CN114139936A - Cloud intelligent early warning and repair reporting system based on exhibition item interactive data - Google Patents
Cloud intelligent early warning and repair reporting system based on exhibition item interactive data Download PDFInfo
- Publication number
- CN114139936A CN114139936A CN202111436186.1A CN202111436186A CN114139936A CN 114139936 A CN114139936 A CN 114139936A CN 202111436186 A CN202111436186 A CN 202111436186A CN 114139936 A CN114139936 A CN 114139936A
- Authority
- CN
- China
- Prior art keywords
- data
- exhibition item
- exhibition
- module
- item
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000002452 interceptive effect Effects 0.000 title claims abstract description 16
- 230000008439 repair process Effects 0.000 title claims abstract description 13
- 230000003993 interaction Effects 0.000 claims abstract description 27
- 238000004891 communication Methods 0.000 claims abstract description 18
- 230000002159 abnormal effect Effects 0.000 claims abstract description 16
- 238000007405 data analysis Methods 0.000 claims description 15
- 238000013500 data storage Methods 0.000 claims description 11
- 230000006698 induction Effects 0.000 claims description 8
- 238000007619 statistical method Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 230000003203 everyday effect Effects 0.000 claims 1
- 230000001747 exhibiting effect Effects 0.000 claims 1
- 238000012423 maintenance Methods 0.000 abstract description 6
- 238000004804 winding Methods 0.000 description 7
- 238000000034 method Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000013479 data entry Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000007667 floating Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 238000005096 rolling process Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Emergency Management (AREA)
- Data Mining & Analysis (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The utility model relates to the technical field of exhibition item early warning and repair, in particular to a cloud intelligent early warning and repair system based on exhibition item interactive data, which comprises: the system comprises an exhibition item, a cloud server and terminal equipment; the exhibition item is used for showing media information in various forms to interact with the tourist, and the exhibition item is in signal connection with the cloud server; the cloud server is used for uniformly storing the interaction information of the tourists, counting and analyzing data at regular time and finding out abnormal data, and is in signal connection with the terminal equipment. The system of the utility model uses the infrared sensing module to report each time of tourist interaction information of the exhibition item to the remote cloud server, the interaction information is uniformly stored by the server, the stored data is regularly counted and analyzed, abnormal data is found out, and the abnormal data is automatically reported to the related responsible person through the existing communication equipment such as mobile phone computers, so that the responsible person can more quickly and accurately master the failure condition of the exhibition item, and the periodical exhibition item maintenance time of the exhibition hall is reduced.
Description
Technical Field
The utility model relates to the technical field of exhibition item early warning and repair, in particular to a cloud intelligent early warning and repair system based on exhibition item interactive data.
Background
With the development of science and technology, exhibition techniques for exhibition in an exhibition hall are diversified, and the exhibition is an emerging social media tool for transferring information, which comprises media displayed in various forms such as virtual book flipping, interactive projection, floating imaging, interaction, multimedia story walls and the like. In order to ensure that the tourists can have the best experience process, the exhibition hall can regularly overhaul and maintain the exhibition items and eliminate the failure of the exhibition item equipment.
In the prior art, for example, Chinese patent numbers are: CN 212224864U, "a science and technology museum exhibition maintenance tool", includes pillar, rolling box and base; the winding box is provided with two, winding box one side is provided with the link, winding box inside is provided with branch, winding box inside is provided with clockwork spring, winding box inside is provided with the protecting band, the winding box is stretched out to protecting band one end, the protecting band is stretched out winding box one end and is provided with the couple, the couple is installed in protecting band one side through fixed buckle, the pillar bottom is provided with vibrations siren, vibrations siren passes through bolt fixed mounting in pillar one side, the pillar bottom is provided with the battery, inside the battery imbeds the pillar, the battery passes through the wire with vibrations siren and is connected. When sightseeing personnel touch or want to cross the protective belt, the strut can vibrate, and the vibration alarm can make a sound to warn, so that the personnel can conveniently carry out emergency treatment.
However, in the prior art, the running states of all the exhibition items need to be manually checked one by one, including the interactive contents of hardware, appearance and software of the exhibition items, so that not only is the maintenance of the exhibition items time-consuming and long, but also a large amount of manpower and material resources are consumed, and the failed exhibition items cannot be timely and effectively found.
