning module, an acquisition module, an analysis module and a collection module; according to the invention, repeated testing is carried out in different environments, the guiding performance of the intelligent column lamp under various complex conditions can be comprehensively evaluated, it is ensured that the intelligent column lamp can stably and reliably play a role in different environments, the acquisition module adopts a positioning mode of combining a GPS module and a geomagnetic fingerprint module, the accuracy of position information acquisition is improved, and the accuracy of positioning information acquisition is improved. The real position of the testee on the simulation route can be ensured to be obtained, the collected data is preprocessed through the intelligent gateway and then transmitted to the cloud server through the Wi-Fi module, the latest position information is obtained in time, and the accuracy of the test system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart column lamps, and in particular to a method and system for testing the directional performance of smart column lamps based on the Internet of Things. Background Art

[0002] With the acceleration of the process of urban intelligence, smart column lights, as a facility that integrates lighting and intelligent guidance functions, are increasingly used in public places. They can provide navigation guidance for pedestrians and help people reach their destinations more conveniently.

[0003] At present, the data collection of the guidance performance of smart column lights mainly relies on the single GPS positioning technology. GPS positioning has the problem of insufficient accuracy in some scenarios, resulting in positioning drift, making it difficult to fully and accurately obtain the location information of the tester and the test equipment, thus affecting the accuracy of the evaluation of the guidance performance of the smart column lights; During the guidance test of smart column lights, the focus is mainly on simple statistics and analysis of the positions of testers and test equipment, and only on basic indicators such as whether the preset destination has been reached. There is a lack of in-depth analysis of the detailed deviations between the actual travel path and the preset guidance path. At the same time, the intuitive feelings of the testers during use are ignored, resulting in the test results being unable to reflect the effect of smart column lights in the guidance field.

[0004] Therefore, a smart column lamp guidance test method and system based on the Internet of Things is proposed to solve the above problems. Summary of the invention

[0005] The main purpose of the present invention is to provide a method and system for testing the directional performance of a smart column lamp based on the Internet of Things to solve the problems raised in the above background.

[0006] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a smart column lamp guidance test system based on the Internet of Things, the test system includes a planning module, a collection module, an analysis module and a collection module; The planning module is used to set a simulation route by providing the current actual site through GIS, and set a number of smart column lights along the simulation route. Then the tester uses the test equipment to perform a directional test along the set simulation route in different environments; The acquisition module is used to locate and collect the location information of the tester and the test equipment on the set simulation route in real time through the GPS module and the geomagnetic fingerprint module, and after processing the collected location information through the edge computing module, transmit it to the cloud server through the Wi-Fi module; The analysis module is used to compare the real-time collected position information with the guidance instructions of the corresponding smart column lamp to determine whether the tester and the test equipment are traveling according to the expected simulation route, and calculate the distance deviation and angle deviation between the actual travel route and the expected simulation route; The collection module is used to provide real-time feedback of the intuitive feeling of the smart column lamp guidance through the test equipment, transmit the data to the cloud server for collection, and use Python to draw a line graph or a bar graph based on the collected data.

[0007] The planning module includes a setting unit and an installation unit; The setting unit is used to set a simulated route by providing the current actual site through GIS; The installation unit is used to install a plurality of smart column lights through a set simulated route.

[0008] The acquisition module includes a positioning unit, an auxiliary unit, an edge computing unit and a transmission unit; The positioning unit is used to locate and collect the position information of the tester and the test equipment in real time through GPS; The auxiliary unit is used to assist GPS positioning through the geomagnetic fingerprint module to ensure the accuracy of GPS positioning and collection in bad weather; The edge computing unit is used to pre-process the collected location information through the intelligent gateway, including format conversion, denoising and fusion analysis; The transmission unit is used to transmit the pre-processed location information to the cloud server through the Wi-Fi module.

[0009] The analysis module includes a comparison unit and a calculation unit.

[0010] The calculation unit is used to collect the position information and compare it with the guidance instructions of the smart column lamp to determine whether the tester and the test equipment are traveling according to the expected simulation route. The calculation formula is as follows: ; in, From the starting point to and When the actual route point is two points, the difference between the actual route point and the simulated route point is Indicates the actual route point sequence Points, Indicates the first Points, express and The distance measure between Represents the smallest cumulative distance value selected from the three predecessor states.

