WO2022052341A1

WO2022052341A1 - Intelligent early warning method, related apparatus, and computer storage medium

Info

Publication number: WO2022052341A1
Application number: PCT/CN2020/134720
Authority: WO
Inventors: 段永远
Original assignee: 宇龙计算机通信科技(深圳)有限公司
Priority date: 2020-09-11
Filing date: 2020-12-09
Publication date: 2022-03-17
Also published as: CN112201004A

Abstract

Disclosed are an intelligent early warning method, a related apparatus and a computer storage medium. The method comprises: sending location information to an Internet of Things (IoT) server, said location information being used for enabling the IoT server to obtain traffic information reported by an IoT device in a preset range, and for determining the traffic situation around a wearable device according to the traffic information; receiving from the IoT server the traffic situation around the wearable device; when the traffic situation around the wearable device satisfies a preset condition, generating early warning prompt information. The present application combines the Internet of Things with a wearable device, using the traffic situation around the wearable device for generating early warning prompt information to alert the user, thereby effectively ensuring personal safety.

Description

Intelligent early warning method, related device and computer storage medium

technical field

The present application relates to the technical field of electronic equipment, and in particular, to an intelligent early warning method, a related device, and a computer storage medium.

Background technique

Existing smart glasses generally complete functions such as adding schedules, map navigation, interacting with friends, taking photos and videos, and making video calls with friends through voice or motion control. Smart glasses refer to wearable glasses devices that have an independent operating system like a smart phone and can realize various functions through software installation. With the development of smart glasses technology, users will be like walking and playing with mobile phones in their daily life. They browse pictures, videos, etc. through smart glasses while walking. Safety hazards, not conducive to personal safety.

SUMMARY OF THE INVENTION

The embodiments of the present application provide an intelligent early warning method, related equipment, and computer storage medium, which apply the Internet of Things to wearable devices, improve personal safety functions for wearable devices, effectively reduce the occurrence of traffic accidents, and protect the personal safety of users. Safety.

In order to solve the above technical problems, this application includes the following technical solutions:

In a first aspect, the embodiment of the present application provides an intelligent early warning method, the method includes:

Send location information to an Internet of Things (The Internet of Things, IOT) server; the location information is used to enable the IOT server to obtain traffic information reported by IOT devices within a preset range, and to determine the available traffic information according to the traffic information. The traffic situation in which the wearable device is located;

receiving the traffic condition of the wearable device sent by the IOT server;

When the traffic condition in which the wearable device is located satisfies the preset condition, early warning prompt information is generated.

In a second aspect, the embodiment of the present application provides another method for intelligent early warning, the method includes:

Receive location information sent by wearable devices;

Receive traffic information reported by IoT devices within a preset range according to the location information;

Determine the traffic condition in which the wearable device is located according to the traffic information of the IOT device;

The traffic condition is sent to the wearable device, so that the wearable device generates early warning prompt information when the traffic condition in which the wearable device is located satisfies a preset condition.

In a third aspect, an embodiment of the present application provides a wearable device, the device comprising:

A sending module, configured to send location information to an IoT server; the location information is used to enable the IOT server to obtain traffic information reported by IOT devices within a preset range, and to determine the wearable device according to the traffic information traffic conditions;

a receiving module, configured to receive the traffic condition of the wearable device sent by the IOT server;

A generating module is configured to generate early warning prompt information when the traffic condition in which the wearable device is located satisfies a preset condition.

In a fourth aspect, an embodiment of the present application provides an Internet of Things IOT server, where the server includes:

a first receiving module, configured to receive the location information sent by the wearable device;

a second receiving module, configured to receive, according to the location information, the traffic information reported by the Internet of Things IOT devices within a preset range;

an information determination module, configured to determine the traffic condition in which the wearable device is located according to the traffic information of the IOT device;

A sending module, configured to send the traffic condition to the wearable device, so that the wearable device generates early warning prompt information when the traffic condition in which the wearable device is located satisfies a preset condition.

In a fifth aspect, an embodiment of the present application provides another apparatus for a wearable device, and the apparatus includes a processor, a memory, and a communication interface:

the processor is connected to the memory and the communication interface;

the memory for storing executable program codes;

The processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the method according to the above-mentioned first aspect.