Disclosure of Invention
Aiming at the defects in the prior art, the utility model aims to provide a cloud intelligent early warning and repair system based on exhibition item interactive data.
In order to achieve the purpose, the utility model provides the following technical scheme:
the utility model provides a high in clouds intelligence early warning report system of repairment based on exhibition item interactive data, includes:
the system comprises an exhibition item, a cloud server and terminal equipment;
the exhibition item is used for showing media information in various forms to interact with the tourist, and the exhibition item is in signal connection with the cloud server;
the cloud server is used for uniformly storing the interaction information of the tourists, counting and analyzing data at regular time and finding out abnormal data, and is in signal connection with the terminal equipment;
the terminal equipment is used for receiving an abnormal data report from the cloud server.
Further, the cloud server comprises a communication module, a data chart display module, a data storage module and a timing data analysis module;
the communication module is used for receiving and transmitting wireless signals, and the communication model is in signal connection with the terminal equipment;
the data chart module is used for outputting the data recorded in the data storage module in a chart form;
the data storage module is used for storing the data collected from the exhibition item;
the timing data analysis module is used for starting statistical analysis on the stored data at a preset timing moment to obtain a fault exhibition item.
Furthermore, the exhibition item comprises a computer module and an infrared induction module;
the computer module is used for sorting the data acquired by the infrared sensing module, marking a timestamp and sending the timestamp to the cloud server, and is in signal connection with the communication module;
the infrared sensing module is used for recording data signals of approaching and leaving of an object.
Further, the timing data analysis module performs statistical analysis through the stored data, and the step of obtaining the fault development item is as follows:
s1, counting the total interaction time of each exhibition item per day;
s2, calculating the variance of the running time data of the exhibition item in the past 30 days;
s3, calculating the variance of the data added to the single day;
and S4, comparing the variances to obtain a judgment result.
Further, in step S2, the set time length is t1, t2, t3... t30,
average duration calculation
=(t1+t2+t3+...+t30)/30；
Calculate the variance of the overall standard deviation 30 days before:
。
further, in step S3,
average duration calculation
=(t1+t2+t3+...+t31)/31；
The global standard deviation was calculated 31 days before:
。
further, in step S4, based on the data accumulated in the previous stage, when the data is stored in the previous stage
And
when the difference value is larger than a certain check value, the interaction state of the exhibition item is considered to be abnormal, and early warning information can be submitted.
Advantageous effects
Compared with the known public technology, the technical scheme provided by the utility model has the following beneficial effects:
the system of the utility model uses the infrared sensing module to report each time of tourist interaction information of the exhibition item to the remote cloud server, the interaction information is uniformly stored by the server, the stored data is regularly counted and analyzed, abnormal data is found out, and the abnormal data is automatically reported to the related responsible person through the existing communication equipment such as mobile phone computers, so that the responsible person can more quickly and accurately master the failure condition of the exhibition item, and the periodical exhibition item maintenance time of the exhibition hall is reduced.
Drawings
Fig. 1 is a system diagram of a cloud-based intelligent early warning and repair system based on exhibition item interactive data.
Illustration of the drawings:
1. item exhibition; 2. a cloud server; 3. a terminal device; 20. a communication module; 21. a data chart display module; 22. a data storage module; 23. a timing data analysis module; 10. a computer module; 11. and an infrared sensing module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The present invention will be further described with reference to the following examples.
Example 1
Referring to fig. 1, a cloud intelligent early warning and repair system based on exhibition item interactive data includes: the system comprises a display item 1, a cloud server 2 and a terminal device 3;
the exhibition item 1 is used for showing media information in various forms to interact with tourists, and the exhibition item 1 is in signal connection with the cloud server 2;
the exhibition item 1 comprises a computer module 10 and an infrared induction module 11;
the computer module 10 is used for collating the data acquired by the infrared sensing module 11, marking a timestamp and sending the timestamp to the cloud server 2, and the computer module 10 is in signal connection with the communication module 20;
the infrared sensing module 11 is used for recording data signals of approaching and departing of an object.
The cloud server 2 is used for uniformly storing the interaction information of the tourists, counting and analyzing data at regular time and finding out abnormal data, and the cloud server 2 is in signal connection with the terminal equipment 3.