[0011] The calculation unit is used to calculate the distance deviation and angle deviation between the actual travel route and the expected simulated route. The distance deviation calculation formula is: ; Where d represents the distance deviation from the actual route point to the corresponding smart column light in the simulated route point. and represents the horizontal and vertical coordinates of the actual route points, and Represents the horizontal and vertical coordinates of the corresponding smart column lights in the simulated route points.

[0012] The angle deviation calculation formula is: ; in, Represents the angle deviation value, Represents the actual moving direction vector, represents the preset direction vector, Represents the dot product of the actual moving direction vector and the preset direction vector, Represents the length of the actual moving direction vector, Represents the preset direction vector.

[0013] The collection module includes a collection unit and a summary unit.

[0014] The collection unit is used to use the tester to use the test device to feedback the intuitive feeling data of the smart column light in real time and transmit it to the cloud server through the Wi-Fi module. The test device is a smart phone or a smart watch; The summary unit is used to draw a line graph or a bar graph of the collected intuitive feeling data through Python.

[0015] The guide testing method of the smart column lamp based on the Internet of Things includes the following steps: Scenario simulation: set a route in the actual site, simulate the scenarios that people encounter in their daily travel, and set up several smart column lights along the route; Multi-environment testing: The tester and the test equipment simulate travel along the set route in different environments; Data collection: The smart column lamp uses a GPS module and deploys geomagnetic fingerprint positioning to collect real-time location information of the tester and the test equipment on the route. After the location information of the tester and the test equipment is processed by the smart gateway, it is transmitted to the cloud server through the Wi-Fi module.

[0016] Data analysis: By comparing the collected position information with the guidance instructions of the smart column light, it is determined whether the tester or the test equipment is moving along the expected guidance path, and the distance deviation and angle deviation between the actual travel path and the preset guidance path are calculated to evaluate the accuracy of the guidance of the smart column light; Data collection: After the test, let the tester use the application on the test device to provide real-time feedback on the intuitive feeling of the smart column light guidance. Subjective feedback can supplement the deficiency of quantitative data and improve the test from the perspective of user experience. The data will be transmitted to the cloud server for collection, and a line graph or bar graph will be drawn based on the collected data.

[0017] The present invention has the following beneficial effects: 1. In the present invention, a simulated route is set by providing the current actual site, and smart column lights are installed at the landmark points of the simulated route to clarify the guiding range and function of each smart column light, so that subsequent test results can better reflect the guiding performance of the smart column lights in actual applications, avoiding inaccurate test results caused by the large difference between the test scene and the actual use scene, and by repeating the test in different environments, the guiding performance of the smart column lights in various complex situations can be comprehensively evaluated to ensure that they can function stably and reliably in different environments. The acquisition module adopts a positioning method that combines a GPS module and a geomagnetic fingerprint module to improve the accuracy of location information collection, ensuring that the real position of the tester on the simulated route can be obtained, and the collected data is pre-processed by the intelligent gateway and then transmitted to the cloud server through the Wi-Fi module, so as to obtain the latest location information in time and improve the accuracy of the test system.

[0018] 2. In the present invention, in the analysis module, by calculating and comparing the position information collected and received in real time with the guidance instructions of the corresponding smart column lights, it is possible to accurately determine whether the tester and the test equipment are traveling along the expected simulation route, clarify the guiding effect of the guidance instructions of the smart column lights on the actual travel, and at the same time calculate the distance deviation and angle deviation between the actual travel route and the expected simulation route, further understand the degree of deviation between the actual travel path of the tester and the test equipment and the expected simulation route, and make targeted adjustments to the guidance instructions based on the data to optimize the guidance instructions of the smart column lights.

