CN113076999A - Artificial intelligence based information data acquisition method - Google Patents
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Abstract
The invention discloses an artificial intelligence based information data acquisition method, which belongs to the technical field of artificial intelligence data acquisition, and comprises the following specific steps: (1) collecting road information; (2) collecting past information; (3) receiving and analyzing big data; (4) judging and classifying information; (5) collecting real-time data; (6) analyzing and judging real-time data; (7) displaying and alarming the judgment result; (8) storing the judgment result; in the step (1), the artificial intelligence device constructs a global image of a monitored road through a web crawler, an on-line map and received satellite remote sensing image data, and generates image data through map layer superposition and data processing; the invention ensures that the artificial intelligence can not generate judgment errors even if the service time is too long, effectively improves the working quality of traffic managers, does not need the traffic managers to analyze the violation causes by themselves, and improves the problem processing speed of the traffic managers.
Description
Technical Field
The invention relates to the technical field of artificial intelligence data acquisition, in particular to an artificial intelligence information-based data acquisition method.
Background
Through retrieval, the Chinese patent No. CN107463640A discloses an artificial intelligence based information data acquisition method, which avoids repeated information acquisition and ensures the accuracy of data, but has a single judgment method. Artificial intelligence is a new technology science for researching and developing theories, methods, technologies and application systems for simulating, extending and expanding human intelligence, is a branch of computer science, and attempts to understand the essence of intelligence and produces a new intelligent machine which can respond in a manner similar to human intelligence, the research in the field includes robots, language recognition, image recognition, natural language processing, expert systems and the like, the theories and technologies are increasingly mature from birth, the application field is also continuously expanded, it can be assumed that scientific and technological products brought by the artificial intelligence in the future will be 'containers' of human intelligence, the artificial intelligence can simulate the information process of human consciousness and thinking, the artificial intelligence is not human intelligence but can think like a human being, and can exceed the human intelligence, with the progress of science and technology and the development of industry, the traffic volume in cities is increased rapidly, and the original traffic mode can not meet the requirements; meanwhile, as various vehicles are provided for urban traffic in industrial development, the development of urban traffic industry is accelerated, the occurrence frequency of traffic accidents is increased, and in order to reduce the occurrence rate of traffic accidents, many traffic management departments begin to monitor traffic by using artificial intelligence equipment, so that the invention of the artificial intelligence-based information data acquisition method becomes more important.
Firstly, the existing artificial intelligence based information data acquisition method cannot feed back accurate violation behaviors to relevant traffic managers in time, needs the traffic managers to analyze the violation behaviors and reduce the problem processing speed, and secondly, the existing artificial intelligence based information data acquisition method cannot update real-time data, has single artificial intelligence judgment standard, is easy to generate judgment errors due to overlong service time and influences the working quality of the traffic managers.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides an artificial intelligence based information data acquisition method.
In order to achieve the purpose, the invention adopts the following technical scheme:
the information data acquisition method based on artificial intelligence comprises the following specific steps:
(1) collecting road information: collecting and processing the global image of the monitored road by the artificial intelligence equipment to generate image data;
(2) past information collection: receiving image data, collecting traffic information of the road and processing the traffic information to generate original data;
(3) big data receiving and analyzing: receiving traffic big data, processing the traffic big data to generate comparison data, and performing classification marking;
(4) and (3) information judgment and classification: comparing the original data with the comparison data, analyzing and generating judgment data, and carrying out classification marking;
(5) acquiring real-time data: receiving real-time data sent by monitoring equipment and processing the real-time data to generate analysis data;
(6) analyzing and judging real-time data: comparing the analysis data with the judgment data to generate result data and carrying out classification marking;
(7) judging result display and alarming: displaying the result data and analyzing the result data to judge whether an alarm needs to be sent;
(8) and (4) storing a judgment result: and processing the result data to generate and store the storage data.
Further, in the step (1), the artificial intelligence device constructs a global image of the monitored road through a web crawler, an on-line map and received satellite remote sensing image data, and generates image data through map layer superposition and data processing, wherein the artificial intelligence device is one of a robot or a voice assistant.
Further, after the image data is received in the step (2), the image data is analyzed, the traffic information of the road to be monitored corresponding to the image data is called from the database and processed to generate original data.
Further, the traffic big data in the step (3) is extracted from the cloud server and the traffic official website to generate comparison data and is classified and marked, and the specific classification and marking process is as follows:
the method comprises the following steps: integrating data extracted from a cloud server and a traffic official network to generate behavior data;
step two: the behavior data violating the traffic rules is marked as A, and the behavior data not violating the traffic rules is marked as B.
Further, after the raw data, a and B are completely collected in step (4), comparison and correction are performed to generate judgment data, and the specific steps of comparison and analysis are as follows:
i, comparing the original data with A one by one, integrating the same data and marking as X;
and II, comparing the original data with the B, and integrating the same data and marking as Y.
Further, in the step (5), the monitoring device starts to monitor the monitored road in real time and extracts the monitored image through image features to generate analysis data, and the monitoring device is one of a camera, an ultrasonic detector or a velocimeter.
Further, after the analysis data in step (6) are collected by the monitoring device, the collected analysis data are respectively compared and classified with X, Y to generate result data, and the specific comparison and classification criteria are as follows:
s1: comparing the analysis data monitored by the monitoring equipment in real time with the X data one by one and marking the same data as F;
s2: and comparing the analysis data monitored by the monitoring equipment in real time with Y one by one, and marking the same data as T.
Further, in the step (7), the F and T are displayed after being converted according to the definition of the data dictionary, and the received F and T are classified and judged, and the specific classification and judgment steps are as follows:
SS 1: if the received result data is F, starting to send out an alarm, carrying out conversion processing on the F according to the definition of the data dictionary, then displaying the F, and indicating the problem through voice broadcasting;
SS 2: if the received result data is T, alarming and voice broadcasting are not needed, and the data are normally displayed.
Further, the F and the T in the step (8) are simultaneously sent to a cloud server, processed and generated to store data in an encoded form in the cloud server.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the artificial intelligence based information data acquisition method, the passing traffic information of a road to be monitored is collected in a cloud service and processed to generate original data, traffic big data are extracted from a cloud server and a traffic official network and processed to generate comparison data and are classified and marked, behavior data violating a traffic rule are marked as A, behavior data not violating the traffic rule are marked as B, the original data and A, B are compared and corrected to generate judgment data, the judgment accuracy of artificial intelligence is continuously improved by training and optimizing an artificial intelligence data model by using the judgment data, the judgment error is not generated even if the artificial intelligence is used for a long time, and the working quality of traffic managers is effectively improved;
2. the method for collecting the information data based on the artificial intelligence starts to monitor a monitored road in real time through monitoring equipment, a monitoring picture is extracted through image features to generate analysis data, the analysis data are respectively compared with X, Y to generate result data, the data are marked as F when the analysis data are the same as X, the data are marked as T when the analysis data are the same as X, accurate violation behaviors are fed back to relevant traffic managers in time, if the received result data are F, an alarm is sent out, F is converted according to the definition of a data dictionary and then displayed, problems are pointed out through voice broadcasting, if the received result data are T, the alarm and voice broadcasting are not needed, the data are displayed normally, the traffic managers do not need to analyze violation reasons, and the problem processing speed of the traffic managers is improved.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
Fig. 1 is a flow chart of an artificial intelligence based information data acquisition method according to the present invention.
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.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
Referring to fig. 1, the information data acquisition method based on artificial intelligence includes the following specific steps:
(1) collecting road information: collecting and processing the global image of the monitored road by artificial intelligence to generate image data;
(2) past information collection: receiving image data, collecting traffic information of the road and processing the traffic information to generate original data;
(3) big data receiving and analyzing: receiving traffic big data, processing the traffic big data to generate comparison data, and performing classification marking;
(4) and (3) information judgment and classification: comparing the original data with the comparison data, analyzing and generating judgment data, and carrying out classification marking;
(5) acquiring real-time data: receiving real-time data sent by monitoring equipment and processing the real-time data to generate analysis data;
(6) analyzing and judging real-time data: comparing the analysis data with the judgment data to generate result data and carrying out classification marking;
(7) judging result display and alarming: displaying the result data and analyzing the result data to judge whether an alarm needs to be sent;
(8) and (4) storing a judgment result: and processing the result data to generate and store the storage data.
In the step (1), the artificial intelligence device constructs a global image of the monitored road through a network crawler, an on-line map and received satellite remote sensing image data, and generates image data through map layer superposition and data processing, wherein the artificial intelligence device is one of a robot or a voice assistant.
And (3) after the image data is received in the step (2), starting to analyze the image data, calling the traffic information of the road to be monitored corresponding to the image data from the database, and processing the traffic information to generate original data.
In the step (3), the traffic big data is extracted from the cloud server and the traffic official network to generate comparison data and is classified and marked, and the specific classification and marking process is as follows:
the method comprises the following steps: integrating data extracted from a cloud server and a traffic official network to generate behavior data;
step two: the behavior data violating the traffic rules is marked as A, and the behavior data not violating the traffic rules is marked as B.
After the raw data, A and B are completely collected in the step (4), comparison and correction are carried out to generate judgment data, and the specific steps of comparison and analysis are as follows:
i, comparing the original data with A one by one, integrating the same data and marking as X;
and II, comparing the original data with the B, and integrating the same data and marking as Y.
And (5) the monitoring equipment starts to monitor the monitored road in real time and extracts the monitored picture through image features to generate analysis data, wherein the monitoring equipment is one of a camera, an ultrasonic detector or a velocimeter.
After the analysis data in the step (6) are collected by the monitoring equipment, comparing and classifying the collected analysis data with X, Y respectively to generate result data, wherein the specific comparison and classification standard is as follows:
s1: comparing the analysis data monitored by the monitoring equipment in real time with the X data one by one and marking the same data as F;
s2: and comparing the analysis data monitored by the monitoring equipment in real time with Y one by one, and marking the same data as T.
And (7) after the F and the T are converted according to the definition of the data dictionary, displaying the F and the T, and classifying and judging the received F and the received T, wherein the specific classification and judgment steps are as follows:
SS 1: if the received result data is F, starting to send out an alarm, carrying out conversion processing on the F according to the definition of the data dictionary, then displaying the F, and indicating the problem through voice broadcasting;
SS 2: if the received result data is T, alarming and voice broadcasting are not needed, and the data are normally displayed.
And (4) in the step (8), the F and the T are simultaneously sent to a cloud server, processed, generated and encoded and stored in the cloud server.
The working principle and the using process of the invention are as follows: the method for collecting information data based on artificial intelligence comprises the steps that an artificial intelligence device constructs a global image of a monitored road through a web crawler, an on-line map and received satellite remote sensing image data, the global image is superposed with the map layer and processed to generate image data, after the image data are received, the image data are analyzed, past traffic information of the road to be monitored corresponding to the image data is taken out from a database and processed to generate original data, traffic big data are extracted from a cloud server and a traffic official network and processed to generate comparison data and carry out classification marking, and the specific classification marking process is as follows: firstly, integrating data extracted from a cloud server and a traffic official network to generate behavior data, then marking the behavior data violating the traffic rules as A, marking the behavior data not violating the traffic rules as B, starting to collect original data, A and B after classification marking is finished, starting to compare and correct the original data, A and B after the original data, A and B are completely collected, and generating judgment data, wherein the comparison and analysis specifically comprises the following steps: i, comparing the original data with A one by one, integrating the same data and marking as X;
II, comparing the original data with the original data B, integrating the same data and marking the data as Y, starting to monitor the monitored road in real time by monitoring equipment, extracting the monitored image through image features to generate analysis data, comparing the collected analysis data with X, Y respectively and classifying the analysis data to generate result data, wherein the specific comparison classification standard is as follows: s1: comparing the analysis data monitored by the monitoring equipment in real time with the X data one by one and marking the same data as F;
s2: comparing the analysis data monitored by the monitoring equipment in real time with Y one by one, marking the same data as T, carrying out conversion processing on F and T according to the definition of a data dictionary, displaying the F and T, and carrying out classification judgment on the received F and T, wherein the specific classification judgment steps are as follows: SS 1: if the received result data is F, starting to send out an alarm, carrying out conversion processing on the F according to the definition of the data dictionary, then displaying the F, and indicating the problem through voice broadcasting; SS 2: if the received result data is T, alarming and voice broadcasting are not needed, the data are normally displayed, and after the F and T result display is completed, the F and T are simultaneously sent to the cloud server and processed to generate a coding form to be stored in the cloud server.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (9)
1. The information data acquisition method based on artificial intelligence is characterized by comprising the following specific steps of:
(1) collecting road information: collecting and processing the global image of the monitored road by artificial intelligence to generate image data;
(2) past information collection: receiving image data, collecting traffic information of the road and processing the traffic information to generate original data;
(3) big data receiving and analyzing: receiving traffic big data, processing the traffic big data to generate comparison data, and performing classification marking;
(4) and (3) information judgment and classification: comparing the original data with the comparison data, analyzing and generating judgment data, and carrying out classification marking;
(5) acquiring real-time data: receiving real-time data sent by monitoring equipment and processing the real-time data to generate analysis data;
(6) analyzing and judging real-time data: comparing the analysis data with the judgment data to generate result data and carrying out classification marking;
(7) judging result display and alarming: displaying the result data and analyzing the result data to judge whether an alarm needs to be sent;
(8) and (4) storing a judgment result: and processing the result data to generate and store the storage data.
2. The method for collecting information data based on artificial intelligence according to claim 1, wherein in step (1), the artificial intelligence device constructs a global image of the monitored road by using a web crawler, collecting an online map and receiving satellite remote sensing image data, and generates image data by using map layer superposition and data processing, and the artificial intelligence device is one of a robot and a voice assistant.
3. The artificial intelligence based information data acquisition method of claim 1, wherein after the image data is received in the step (2), the image data is analyzed, and traffic information of a road to be monitored corresponding to the image data is retrieved from a database and processed to generate original data.
4. The artificial intelligence based information data acquisition method of claim 1, wherein the traffic big data in the step (3) is extracted from a cloud server and a traffic official network to generate comparison data and is classified and labeled, and the specific classification and labeling process is as follows:
the method comprises the following steps: integrating data extracted from a cloud server and a traffic official network to generate behavior data;
step two: the behavior data violating the traffic rules is marked as A, and the behavior data not violating the traffic rules is marked as B.
5. The artificial intelligence based information data acquisition method according to claim 1, wherein after the raw data, a and B are completely collected in step (4), comparison and correction are performed to generate judgment data, and the specific steps of comparison and analysis are as follows:
i, comparing the original data with A one by one, integrating the same data and marking as X;
and II, comparing the original data with the B, and integrating the same data and marking as Y.
6. The artificial intelligence based information data acquisition method of claim 4, wherein in the step (5), the monitoring device starts to monitor the monitored road in real time and generates the analysis data by image feature extraction of the monitored image, and the monitoring device is one of a camera, an ultrasonic detector or a velocimeter.
7. The artificial intelligence based information data collection method of claim 1, wherein after the analysis data in step (6) is collected by the monitoring device, the collected analysis data is respectively compared with X, Y for classification and result data is generated, and the specific comparison classification criteria are as follows:
s1: comparing the analysis data monitored by the monitoring equipment in real time with the X data one by one and marking the same data as F;
s2: and comparing the analysis data monitored by the monitoring equipment in real time with Y one by one, and marking the same data as T.
8. The artificial intelligence based information data acquisition method according to claim 1, wherein F and T in step (7) are displayed after being converted according to the definition of the data dictionary, and received F and T are classified and judged, and the specific classification and judgment steps are as follows:
SS 1: if the received result data is F, starting to send out an alarm, carrying out conversion processing on the F according to the definition of the data dictionary, then displaying the F, and indicating the problem through voice broadcasting;
SS 2: if the received result data is T, alarming and voice broadcasting are not needed, and the data are normally displayed.
9. The artificial intelligence based information data acquisition method according to claim 1, wherein in the step (8), the F and the T are simultaneously sent to a cloud server and processed to generate a code form to be stored in the cloud server.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114758490A (en) * | 2021-09-30 | 2022-07-15 | 广东可信新能源股份有限公司 | Artificial intelligence data acquisition method and device |
| CN117009938A (en) * | 2023-08-16 | 2023-11-07 | 济南正大科技发展有限公司 | Computer network security analysis system and method based on big data |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106960577A (en) * | 2017-04-21 | 2017-07-18 | 安徽文康科技有限公司 | Check the control method for system of deploying to ensure effective monitoring and control of illegal activities |
| CN108961790A (en) * | 2018-07-24 | 2018-12-07 | 河北德冠隆电子科技有限公司 | Bad weather pre-warning management system and method based on four-dimensional outdoor scene traffic simulation |
| CN109191833A (en) * | 2018-08-29 | 2019-01-11 | 深圳市赛为智能股份有限公司 | A kind of intelligent transportation system and its management method |
| CA3016825A1 (en) * | 2017-09-15 | 2019-03-15 | Sergio Machado Goncalves | Predictive, integrated and intelligent system for control of times in traffic lights |
| CN110059631A (en) * | 2019-04-19 | 2019-07-26 | 中铁第一勘察设计院集团有限公司 | The contactless monitoring defect identification method of contact net |
| CN110378824A (en) * | 2019-06-26 | 2019-10-25 | 公安部交通管理科学研究所 | A kind of public security traffic control data brain and construction method |
| CN111275980A (en) * | 2020-01-21 | 2020-06-12 | 上海天齐智能建筑股份有限公司 | Big data application platform based on Internet + intelligent traffic video monitoring management system |
| KR102150034B1 (en) * | 2019-12-13 | 2020-08-31 | 제주특별자치도 | SAFE DRIVING SUPPORT SYSTEM BASED ON MOBILE IoT AGENT AND METHOD FOR PROCESSING THEREOF |
| CN111754786A (en) * | 2020-07-15 | 2020-10-09 | 遵义同望智能科技有限公司 | System for identifying traffic vehicle passing events on highway |
-
2021
- 2021-04-06 CN CN202110368295.8A patent/CN113076999B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106960577A (en) * | 2017-04-21 | 2017-07-18 | 安徽文康科技有限公司 | Check the control method for system of deploying to ensure effective monitoring and control of illegal activities |
| CA3016825A1 (en) * | 2017-09-15 | 2019-03-15 | Sergio Machado Goncalves | Predictive, integrated and intelligent system for control of times in traffic lights |
| CN108961790A (en) * | 2018-07-24 | 2018-12-07 | 河北德冠隆电子科技有限公司 | Bad weather pre-warning management system and method based on four-dimensional outdoor scene traffic simulation |
| CN109191833A (en) * | 2018-08-29 | 2019-01-11 | 深圳市赛为智能股份有限公司 | A kind of intelligent transportation system and its management method |
| CN110059631A (en) * | 2019-04-19 | 2019-07-26 | 中铁第一勘察设计院集团有限公司 | The contactless monitoring defect identification method of contact net |
| CN110378824A (en) * | 2019-06-26 | 2019-10-25 | 公安部交通管理科学研究所 | A kind of public security traffic control data brain and construction method |
| KR102150034B1 (en) * | 2019-12-13 | 2020-08-31 | 제주특별자치도 | SAFE DRIVING SUPPORT SYSTEM BASED ON MOBILE IoT AGENT AND METHOD FOR PROCESSING THEREOF |
| CN111275980A (en) * | 2020-01-21 | 2020-06-12 | 上海天齐智能建筑股份有限公司 | Big data application platform based on Internet + intelligent traffic video monitoring management system |
| CN111754786A (en) * | 2020-07-15 | 2020-10-09 | 遵义同望智能科技有限公司 | System for identifying traffic vehicle passing events on highway |
Non-Patent Citations (2)
| Title |
|---|
| SHIVA ASADIANFAM等: "TVD-MRDL: traffic violation detection system using MapReduce-based deep learning for large-scale data", 《MULTIMEDIA TOOLS AND APPLICATIONS》, vol. 80, pages 2489 - 2516, XP037335962, DOI: 10.1007/s11042-020-09714-8 * |
| 薛大暄等: "基于数据挖掘的交通监控信息融合技术研究", 《现代电子技术》, vol. 43, no. 13, pages 88 - 91 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114758490A (en) * | 2021-09-30 | 2022-07-15 | 广东可信新能源股份有限公司 | Artificial intelligence data acquisition method and device |
| CN117009938A (en) * | 2023-08-16 | 2023-11-07 | 济南正大科技发展有限公司 | Computer network security analysis system and method based on big data |
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