In a sixth aspect, an embodiment of the present application provides another device for an IoT server, the device includes a processor, a memory, and a communication interface:

the processor is connected to the memory and the communication interface;

the memory for storing executable program codes;

The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the intelligent early warning method according to the second aspect above.

In a seventh aspect, an embodiment of the present application provides a computer storage medium on which a computer program is stored, characterized in that, when the program is executed by a processor, the intelligent early warning methods of the first and second aspects above are implemented.

This application combines the Internet of Things with wearable devices. Through the comprehensive analysis of artificial intelligence of the central server of the Internet of Things, when the preset conditions are met, the early warning information of the traffic conditions around the wearable device is generated and fed back to the device in time. The device makes corresponding decisions in a timely manner according to the obtained early warning information, and sends out prompt information. The user takes safety actions according to the prompt information, which further ensures personal safety.

Description of drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only These are some embodiments of the present application. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without any creative effort.

1 is a schematic structural diagram of an intelligent early warning system provided by an embodiment of the present application;

2 is a schematic flowchart of an intelligent early warning method provided by an embodiment of the present application;

3 is an early warning diagram of a wearable device provided by an embodiment of the present application;

4 is a schematic flowchart of another intelligent early warning method provided by an embodiment of the present application;

FIG. 5 is a schematic structural diagram of a wearable device provided by an embodiment of the present application;

6 is a schematic structural diagram of an IOT server provided by an embodiment of the present application;

FIG. 7 is another schematic structural diagram of a wearable device provided by an embodiment of the present application;

FIG. 8 is another schematic structural diagram of an IOT server provided by an embodiment of the present application.

detailed description

In order to make the above objects, features and advantages of the present application more clearly understood, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

The terms "first", "second", "third" and the like in the description and claims of the present application and the above drawings are used to distinguish different objects, rather than to describe a specific order. Furthermore, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes unlisted steps or units, or optionally also includes For other steps or units inherent to these processes, methods, products or devices.

Please refer to FIG. 1 , which is a schematic structural diagram of an intelligent early warning system provided by an embodiment of the present application. The structure of the intelligent early warning system may include a first terminal cluster, an Internet of Things (The Internet of Things, IOT) server 20 and a second terminal cluster.

The first terminal cluster may be a wearable device, and specifically includes one or more wearable devices, wherein the multiple wearable devices may include a wearable device 10a, a wearable device 10b, and the like. The wearable devices in the first terminal cluster can be used by users to watch pictures, videos, listen to songs, listen to voices, and other functions. The wearable devices may specifically be smart glasses, smart watches, smart bracelets, and the like. Any wearable device in the first terminal cluster can establish a data relationship with the network, and establish a data connection relationship with the IOT server 20 through the network, for example, the wearable device reports location information to the IOT server. The first terminal cluster may be, but not limited to, devices such as smart glasses, smart watches, and smart bracelets that can watch pictures and videos.

The second terminal cluster may be an IOT device, specifically including one or more IOT devices, wherein the multiple IOT devices may include an IOT device 30a, an IOT device 30b . . . and the like. The IOT device in the second terminal cluster may be used for functions such as reporting traffic information to the IOT server in real time. Among them, the IOT devices can be smart street lights, smart traffic lights, and smart cameras. Any IOT device in the second terminal cluster can establish a data relationship with the network, and establish a data connection relationship with the IOT server 20 through the network, for example, the IOT device reports traffic information to the IOT server. Among them, the second terminal cluster may be, but not limited to, smart street lights, smart traffic lights, and smart cameras that can report traffic information in real time.

The network can be a medium that provides a communication link between any wearable device in the first terminal cluster and the IOT server 20 or between any IOT device in the second terminal cluster and the IOT server 20, or it can be a medium including network devices and IOT servers 20. The transmission medium of the Internet is not limited to this. The fifth generation mobile communication technology (5th generation mobile networks, 5G) used in this application is the latest generation of cellular mobile communication technology. (3th generation mobile networks, 3G) and the extension after the second generation mobile communication technology (2-Generation wireless telephone technology, 2G) system. The performance goals of 5G are high data rates, reduced latency, energy savings, lower costs, increased system capacity, and massive device connectivity. 5G has more powerful communication and bandwidth capabilities, which can meet the requirements of high-speed, stable and wide coverage of IoT applications. The transmission medium can be a wired link (such as, but not limited to, coaxial cable, optical fiber, and digital subscriber line (DSL), etc.) or a wireless link (such as, but not limited to, wireless fidelity (WIFI), Bluetooth and mobile device networks, etc.).