[0019] 3. In the summary unit of the present invention, the tester uses a smart phone or a smart watch to provide real-time feedback on the intuitive feeling data of the smart column light guidance, so as to directly understand whether the smart column light is eye-catching and whether the guidance information is easy to understand during the actual use of the tester. The data will be transmitted to the cloud server through the Wi-Fi module, and a line graph or a bar graph will be drawn for the collected intuitive feeling data through Python, so as to visualize a large amount of complex subjective feedback data and intuitively analyze the trends and patterns in the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a method flow chart of the guide performance testing method and system of the smart column lamp based on the Internet of Things of the present invention; Figure 2 This is a system flow chart of the guide performance testing method and system of the smart column lamp based on the Internet of Things of the present invention; Figure 3 This is a planning module flow chart of the guide testing method and system of the smart column lamp based on the Internet of Things of the present invention; Figure 4 This is a flow chart of the collection module of the guide testing method and system of the smart column lamp based on the Internet of Things of the present invention; Figure 5 This is a flow chart of the analysis module of the guide testing method and system of the smart column lamp based on the Internet of Things of the present invention; Figure 6 This is a flow chart of the collection module of the guide testing method and system of the smart column lamp based on the Internet of Things of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Implementation See also Figure 1-Figure 6 ,The present invention provides a technical solution: a smart column lamp guidance test system based on the Internet of Things, the test system includes a planning module, a collection module, an analysis module and a collection module; The planning module is used to set a simulation route using the current actual site provided by GIS, and to set a number of smart column lights along the simulation route. The tester then uses the test equipment to conduct a directional test along the set simulation route in different environments. The acquisition module is used to locate and collect the location information of the tester and the test equipment on the set simulation route in real time through the GPS module and the geomagnetic fingerprint module, and after processing the collected location information through the edge computing module, transmit it to the cloud server through the Wi-Fi module; The analysis module is used to compare the real-time collected location information with the guidance instructions of the corresponding smart column lights to determine whether the tester and the test equipment are traveling along the expected simulation route, and calculate the distance deviation and angle deviation between the actual route and the expected simulation route; The collection module is used to provide real-time feedback on the intuitive feeling of the smart column lamp guidance through the test equipment, transmit the data to the cloud server for collection, and use Python to draw line graphs or bar graphs based on the collected data.

[0023] The planning module includes a setting unit and an installation unit; The setting unit is used to set a simulated route by providing the current actual site through GIS; The installation unit is used to install a plurality of smart column lights through a set simulated route.

[0024] The acquisition module includes a positioning unit, an auxiliary unit, an edge computing unit and a transmission unit; The positioning unit is used to locate and collect the position information of the tester and the test equipment in real time through GPS; The auxiliary unit is used to assist GPS positioning through the geomagnetic fingerprint module to ensure the accuracy of GPS positioning and collection in bad weather; The edge computing unit is used to pre-process the collected location information through the intelligent gateway, including format conversion, denoising and fusion analysis; The transmission unit is used to transmit the pre-processed location information to the cloud server through the Wi-Fi module.

[0025] The transmission unit is used to transmit the pre-processed location information to the cloud server through the Wi-Fi module.

[0026] By providing the current actual site to set a simulated route, the set simulated route includes different road conditions such as straight roads, curves, and intersections. At the same time, smart column lights are installed at the landmarks of the simulated route to clarify the guiding range and function of each smart column light, so that the subsequent test results can better reflect the guiding performance of the smart column lights in actual applications, avoiding inaccurate test results caused by the large difference between the test scene and the actual use scene. The tester holds the test equipment and walks along the set simulated route. Repeated tests are carried out in daytime, night, rainy days, rush hour, rush hour and other environments. By testing in multiple environments, the guiding performance of the smart column lights in various complex situations can be fully evaluated to ensure that they can function stably and reliably in different environments. The acquisition module adopts a positioning method that combines the GPS module and the geomagnetic fingerprint module. The GPS module can provide the approximate location information of the tester and the test equipment in real time, while the geomagnetic fingerprint module can assist the GPS in bad weather or when the GPS signal is interfered. Precise positioning improves the accuracy of location information collection, ensures that the actual location of the tester on the simulated route can be obtained, and provides a reliable data basis for subsequent analysis. The collected data is converted into a format, denoised, and fused through an intelligent gateway before being transmitted to the cloud server through a Wi-Fi module, reducing the processing load of the cloud server while obtaining the latest location information in a timely manner, thereby improving the accuracy of the test system.

[0027] Implementation II See also Figure 1-Figure 6 ,The present invention provides a technical solution: a smart column lamp guidance test system based on the Internet of Things, the test system includes a planning module, a collection module, an analysis module and a collection module; The planning module is used to set a simulation route using the current actual site provided by GIS, and to set a number of smart column lights along the simulation route. The tester then uses the test equipment to conduct a directional test along the set simulation route in different environments. The acquisition module is used to locate and collect the location information of the tester and the test equipment on the set simulation route in real time through the GPS module and the geomagnetic fingerprint module, and after processing the collected location information through the edge computing module, transmit it to the cloud server through the Wi-Fi module; The analysis module is used to compare the real-time collected location information with the guidance instructions of the corresponding smart column lights to determine whether the tester and the test equipment are traveling along the expected simulation route, and calculate the distance deviation and angle deviation between the actual route and the expected simulation route; The collection module is used to provide real-time feedback on the intuitive feeling of the smart column lamp guidance through the test equipment, transmit the data to the cloud server for collection, and use Python to draw line graphs or bar graphs based on the collected data.