The cloud server 2 comprises a communication module 20, a data chart display module 21, a data storage module 22 and a timing data analysis module 23;
the communication module 20 is used for transceiving wireless signals, and the communication module 20 is in signal connection with the terminal device 3;
the data chart module 21 is used for outputting the data recorded in the data storage module 22 in a chart form;
the data storage module 22 is used for storing the data collected from the exhibition item 1;
the timing data analysis module 23 is configured to start statistical analysis on the stored data at a predetermined timing to obtain a fault exhibition item.
The terminal device 3 is used for receiving an abnormal data report from the cloud server 2.
The timing data analysis module 23 performs statistical analysis through the stored data, and the steps of obtaining the fault development item are as follows:
s1, counting the total interaction time of each exhibition item 1 per day:
all detection states and timestamp data submitted by the exhibition computer are stored in the database exhibition item sensing record table;
table 1 exhibition item induction recording table
| Column name | Description of the utility model |
| id | Record number |
| product_id | Exhibition item number |
| status | Sensing state, starting sensing and losing sensing separately |
| created_at | Time stamp of recording |
Using SQL queries, all state data of the previous day of an exhibition is queried one at a time (dirty data that may be generated by the closed house date is not processed) and sorted in descending order by the commit timestamp.
And traversing all the data entries, and obtaining the time difference obtained by subtracting the timestamp which is close to the last induction starting time from the timestamp which loses the object induction data entry, namely the current interaction time (unit second).
Δ t = t2 (loss of induction timestamp) -t1 (start of induction timestamp of the next entry immediately next) adds all the interaction times, i.e. the total interaction time of the day of the show item. Storing the result into an exhibition item interaction time table;
TABLE 2 show item interaction time table
| Column name | Description of the utility model |
| id | Record number |
| product_id | Exhibition item number |
| Date | Date of recording |
| Action_time | Total time of interaction |
| Is_breakdown | Manually-determined fault condition (for calibration data) |
| Is_holiday | Whether to save holidays |
S2, calculating the variance of the running time data of the past 30 days of the exhibition item 1:
confirming whether the current day is a holiday, and inquiring the exhibition item interaction time table by using SQL to obtain daily interaction time data of 30 days (the holiday attribute is the same as the current day) of a certain exhibition item in perfect and fault-free operation before the current day;
setting the time length to be t1, t2, t3... t30,
average duration calculation
=(t1+t2+t3+...+t30)/30；
Calculate the variance of the overall standard deviation 30 days before:
。
s3, calculating the variance of the data added to the single day:
average duration calculation
=(t1+t2+t3+...+t31)/31；
The global standard deviation was calculated 31 days before:
。
s4, comparing the variances to obtain a judgment result:
according to the data accumulated earlier, when
And
when the difference value is larger than a certain check value, the interaction state of the exhibition item 1 is considered to be abnormal, and early warning information can be submitted.
In this embodiment, before the visitor arrives at the exhibition item 1, the visitor operates the exhibition item 1, the infrared sensing device 11 in the exhibition item 1 records the signal that the object is close to and leaves, and the signal is collected by the computer module 10 in the exhibition item 1, and is arranged into the data information with the timestamp, and then is transmitted to the external communication module 20 in the cloud server 2 through the network. After receiving the request information, the server program deployed in the cloud server 2 processes the request information into a database SQL statement through the data storage module 22, and stores the database SQL statement in the database.
The server program is provided with a timing data analysis module 23, and statistical analysis is carried out on the exhibition item interaction data in the database every morning to obtain possible fault exhibition items. At this time, the procedure was carried out in 2 steps.
The first step is that the exhibition item maintenance early warning information is pushed to a terminal wading pen 3 of a venue manager through a communication module 20 of the system, and the maintainer is reminded to finally confirm the operation state of the field exhibition item;
and the second step is to store the data analysis result into a database, and output the data analysis result to a browser webpage end in a chart form through a data chart display module 21, so that a manager can access the chart of the webpage end and check the specific analysis result and the operation condition of the exhibition item. The maintainer combines the actual running state of the exhibition item to evaluate and feed back the intelligent data analysis result of the system, and the result is stored in the database, so that more accurate calibration can be carried out on the subsequent data analysis.