The IOT server can be a server that can provide a variety of services. It can receive data such as location information sent by any wearable device in the network or the first terminal cluster, or send traffic conditions to any wearable device in the network or the first terminal cluster. It can also receive data such as traffic information sent by any IOT device in the network or the second terminal cluster, or notify the network or any IOT device in the second terminal cluster to report the traffic information. The IOT server 20 can be, but is not limited to, a hardware server, a virtual server, a cloud server, and the like.

Next, the intelligent early warning method provided by the embodiment of the present application will be introduced with reference to the intelligent early warning system shown in FIG. 1 .

Please refer to FIG. 2. FIG. 2 is a schematic flowchart of an intelligent early warning method in an embodiment of the present application. The method includes:

S201, the wearable device reports location information to the IOT server.

Specifically, after the wearable device is connected to the IOT server, it reports the location information to the IOT server at preset time intervals. The frequency of reporting the location information is, for example, but not limited to, once per second. If the time interval for reporting location information is too long (that is, the frequency of reporting location information is too low), the device will not give early warning in time, which will bring danger to users. If the time interval for reporting location information is too short (that is, the frequency of reporting location information is too high), the battery life of the device will be reduced. The frequency may be set by the user according to their own needs, or may be uniformly set by the manufacturer when the wearable device leaves the factory, which is not limited in this embodiment of the present application.

S202. The IOT server obtains, according to the position information of the wearable device, the traffic information reported by the IOT device within a preset range.

Specifically, after receiving the location information of the wearable device, the IOT server obtains a list of IOT devices within a preset range around the wearable device according to the location information. The preset range may be, but is not limited to, a range within a radius of five meters with the wearable device as the center. After acquiring the list of IOT devices, the IOT server notifies the IOT devices within the preset range to report traffic information at preset time intervals. The preset time interval can be, but is not limited to, once every second.

Exemplarily, during use of a certain smart glasses, the location information is first reported to the IOT server at a frequency of once per second. Based on the location information reported by the smart glasses, the IOT server obtains a list of IOT devices centered on the smart glasses and within a radius of 5 meters, and notifies the IOT devices within this range to report traffic information at intervals of once per second.

Specifically, the above traffic information includes at least one of the following: traffic light information, vehicle speed, vehicle density, and pedestrian density.

Optionally, the above-mentioned traffic information may be traffic light information. The traffic light information may include: color information and time information.

Exemplarily, when the traffic indicator information is reported as the traffic information, the traffic indicator reports the color information and time information of the traffic lights at a certain position within the preset range of the wearable device to the IOT server in real time. For example, the traffic lights at a certain intersection within the preset range indicate three directions: turn left, go straight, and turn right. The indicator lights of the three directions are green, red and red respectively. Among them, the red lights in the direction of going straight and turning right will display a 10-second countdown at 19:10:10 Beijing time. At this time, the traffic light will report the above-mentioned left-turn green light, straight red light, right-turn red light, 10-second countdown displayed at 19:10:10 Beijing time, and the specific location information of the traffic light to the IOT server.

Optionally, the above-mentioned traffic information may be the speed of the vehicle. The running speed of the vehicle is the speed at which the vehicle passes through a certain position at a certain moment.

Exemplarily, when the vehicle speed is reported as the traffic information, the IOT server selects a certain fixed position on a certain road within a preset range, the IOT device is a smart street light, and a speed detection device is installed on the smart street light. During the process, the vehicle overspeeds over the sensing line, resulting in flash photography to detect the speed of the vehicle passing through the location at a certain moment, and report the data to the IOT server.

Optionally, the above traffic information may be vehicle density. The vehicle density is the number of vehicles passing through a certain road section within a preset time period.

Exemplarily, when the vehicle density is reported as the traffic information, the IOT server selects a certain road within a preset range, and the IOT device is an intelligent traffic light. The number of vehicles, the obtained number of vehicles is the vehicle density, and the data is reported to the server as traffic information.