[0028] The analysis module includes a comparison unit and a calculation unit.

[0029] The calculation unit is used to collect the location information and compare it with the guidance instructions of the smart column light to determine whether the tester and the test equipment are traveling along the expected simulation route. The calculation formula is as follows: ; in, From the starting point to and When the actual route point is two points, the difference between the actual route point and the simulated route point is Indicates the actual route point sequence Points, Indicates the first Points, express and The distance measure between Represents the smallest cumulative distance value selected from the three predecessor states.

[0030] The calculation unit is used to calculate the distance deviation and angle deviation between the actual travel route and the expected simulated route. The distance deviation calculation formula is: ; Where d represents the distance deviation from the actual route point to the corresponding smart column light in the simulated route point. and represents the horizontal and vertical coordinates of the actual route points, and Represents the horizontal and vertical coordinates of the corresponding smart column lights in the simulated route points.

[0031] The angle deviation calculation formula is: ; in, Represents the angle deviation value, Represents the actual moving direction vector, represents the preset direction vector, Represents the dot product of the actual moving direction vector and the preset direction vector, Represents the length of the actual moving direction vector, Represents the preset direction vector.

[0032] In the analysis module, by calculating and comparing the real-time collected and received location information with the corresponding smart column light guidance instructions, it is possible to accurately determine whether the tester and the test equipment are traveling along the expected simulation route, clarify the guiding effect of the smart column light guidance instructions on the actual travel, and calculate the distance deviation and angle deviation between the actual travel route and the expected simulation route. The degree of deviation between the actual travel path of the tester and the test equipment and the expected simulation route is further understood. When large deviations frequently occur on certain sections of road or in specific environments, that is, the setting of the smart column light guidance instructions in this section and environment is unreasonable, targeted adjustments are made to the guidance instructions to optimize the guidance instructions of the smart column light.

[0033] Implementation Three See also Figure 1-Figure 6 ,The present invention provides a technical solution: a smart column lamp guidance test system based on the Internet of Things, the test system includes a planning module, a collection module, an analysis module and a collection module; The planning module is used to set a simulation route using the current actual site provided by GIS, and to set a number of smart column lights along the simulation route. The tester then uses the test equipment to conduct a directional test along the set simulation route in different environments. The acquisition module is used to locate and collect the location information of the tester and the test equipment on the set simulation route in real time through the GPS module and the geomagnetic fingerprint module, and after processing the collected location information through the edge computing module, transmit it to the cloud server through the Wi-Fi module; The analysis module is used to compare the real-time collected location information with the guidance instructions of the corresponding smart column lights to determine whether the tester and the test equipment are traveling along the expected simulation route, and calculate the distance deviation and angle deviation between the actual route and the expected simulation route; The collection module is used to provide real-time feedback on the intuitive feeling of the smart column lamp guidance through the test equipment, transmit the data to the cloud server for collection, and use Python to draw line graphs or bar graphs based on the collected data.

[0034] The acquisition module includes a positioning unit, an auxiliary unit, an edge computing unit, and a transmission unit; The positioning unit is used to locate and collect the location information of the tester and the test equipment in real time through GPS; The auxiliary unit is used to assist GPS positioning through the geomagnetic fingerprint module to ensure the accuracy of GPS positioning and collection in bad weather; The edge computing unit is used to pre-process the collected location information through the intelligent gateway, including format conversion, denoising and fusion analysis; The transmission unit is used to transmit the pre-processed location information to the cloud server through the Wi-Fi module.

[0035] The collection module includes a collection unit and a summary unit.

[0036] The collection unit is used to use the test equipment to feedback the intuitive feeling data of the smart column light in real time through the tester and transmit it to the cloud server through the Wi-Fi module. The test equipment is a smart phone or a smart watch; The summary unit is used to draw a line graph or a bar graph of the collected intuitive feeling data through Python.

[0037] In the summary unit, testers use smartphones or smart watches to provide real-time feedback on the intuitive feeling data of the smart column lights. They can directly understand whether the smart column lights are eye-catching and whether the guidance information is easy to understand during actual use. The data will be transmitted to the cloud server through the Wi-Fi module, and the collected intuitive feeling data will be plotted as a line graph or bar graph through Python, so that a large amount of complex subjective feedback data can be visualized and the trends and patterns in the data can be intuitively analyzed.