Therefore, the system uses the infrared sensing module 11 to report each time of visitor interaction information of the exhibition item 1 to the remote cloud server 2, the interaction information is uniformly stored by the server, the data is regularly counted and analyzed, abnormal data is found out, the abnormal data is automatically reported to relevant responsible persons through the existing communication equipment such as mobile phone computers, and the periodical exhibition item maintenance time of the exhibition hall can be reduced.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (7)
1. The utility model provides a high in clouds intelligence early warning report system of repairment based on exhibition item interactive data which characterized in that includes:
the system comprises a display item (1), a cloud server (2) and a terminal device (3);
the exhibition item (1) is used for exhibiting media information in various forms to interact with tourists, and the exhibition item (1) is in signal connection with the cloud server (2);
the cloud server (2) is used for uniformly storing interaction information of tourists, counting and analyzing data at regular time and finding abnormal data, and the cloud server (2) is in signal connection with the terminal equipment (3);
the terminal device (3) is used for receiving an abnormal data report from the cloud server (2).
2. The cloud intelligent early warning and repair system based on exhibition item interactive data, according to claim 1, is characterized in that: the cloud server (2) comprises a communication module (20), a data chart display module (21), a data storage module (22) and a timing data analysis module (23);
the communication module (20) is used for transceiving wireless signals, and the communication module (20) is in signal connection with the terminal equipment (3);
the data chart module (21) is used for outputting the data recorded in the data storage module (22) in a chart form;
the data storage module (22) is used for storing the data collected from the exhibition item (1);
the timing data analysis module (23) is used for starting statistical analysis on the stored data at a preset timing moment to obtain a fault exhibition item.
3. The cloud intelligent early warning and repair system based on exhibition item interactive data, according to claim 2, is characterized in that: the exhibition item (1) comprises a computer module (10) and an infrared induction module (11);
the computer module (10) is used for collating the data acquired by the infrared sensing module (11), marking a timestamp and sending the timestamp to the cloud server (2), and the computer module (10) is in signal connection with the communication module (20);
the infrared sensing module (11) is used for recording data signals of approaching and leaving of an object.
4. The cloud intelligent early warning and repairing system based on exhibition item interactive data as claimed in claim 2, wherein the timing data analysis module (23) performs statistical analysis through the stored data, and the step of obtaining the fault exhibition item is:
s1, counting the total interaction time of each exhibition item (1) every day;
s2, calculating the variance of the running time data of the exhibition item (1) in the past 30 days;
s3, calculating the variance of the data added to the single day;
and S4, comparing the variances to obtain a judgment result.
5. The cloud-based intelligent early warning and repairing system based on exhibition-item interactive data of claim 4, wherein in step S2, the time duration is set as t1, t2, t3... t30,
average duration calculation
=(t1+t2+t3+...+t30)/30；
Calculate the variance of the overall standard deviation 30 days before:
。
6. the cloud-based intelligent early warning and repair system for exhibition-item interaction data according to claim 4, wherein in step S3,
average duration calculation
=(t1+t2+t3+...+t31)/31；
The global standard deviation was calculated 31 days before:
。
7. the cloud-based intelligent early-warning and repair system based on exhibition item interactive data of claim 4, wherein in step S4, according to the data accumulated in the previous stage, when the data is updated, the data is updated according to the updated data
And
is greater than a certain differenceWhen the experience value is obtained, the interaction state of the exhibition item (1) is considered to be abnormal, and early warning information can be submitted.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111436186.1A CN114139936A (en) | 2021-11-29 | 2021-11-29 | Cloud intelligent early warning and repair reporting system based on exhibition item interactive data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111436186.1A CN114139936A (en) | 2021-11-29 | 2021-11-29 | Cloud intelligent early warning and repair reporting system based on exhibition item interactive data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114139936A true CN114139936A (en) | 2022-03-04 |
Family
ID=80389976