Optionally, the above traffic information may be pedestrian density. The pedestrian density is the number of pedestrians passing through a certain road section within a preset time range.

Exemplarily, when the pedestrian density is reported as the traffic information, the IOT server selects a certain intersection within a preset range, and the IOT device is an intelligent traffic light. Between 10:00 and 11:00 Beijing time, the number of pedestrians passing through in this time period is calculated, and the obtained number of pedestrians is the pedestrian density, and the data is reported to the server as traffic information.

Optionally, the above-mentioned traffic information may be traffic light information and vehicle speed. That is, the color information, time information of a traffic light at a certain position, and the speed of a vehicle passing through the position at a certain time are reported to the IOT server as traffic information.

Exemplarily, if the IOT device at a certain intersection within the preset range is a smart traffic light. The intelligent traffic light indicates three directions: turn left, go straight, and turn right. The colors of the indicator lights in the three directions are green, red, and red, respectively. The red lights in the direction of going straight and turning right show a countdown of 10 seconds at 10:00 Beijing time. . At 10:00 Beijing time, the speed detection device detected that the speed of the vehicle passing through this position was 30km/h. The IOT device reports the color information, time information, and vehicle speed of the traffic light at the location at this moment to the IOT server as traffic information.

S203. The IOT server determines the traffic condition in which the wearable device is located according to the traffic information.

Specifically, after acquiring the traffic information from the IOT device, the IOT server analyzes the traffic information to obtain the current traffic condition of the wearable device.

Exemplarily, when a user is walking using smart glasses, the IOT device detects that a car is approaching the user at a speed of 30 km/h at a position 3 meters behind the user. At this time, the IOT device sends the above traffic information to the IOT server, and the IOT server analyzes and obtains the current traffic condition of the wearable device according to the traffic information.

S204. The IOT server sends the traffic condition to the wearable device.

Specifically, the IOT server receives the traffic information sent from the IOT device, obtains the traffic condition where the wearable device is located after analysis, and sends the traffic condition information to the wearable device. For example, but not limited to, the traffic condition is represented by a result code, that is, a result code is generated from the traffic condition information, and the result code is sent to the wearable device. The result code is, for example, but not limited to, a numeric value or a character string.

Exemplarily, when a user is walking using smart glasses, the IOT device detects that a car is approaching the user at a speed of 30 km/h at a position 3 meters behind the user. At this time, the IOT device sends the above traffic information to the IOT server, and the IOT server analyzes and obtains the current traffic condition of the wearable device according to the traffic information. The result code is sent to the wearable device.

S205 , the wearable device generates early warning prompt information when the traffic condition in which it is located satisfies the preset condition.

Specifically, the wearable device receives the traffic condition sent from the IOT server, and if the traffic condition satisfies the preset condition, the wearable device generates early warning prompt information according to the traffic condition, and the early warning prompt information is used to prompt the user that it is currently in an emergency situation . The preset condition may be that there is danger within a radius of 5 meters with the wearable device as the center.

Exemplarily, a user walks to a certain intersection while using the smart glasses. When a bicycle approaches the user at a distance of two meters from the user, and the distance is getting closer, the smart glasses receive a message from the IOT server. The result code, since the current situation meets the preset condition within 5 meters of the distance, at this time, the smart glasses will send out vibration information to inform the user that they are currently in an emergency situation.

Further, the early warning prompt information is used to prompt the user that it is currently in an emergency situation. The warning prompt information can be at least one of the following: vibration prompt information, voice prompt information, text prompt information or animation prompt information.

As shown in FIG. 3 , FIG. 3 exemplarily shows an early warning diagram of a wearable device, where the wearable device is smart glasses. As shown in screen 301, a user is listening to music with smart glasses. When he walks to a certain intersection, when a car approaches the user two meters behind the user, the smart glasses receive the result code from the IOT server. The smart glasses obtain the current emergency situation according to the result code, and a warning screen as shown in 302 will appear at this time, which is used to inform the user that the current emergency situation is to warn the user to pay attention to avoid danger.

Further, if the wearable device is currently playing video or music, in an emergency, the wearable device can pause the video or music playback and issue a prompt message.

Exemplarily, a user is watching a video with smart glasses, and when he walks to a certain intersection, when a car approaches the user two meters behind the user, the smart glasses receive the result code from the IOT server, and the smart glasses According to the result code, the current emergency situation is obtained. At this time, the smart glasses will pause to play the video and display a warning screen to remind the user that the current situation is an emergency and to avoid danger.

Please refer to FIG. 4. FIG. 4 is a schematic flowchart of another intelligent early warning method provided by an embodiment of the present application. The method includes:

S401, the wearable device reports location information to the IOT server.

Specifically, after the wearable device is connected to the IOT server, it reports the location information to the IOT server at preset time intervals. The frequency of reporting location information can be once per second. If the time interval for reporting location information is too long, the experience of the wearable device will be reduced, and if the time is too short, the battery life of the device will be reduced.

S402, the IOT server acquires a list of IOT devices centered on the wearable device and within a radius of 5 meters, and the IOT device sends traffic information to the IOT server.

Specifically, after receiving the location information of the wearable device, the IOT server obtains a list of IOT devices centered on the wearable device and within a radius of 5 meters according to the location information, and all IOT devices that meet this condition report to the IOT server according to the preset time. Report traffic information at intervals. The preset time interval may be once every second.

Optionally, the above traffic information sending method may be: first, the IOT server obtains the IOT devices within a preset range, and then sends an instruction to notify the IOT device to report the traffic information to the IOT devices within the preset range, and finally, receives the instruction. The IOT device reports traffic information to the server.

Optionally, the above-mentioned way of sending the traffic information may also be that the IOT device reports the traffic information to the IOT server all the time. After the IOT server receives the location information of the wearable device, it filters out the traffic information reported by the IOT devices within this range from all the IOT devices according to the location information according to the device identifier.

Exemplarily, during use of a certain smart glasses, the location information is first reported to the IOT server at a frequency of once per second. Based on the location information reported by the smart glasses, the IOT server obtains a list of IOT devices centered on the smart glasses and within a distance of 5 meters, and notifies the IOT devices within this range to report traffic information at a frequency of once per second.

Further, the above traffic information includes at least one of the following: traffic light information, vehicle speed, vehicle density, and pedestrian density.

Optionally, when the IOT server obtains the traffic information reported by the IOT device within a preset range, the traffic information may be traffic light information. For specific examples, please refer to the foregoing embodiments, which will not be repeated here.

Optionally, when the IOT server acquires the traffic information reported by the IOT device within a preset range, the traffic information may be the speed of the vehicle. For specific examples, please refer to the foregoing embodiments, which will not be repeated here.

Optionally, when the IOT server obtains the traffic information reported by the IOT device within a preset range, the traffic information may be vehicle density. For specific examples, please refer to the foregoing embodiments, which will not be repeated here.

Optionally, when the IOT server obtains the traffic information reported by the IOT device within a preset range, the traffic information may be pedestrian density. For specific examples, please refer to the foregoing embodiments, which will not be repeated here.

Optionally, when the IOT server obtains the traffic information reported by the IOT device within a preset range, the traffic information may be traffic light information and vehicle density. For specific examples, please refer to the above-mentioned embodiments, which will not be repeated here.

S403 , the IOT server determines, according to the reported traffic information, that the traffic condition in which the wearable device is located is that a car has struck.

Specifically, after the IOT server obtains the traffic information within a preset range from the IOT device according to the position information of the wearable device, it is obtained through analysis that the traffic condition in which the wearable device is located is that a car hits.

Exemplarily, a user is walking on the road wearing smart glasses, and a car is driving towards the user at a speed of 30km/h directly behind him. The IOT device within 5 meters of the smart glasses sends the above traffic information. To the IOT server, the IOT server analyzes the traffic situation where the smart glasses are located according to the traffic information as being hit by a car.

S404. The IOT server generates a result code according to the above traffic conditions.

Specifically, the IOT server obtains the traffic condition after analyzing the traffic information, and generates a result code for the traffic condition.

Exemplarily, a user is walking on the road wearing smart glasses, and a car is driving towards the user at a speed of 30km/h directly behind him. The IOT device within 5 meters of the smart glasses sends the above traffic information. to the IOT server. According to the traffic information, the IOT server analyzes that the traffic situation where the smart glasses are located is that a car is crashing, and then generates a result code for the traffic situation, such as the number 0, which means that the smart glasses and the user are currently in an emergency situation.

S405, the IOT server sends the result code to the wearable device.

Specifically, after the IOT server generates a result code according to the analyzed traffic conditions, it sends the result code to the wearable device.

Exemplarily, a user is walking on the road wearing smart glasses, and a car is driving towards the user at a speed of 30km/h directly behind him. The IOT device within 5 meters of the smart glasses sends the above traffic information. to the IOT server. According to the traffic information, the IOT server analyzes that the traffic condition of the smart glasses is that a car is hitting, and then generates a result code for the traffic condition, such as the number 0, which means that the smart glasses are currently in an emergency situation. The IOT server sends the result code with the number 0 to the smart glasses.

S406, the wearable device generates animation prompt information.

Specifically, the traffic condition represented by the wearable device analysis result code is an emergency situation, so an animation prompt message is generated to remind the user that the user is currently in an emergency situation and pays attention to avoid danger.

Exemplarily, a user is walking on the road wearing smart glasses, and a car is driving towards the user at a speed of 30km/h directly behind him. The IOT device within 5 meters of the smart glasses sends the above traffic information. to the IOT server. According to the traffic information, the IOT server analyzes that the traffic condition of the smart glasses is that a car is hitting, and then generates a result code for the traffic condition, such as the number 0, which means that the smart glasses are currently in an emergency situation. The IOT server sends the result code with the number 0 to the smart glasses. After analyzing the result code, the smart glasses know that it is in an emergency situation, and then generates animation information to remind the user that the user is currently in an emergency situation, and pay attention to avoid danger.

This application combines the Internet of Things with wearable devices. Through the comprehensive analysis of artificial intelligence of the central server of the Internet of Things, when the preset conditions are met, the early warning information of the traffic conditions around the wearable device is generated and fed back to the device in time. The device makes corresponding decisions in a timely manner according to the obtained early warning information, and sends out prompt information, and the user takes safety actions according to the prompt information, which further guarantees personal safety.

Please refer to FIG. 5 , based on the intelligent early warning method, FIG. 5 is a schematic structural diagram of a wearable device 500 provided in an embodiment of the present application, including:

The sending module 501 is configured to send location information to the IOT server; the location information is used to enable the IOT server to obtain the traffic information reported by the IOT devices within a preset range, and to determine the location of the wearable device according to the traffic information. traffic conditions at the place;

A receiving module 502, configured to receive the traffic condition of the wearable device sent by the IOT server;

The generating module 503 is configured to generate early warning prompt information when the traffic condition in which the wearable device is located satisfies a preset condition.

In some embodiments, receiving module 502 includes:

A unit for receiving traffic condition information, configured to receive the traffic condition in which the wearable device is located and sent by the IOT server;

A receiving result code unit, configured to receive the result code sent by the IOT server.

In some embodiments, the traffic information includes at least one of the following: traffic light information, vehicle speed, vehicle density, and pedestrian density.

Please refer to FIG. 6 , based on the intelligent early warning method, FIG. 6 is a schematic structural diagram of an IOT server 600 provided in an embodiment of the present application, including:

The first receiving module 601 is used for receiving the position information sent by the wearable device;

The second receiving module 602 is configured to acquire, according to the location information, the traffic information reported by the Internet of Things IOT devices within a preset range;

an information determination module 603, configured to determine the traffic condition in which the wearable device is located according to the traffic information;

The sending module 604 is configured to send the traffic condition to the wearable device, so that the wearable device generates warning prompt information when the traffic condition in which the wearable device is located meets a preset condition.

In some embodiments, the information determination module 603 includes:

a traffic condition determining unit, configured to determine the traffic condition in which the wearable device is located according to the traffic information;

A determination result code unit, configured to determine the result code according to the traffic information.

In some embodiments, the sending module 604 includes:

a traffic condition sending unit, configured to send the traffic condition to the wearable device so that the wearable device generates early warning prompt information when the traffic condition in which the wearable device is located satisfies a preset condition;

A result code sending unit, configured to send the result code to the wearable device.

In some embodiments, the IOT devices within the preset range report traffic information at preset time intervals.

It should be noted that when the wearable device and the IOT server provided in the above embodiments execute the intelligent early warning method, only the division of the above functional modules is used as an example for illustration. In practical applications, the above functions can be allocated by different The function module is completed, that is, the internal structure of the device is divided into different function modules, so as to complete all or part of the functions described above. In addition, the wearable device, the IOT server and the intelligent early warning method embodiments provided by the above embodiments belong to the same concept, and the embodiment and implementation process are detailed in the method embodiments, which will not be repeated here.

Please refer to FIG. 7 , which is another schematic structural diagram of a wearable device 700 provided in an embodiment of the present application. The wearable device 700 may at least include: at least one processor 701, such as a CPU, at least one network interface 704, a user interface 703 , memory 705 , at least one communication bus 702 . Among them, the communication bus 702 is used to realize the connection and communication between these components. User interface 703 may include, but is not limited to, a touch screen, keyboard, mouse, joystick, and the like. The network interface 704 may optionally include a standard wired interface, a wireless interface (eg, a WIFI interface, a Bluetooth interface), and a communication connection with the server can be established through the network interface 704 . The memory 702 may be high-speed RAM memory or non-volatile memory, such as at least one disk memory. As shown in FIG. 7 , the memory 705 as a computer storage medium may include an operating system, a network communication module, a user interface module and program instructions.

It should be noted that the network interface 704 may be connected to an acquirer, a transmitter or other communication modules, and other communication modules may include, but are not limited to, a WiFi module, a Bluetooth module, etc. transmitters, transmitters and other communication modules, etc.

The processor 701 may be configured to invoke program instructions stored in the memory 705, and may perform the following steps:

Sending location information to the IOT server; the location information is used to enable the IOT server to obtain traffic information reported by IOT devices within a preset range, and to determine the traffic condition where the wearable device is located according to the traffic information;

receiving the traffic condition of the wearable device sent by the IOT server;

Possibly, the traffic condition in which the wearable device is located is characterized by a result code;

After receiving the traffic condition of the wearable device sent by the IOT server, the processor 701 is further configured to execute:

The result code sent by the IOT server is received.

Possibly, the traffic information includes at least one of the following: traffic light information, vehicle speed, vehicle density, and pedestrian density.

Please refer to FIG. 8 , which is another schematic structural diagram of an IOT server 800 provided in an embodiment of the present application. The IOT server 800 may at least include: at least one processor 801, such as a CPU, at least one network interface 804, a user interface 803, Memory 805, at least one communication bus 802. Among them, the communication bus 802 is used to realize the connection and communication between these components. User interface 803 may include, but is not limited to, a touch screen, keyboard, mouse, joystick, and the like. Optionally, the network interface 804 may include a standard wired interface, a wireless interface (eg, a WIFI interface, a Bluetooth interface), and a communication connection with the server may be established through the network interface 804 . The memory 802 may be high-speed RAM memory or non-volatile memory, such as at least one disk memory. As shown in FIG. 8 , the memory 805 as a computer storage medium may include an operating system, a network communication module, a user interface module and program instructions.

It should be noted that the network interface 804 may be connected to an acquirer, a transmitter, or other communication modules, and other communication modules may include, but are not limited to, a WiFi module, a Bluetooth module, etc. It can be understood that the IOT server in this embodiment of the present application may also include an acquirer , transmitters and other communication modules, etc.

The processor 801 can be used to invoke program instructions stored in the memory 805, and can perform the following steps:

Receive location information sent by wearable devices;

Acquire traffic information reported by IOT devices within a preset range according to the location information;

Determine the traffic condition in which the wearable device is located according to the traffic information;

After the processor 801 determines the traffic condition in which the wearable device is located according to the traffic information, the processor 801 is further configured to execute: determining the result code according to the traffic information;

Possibly, after the processor 801 sends the traffic condition to the wearable device, it is further configured to: send the result code to the wearable device.

Possibly, the IOT devices within the preset range report traffic information at preset time intervals.

Embodiments of the present application also provide a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the computer or processor is run on a computer or a processor, the computer or the processor is made to execute any one of the above methods. or multiple steps. If the above-mentioned components of the wearable device and the IOT server are implemented in the form of software functional units and sold or used as independent products, they may be stored in the computer-readable storage medium.

In the above-mentioned embodiments, it may be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented in software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer may be a general purpose computer, special purpose computer, computer network, or other programmable device. The computer instructions may be stored in or transmitted over a computer-readable storage medium. The computer instructions can be sent from a website site, computer, server, or data center via wired (eg, coaxial cable, optical fiber, Digital Subscriber Line (DSL)) or wireless (eg, infrared, wireless, microwave, etc.) another website site, computer, server or data center for transmission. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that includes an integration of one or more available media. The available media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, Digital Video Disc (DVD), or semiconductor media (eg, solid state disks, SSD) )Wait.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, The processes of the embodiments of the various methods described above may be included. The aforementioned storage medium includes: a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk and other media that can store program codes. The technical features in this embodiment and the implementation can be combined arbitrarily if there is no conflict.

The above-mentioned embodiments are only preferred embodiments of the present application to describe, and do not limit the scope of the present application. Without departing from the design spirit of the present application, those of ordinary skill in the art can make the technical solutions of the present application. Various modifications and improvements should fall within the protection scope determined by the claims of the present application.

Claims

An intelligent early warning method, characterized in that it includes:

Sending location information to an IoT server; the location information is used to enable the IOT server to obtain traffic information reported by IOT devices within a preset range, and to determine the traffic condition of the wearable device according to the traffic information;

receiving the traffic condition of the wearable device sent by the IOT server;

When the traffic condition in which the wearable device is located satisfies the preset condition, early warning prompt information is generated.
The method according to claim 1, wherein the traffic condition in which the wearable device is located is represented by a result code;

The receiving the traffic condition of the wearable device sent by the IOT server includes: receiving the result code sent by the IOT server.
The method according to claim 1, wherein the traffic information includes at least one of the following: traffic light information, vehicle speed, vehicle density, and pedestrian density.
An intelligent early warning method, characterized in that it includes:

Receive location information sent by wearable devices;

Acquire traffic information reported by IoT devices within a preset range according to the location information;

Determine the traffic condition in which the wearable device is located according to the traffic information;

The traffic condition is sent to the wearable device, so that the wearable device generates early warning prompt information when the traffic condition in which the wearable device is located satisfies a preset condition.
The method according to claim 4, wherein the traffic condition in which the wearable device is located is represented by a result code;

The determining of the traffic condition in which the wearable device is located according to the traffic information includes: determining the result code according to the traffic information;

The sending the traffic condition to the wearable device includes: sending the result code to the wearable device.
The method according to claim 4, wherein the IOT devices within the preset range report traffic information at preset time intervals.
The method according to claim 4, wherein the traffic information includes at least one of the following: traffic light information, vehicle speed, vehicle density, and pedestrian density.
A wearable device, characterized in that the device comprises:

A sending module, configured to send location information to an IoT server; the location information is used to enable the IOT server to obtain traffic information reported by IOT devices within a preset range, and to determine the wearable device according to the traffic information traffic conditions;

a receiving module, configured to receive the traffic condition of the wearable device sent by the IOT server;

A generating module is configured to generate early warning prompt information when the traffic condition in which the wearable device is located satisfies a preset condition.
An Internet of Things IOT server, characterized in that the server includes:

a first receiving module, configured to receive the location information sent by the wearable device;

a second receiving module, configured to acquire, according to the location information, the traffic information reported by the Internet of Things IOT devices within a preset range;

an information determination module, configured to determine the traffic condition in which the wearable device is located according to the traffic information;

A sending module, configured to send the traffic condition to the wearable device, so that the wearable device generates early warning prompt information when the traffic condition in which the wearable device is located satisfies a preset condition.
A wearable device, comprising a processor, a memory and a communication interface:

the processor is connected to the memory and the communication interface;

the memory for storing executable program codes;

The processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the method according to any one of claims 1-3.
An Internet of Things IOT server, characterized in that it includes a processor, a memory and a communication interface:

the processor is connected to the memory and the communication interface;

the memory for storing executable program codes;

The processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to execute the method according to any one of claims 4-7.
A computer storage medium, characterized in that the computer storage medium has a plurality of instructions, and the instructions are suitable for being loaded by a processor and performing the method steps of any one of claims 1-7.