[0038] In the present invention, the method and system for testing the guidance of smart column lights based on the Internet of Things provide a simulated route set in the current actual site. The set simulated route includes different road conditions such as straight roads, curves, and intersections. At the same time, smart column lights are installed at the landmark points of the simulated route to clarify the guidance range and function of each smart column light, so that subsequent test results can better reflect the guidance performance of the smart column lights in actual applications, avoiding inaccurate test results caused by the large difference between the test scene and the actual use scene. The tester holds the test device and moves along the set simulated route, and repeats the test in daytime, night, rainy days, rush hour, rush hour, etc. By testing in multiple environments, the guidance performance of the smart column lights in various complex situations can be comprehensively evaluated to ensure that they can function stably and reliably in different environments. The acquisition module adopts a positioning method that combines a GPS module and a geomagnetic fingerprint module. The GPS module can provide real-time approximate location information of the tester and the test equipment, while the geomagnetic fingerprint module can assist the GPS in bad weather or when the GPS signal is interfered. Precise positioning improves the accuracy of location information collection, ensures that the actual location of the tester on the simulated route can be obtained, and provides a reliable data basis for subsequent analysis. The collected data is converted into a format, denoised, and fused through the intelligent gateway before being transmitted to the cloud server through the Wi-Fi module, reducing the processing volume of the cloud server while being able to obtain the latest location information in a timely manner, improving the accuracy of the test system. In the analysis module, by calculating and comparing the real-time collected and received location information with the corresponding guidance instructions of the smart column lights, it is possible to accurately determine whether the tester and the test equipment are traveling along the expected simulated route, clarify the guiding effect of the guidance instructions of the smart column lights on the actual travel, and calculate the distance deviation and angle deviation between the actual travel route and the expected simulated route. , further understand the degree of deviation between the actual travel path of the tester and the test equipment and the expected simulation route. When large deviations frequently occur on certain sections of road or in specific environments, that is, the setting of the guidance instructions of the smart column lights on this section of road and in this environment is unreasonable, make targeted adjustments to the guidance instructions and optimize the guidance instructions of the smart column lights. In the summary unit, the tester uses a smart phone or smart watch to provide real-time feedback on the intuitive feeling data of the smart column lights. It can directly understand whether the smart column lights are eye-catching and whether the guidance information is easy to understand during actual use. The data will be transmitted to the cloud server through the Wi-Fi module, and the collected intuitive feeling data will be plotted as a line graph or bar graph through Python, so that a large amount of complex subjective feedback data can be visualized and the trends and patterns in the data can be intuitively analyzed.

[0039] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or apparatus; The guide testing method of the smart column lamp based on the Internet of Things includes the following steps: Scenario simulation: set a route in the actual site, simulate the scenarios that people encounter in their daily travel, and set up several smart column lights along the route; Multi-environment testing: The tester and the test equipment simulate travel along the set route in different environments; Data collection: The smart column lamp uses a GPS module and deploys geomagnetic fingerprint positioning to collect real-time location information of the tester and the test equipment on the route. After the location information of the tester and the test equipment is processed by the smart gateway, it is transmitted to the cloud server through the Wi-Fi module.

[0040] Data analysis: By comparing the collected position information with the guidance instructions of the smart column light, it is determined whether the tester or the test equipment is moving along the expected guidance path, and the distance deviation and angle deviation between the actual travel path and the preset guidance path are calculated to evaluate the accuracy of the guidance of the smart column light; Data collection: After the test, let the tester use the application on the test device to provide real-time feedback on the intuitive feeling of the smart column light guidance. Subjective feedback can supplement the deficiency of quantitative data and improve the test from the perspective of user experience. The data will be transmitted to the cloud server for collection, and a line graph or bar graph will be drawn based on the collected data.

[0041] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. The smart column light guidance test system based on the Internet of Things is characterized by: The test system includes a planning module, an acquisition module, an analysis module and a collection module; The planning module is used to set a simulation route by providing the current actual site through GIS, and set a number of smart column lights along the simulation route. Then the tester uses the test equipment to perform a directional test along the set simulation route in different environments; The acquisition module is used to locate and acquire the location information of the tester and the test equipment on the set simulation route in real time through the GPS module and the geomagnetic fingerprint module, and after processing the acquired location information through the edge computing module, transmit it to the cloud server through the Wi-Fi module; The analysis module is used to compare the real-time collected position information with the guidance instructions of the corresponding smart column lamp to determine whether the tester and the test equipment are traveling according to the expected simulation route, and calculate the distance deviation and angle deviation between the actual travel route and the expected simulation route; The collection module is used to provide real-time feedback of the intuitive feeling of the smart column lamp guidance through the test equipment, transmit the data to the cloud server for collection, and use Python to draw a line graph or a bar graph based on the collected data.

2. According to the IoT-based smart column lamp guidance test system of claim 1, it is characterized in that: The planning module includes a setting unit and an installation unit; The setting unit is used to set a simulated route by providing the current actual site through GIS; The installation unit is used to install a plurality of smart column lights through a set simulated route.

3. The IoT-based smart column lamp guidance test system according to claim 1 is characterized in that: The acquisition module includes a positioning unit, an auxiliary unit, an edge computing unit and a transmission unit; The positioning unit is used to locate and collect the position information of the tester and the test equipment in real time through GPS; The auxiliary unit is used to assist GPS positioning through the geomagnetic fingerprint module to ensure the accuracy of GPS positioning and collection in bad weather; The edge computing unit is used to pre-process the collected location information through the intelligent gateway, including format conversion, denoising and fusion analysis; The transmission unit is used to transmit the pre-processed location information to the cloud server through the Wi-Fi module.

4. The IoT-based smart column lamp guidance test system according to claim 1 is characterized in that: The analysis module includes a comparison unit and a calculation unit.

5. The IoT-based smart column lamp guidance test system according to claim 4 is characterized in that: The calculation unit is used to collect the position information and compare it with the guidance instructions of the smart column lamp to determine whether the tester and the test equipment are traveling according to the expected simulation route. The calculation formula is as follows: ； in, From the starting point to and When the actual route point is two points, the difference between the actual route point and the simulated route point is Indicates the actual route point sequence Points, Indicates the first Points, express and The distance measure between Represents the smallest cumulative distance value selected from the three predecessor states.

6. The IoT-based smart column lamp guidance test system according to claim 4 is characterized in that: The calculation unit is used to calculate the distance deviation and angle deviation between the actual travel route and the expected simulated route. The distance deviation calculation formula is: ； Where d represents the distance deviation from the actual route point to the corresponding smart column light in the simulated route point. and represents the horizontal and vertical coordinates of the actual route points, and Represents the horizontal and vertical coordinates of the corresponding smart column lights in the simulated route points.

7. The IoT-based smart column lamp guidance test system according to claim 6 is characterized in that: The angle deviation calculation formula is: ； in, Represents the angle deviation value, Represents the actual moving direction vector, represents the preset direction vector, Represents the dot product of the actual moving direction vector and the preset direction vector, Represents the length of the actual moving direction vector, Represents the preset direction vector.

8. The IoT-based smart column light guidance test system according to claim 1 is characterized in that: The collection module includes a collection unit and a summary unit.

9. The IoT-based smart column lamp guidance test system according to claim 8, characterized in that: The collection unit is used to use the tester to use the test device to feedback the intuitive feeling data of the smart column light in real time and transmit it to the cloud server through the Wi-Fi module. The test device is a smart phone or a smart watch; The summary unit is used to draw a line graph or a bar graph of the collected intuitive feeling data through Python.

10. The testing method of the smart column lamp guidance testing system based on the Internet of Things according to any one of claims 1 to 9, characterized in that: The following steps are involved: Scenario simulation: set a route in the actual site, simulate the scenarios that people encounter in their daily travel, and set up several smart column lights along the route; Multi-environment testing: The tester and the test equipment simulate travel along the set route in different environments; Data collection: The smart column lamp uses a GPS module and deploys geomagnetic fingerprint positioning to collect real-time location information of the tester and the test equipment on the route. After the location information of the tester and the test equipment is processed by the smart gateway, it is transmitted to the cloud server through the Wi-Fi module; Data analysis: By comparing the collected position information with the guidance instructions of the smart column light, it is determined whether the tester or the test equipment is moving along the expected guidance path, and the distance deviation and angle deviation between the actual travel path and the preset guidance path are calculated to evaluate the accuracy of the guidance of the smart column light; Data collection: After the test, let the tester use the application on the test device to provide real-time feedback on the intuitive feeling of the smart column light guidance. Subjective feedback can supplement the deficiency of quantitative data and improve the test from the perspective of user experience. The data will be transmitted to the cloud server for collection, and a line graph or bar graph will be drawn based on the collected data.

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