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111436186.1A Pending CN114139936A (en) | 2021-11-29 | 2021-11-29 | Cloud intelligent early warning and repair reporting system based on exhibition item interactive data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114139936A (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105302120A (en) * | 2015-11-19 | 2016-02-03 | 广州云湾信息技术有限公司 | Remote service device, system and method of intelligent equipment |
| CN105430091A (en) * | 2015-12-11 | 2016-03-23 | 山东科大机电科技股份有限公司 | Cloud storage based remote equipment health management method and system using same |
| CN106650846A (en) * | 2016-11-25 | 2017-05-10 | 塔米智能科技（北京）有限公司 | Science museum item on display popularity statistical system based on RFID and using method thereof |
| CN110727560A (en) * | 2019-10-12 | 2020-01-24 | 北京百度网讯科技有限公司 | Cloud service alarm method and device |
| CN110940921A (en) * | 2019-12-11 | 2020-03-31 | 山东工商学院 | Multi-fault diagnosis method and system of lithium ion battery string based on correction variance |
| CN111193643A (en) * | 2019-12-31 | 2020-05-22 | 苏州浪潮智能科技有限公司 | Cloud server state monitoring system and method |
| CN111487912A (en) * | 2020-05-12 | 2020-08-04 | 机科发展科技股份有限公司 | Central intelligent control system in venue |
| CN111865695A (en) * | 2020-07-28 | 2020-10-30 | 浪潮云信息技术股份公司 | Method and system for automatic fault handling in cloud environment |
-
2021
- 2021-11-29 CN CN202111436186.1A patent/CN114139936A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105302120A (en) * | 2015-11-19 | 2016-02-03 | 广州云湾信息技术有限公司 | Remote service device, system and method of intelligent equipment |
| CN105430091A (en) * | 2015-12-11 | 2016-03-23 | 山东科大机电科技股份有限公司 | Cloud storage based remote equipment health management method and system using same |
| CN106650846A (en) * | 2016-11-25 | 2017-05-10 | 塔米智能科技（北京）有限公司 | Science museum item on display popularity statistical system based on RFID and using method thereof |
| CN110727560A (en) * | 2019-10-12 | 2020-01-24 | 北京百度网讯科技有限公司 | Cloud service alarm method and device |
| CN110940921A (en) * | 2019-12-11 | 2020-03-31 | 山东工商学院 | Multi-fault diagnosis method and system of lithium ion battery string based on correction variance |
| CN111193643A (en) * | 2019-12-31 | 2020-05-22 | 苏州浪潮智能科技有限公司 | Cloud server state monitoring system and method |
| CN111487912A (en) * | 2020-05-12 | 2020-08-04 | 机科发展科技股份有限公司 | Central intelligent control system in venue |
| CN111865695A (en) * | 2020-07-28 | 2020-10-30 | 浪潮云信息技术股份公司 | Method and system for automatic fault handling in cloud environment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110276410B (en) | Method and device for determining bad reason, electronic equipment and storage medium | |
| CN106940677A (en) | One kind application daily record data alarm method and device | |
| CN102611565B (en) | Regular expression-based alarm correlation analysis method for monitoring system | |
| WO2016177566A1 (en) | Anomaly detection for context-dependent data | |
| CN106817708B (en) | A kind of inspection cluster construction method and device | |
| Huang et al. | Building intelligence in automated traffic signal performance measures with advanced data analytics | |
| US20170039264A1 (en) | Area modeling by geographic photo label analysis | |
| CN110751080A (en) | Gathering early warning method and system for abnormal personnel and related device | |
| CN105912709A (en) | Big data-based accompanying vehicle analysis method and system | |
| CN112181967A (en) | Method and device for monitoring source data quality, computer equipment and medium | |
| CN107784649A (en) | Plug test remote alarming system and method based on image recognition | |
| CN102385632A (en) | Method and system for log automatic classification and notification | |
| CN114936214A (en) | Data real-time updating method, device, equipment and storage medium | |
| CN100413257C (en) | Network element warning data obtaining method | |
| CN114139936A (en) | Cloud intelligent early warning and repair reporting system based on exhibition item interactive data | |
| KR20170137756A (en) | Aggregation of large amounts of temporal data from multiple overlapping sources | |
| CN107608584B (en) | Method for automatically refreshing man-machine interface picture | |
| CN110019237B (en) | System and method for analyzing criminal whereabouts based on map | |
| CN108874767B (en) | Four-dimensional model intelligent comparison system and method for public security system | |
| CN116149947A (en) | Quality evaluation method and device for data model, electronic equipment and storage medium | |
| CN102402610A (en) | Method and system for automatically classifying and informing logs | |
| CN112182212B (en) | Processing method and system for network vehicle collision data | |
| CN109697856B (en) | Vehicle information searching and seizing method | |
| CN205510066U (en) | Well short wave transmitting machine fault early -warning device | |
| Steur | Twitter as a spatio-temporal source for incident management |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |