CN114613101A - Intelligent hotel security system based on big data - Google Patents
Intelligent hotel security system based on big data Download PDFInfo
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- G—PHYSICS
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Abstract
The invention discloses an intelligent hotel intelligent security system based on big data, relates to the technical field of intelligent security, and solves the technical problems that the security function of a hotel in the prior art is single, expansion is not supported, the security effect is poor, and the people flow advantage of the hotel cannot be fully utilized; the system comprises a processor, a data storage module, a management monitoring module, a data acquisition module, a data analysis module and a region early warning module; the security monitoring system is provided with the data analysis module and the area early warning module, so that security monitoring is performed on the hotel from two aspects of environment analysis and character analysis, the security comprehensiveness of the hotel is ensured, and the security of the tenants is ensured; when the suspect is a criminal suspect, early warning is sent to the tenants on the floor where the moving track and the predicted track pass through, and safety personnel are dispatched to arrive in time, so that the safety of the tenants is ensured; when the suspected person is the missing population, the tenants corresponding to the moving track and the predicted track can provide clues to ensure the safety of the missing population.
Description
Technical Field
The invention belongs to the field of intelligent security, relates to a big data technology, and particularly relates to a smart hotel intelligent security system based on big data.
Background
The main functions of the hotel are to provide guests with accommodation, dining, entertainment and leisure. Due to the characteristic of open business of hotels, the number of people coming in and going out of the hotels is large, and the number of people outside the hotels and mobile staff is the largest part, so that various potential safety hazards exist. The potential safety hazard directly influences the personal safety and property safety of the tenants and also directly influences the reputation and business of the hotel. Therefore, the intelligent security system of the hotel with complete functions is necessary.
The invention patent with publication number CN106651119A discloses an engineering security decision system of a smart hotel, which comprises hotel equipment, a state information acquisition interface module, an environment information acquisition interface module, a regional equipment configuration management module, a comprehensive analysis module and an engineering security comprehensive decision module: the hotel equipment is respectively connected with the state information acquisition interface module and the environment information acquisition interface module; the state information acquisition interface module, the environment information acquisition interface module and the regional equipment configuration management module are all connected with the comprehensive analysis module; and the comprehensive analysis module is connected with the engineering security comprehensive decision-making module.
According to the scheme, the running state information of hotel equipment and the environmental parameter information of each area of the hotel are comprehensively analyzed, a processing task is generated when the equipment fails or the environment is abnormal, the generated processing task is decided, an execution object of the task is determined to be pushed, and equipment maintenance or the processing of the environmental abnormal condition can be quickly and accurately realized; however, the security function of the scheme is too single, and abnormal information cannot be transmitted to the tenants; therefore, the above solution still needs further improvement.
Disclosure of Invention
The invention provides a smart hotel intelligent security system based on big data, which is used for solving the technical problems that the security function of a hotel in the prior art is single, the security effect is poor due to the fact that expansion is not supported, and the people flow advantage of the hotel cannot be fully utilized.
The purpose of the invention can be realized by the following technical scheme: an intelligent security system of a smart hotel based on big data comprises a processor and a data storage module;
the processor is respectively communicated and/or electrically connected with the data analysis module and the area early warning module;
the data acquisition module is in communication and/or electrical connection with the acquisition sensor, acquires real-time data through the acquisition sensor and sends the real-time data to the data analysis module;
the data analysis module is used for analyzing the real-time data, generating a data analysis label and carrying out early warning according to the data analysis label; the data analysis tag comprises an environment analysis tag and a person analysis tag, and the form of the data analysis tag is [ the environment analysis tag, the person analysis tag ];
the area early warning module divides the hotel into a plurality of early warning areas according to the data analysis label, and sets area early warning grades for the early warning areas; and sending a safety early warning signal to the tenant, and simultaneously dispatching safety personnel to an early warning area.
Preferably, the acquisition sensor comprises a plurality of high-definition cameras, a temperature sensor, an air quality detector, a humidity sensor and a smoke alarm; the real-time data includes monitoring images, temperature, humidity and smoke concentration.
Preferably, analyzing the real-time data acquisition environment analysis tag includes:
extracting environmental data in the real-time data; wherein the environmental data comprises temperature, humidity, air quality index and smoke concentration;
generating an environment sequence according to the environment data; wherein the environmental sequence is a sequence representation of environmental data;
inputting the environment sequence into an environment evaluation model to obtain a corresponding environment analysis label; the value of the environment analysis tag is 0 or 1, when the environment analysis tag is 1, the environment data is abnormal, and when the environment analysis tag is 0, the environment data is normal.
Preferably, the generating of the environment assessment model comprises:
acquiring an original sequence training set through a data storage module; the original sequence training set comprises temperature, humidity, an air quality index, smoke concentration and a corresponding environment analysis label; when the environmental analysis label is 1, at least one of the temperature, the humidity, the air quality index and the smoke concentration is not in a set proper range;
constructing an artificial intelligence model; wherein the artificial intelligence model comprises one or more of an error back propagation neural network, an RBF neural network, and a deep convolutional neural network;
training, testing and checking the artificial intelligence model through an original sequence training set, and marking the trained artificial intelligence model as an environment evaluation model.
Preferably, analyzing the real-time data to obtain a human analysis tag includes:
extracting image data in the real-time data; the image data is subjected to image preprocessing, and the image preprocessing comprises image segmentation, image denoising and gray level transformation;
acquiring a face image of a person in image data through an image recognition technology, and analyzing and matching the face image with a face image of the person in a suspected feature library; the suspected characteristic library is stored in the data storage module and is updated in real time, and stores the basic information of a suspected person, wherein the basic information comprises a name, an age, a sex and a facial image;
when the analysis matching is successful, setting the character analysis tag as 1, marking the corresponding suspect as a target character, generating the movement track of the target character according to the time sequence, and acquiring the predicted track of the target character through a track prediction model; otherwise, the person analysis flag is set to 0.
Preferably, the obtaining of the plurality of early warning areas comprises:
after the data analysis tag is received by the region early warning module, extracting an environment analysis tag and a character analysis tag;
when the environment analysis tag is 1 and the character analysis tag is 0, acquiring a floor with abnormal environment in the hotel and marking as a target floor, setting the regional early warning level of the target floor to be 1, and sending an environment early warning signal to the management monitoring module and the tenant of the target floor;
when the environment analysis tag is 0 and the figure analysis tag is 1, acquiring floors through which a moving track and a predicted track of a suspect pass and marking the floors as suspect floors, setting the regional early warning level of the suspect floors to be 2, and sending figure early warning signals to the management monitoring module and tenants on the suspect floors;
when the environment analysis label is 1 and the person analysis label is 1, setting the regional early warning level of the hotel to be 3, and sending a danger early warning signal to the management monitoring module and the tenants in the hotel; wherein a plurality of the early warning areas comprise target floors, suspected floors and hotels.
Preferably, the processor is further in communication and/or electrical connection with the management monitoring module; the management monitoring module is respectively communicated and/or electrically connected with the data storage module and the data analysis module;
the management monitoring module performs early warning according to the safety early warning signal and dispatches security personnel; the safety early warning signals comprise environment early warning signals, people early warning signals and danger early warning signals;
the data analysis module is respectively communicated and/or electrically connected with the data acquisition module and the area early warning module; the data acquisition module is in communication and/or electrical connection with the data storage module.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention is provided with a data analysis module and a region early warning module; the data analysis module is used for analyzing the real-time data, extracting environmental data in the real-time data and generating an environmental sequence according to the environmental data; inputting the environment sequence into an environment evaluation model to obtain a corresponding environment analysis tag; extracting image data in the real-time data, acquiring a face image of a person in the image data through an image recognition technology, analyzing and matching the face image with a face image of the person in a suspected feature library, setting a person analysis tag to be 1 when the analysis and matching are successful, and otherwise, setting the person analysis tag to be 0; the area early warning module divides the hotel into a plurality of early warning areas according to the data analysis label, and sets area early warning levels for the early warning areas; sending a safety early warning signal to a tenant, and sending safety personnel to an early warning area; the security monitoring is carried out on the hotel from two angles of environmental analysis and character analysis, the comprehensiveness of the security of the hotel is guaranteed, different security personnel are dispatched according to different early warning fields, and the security of the tenants is guaranteed.
2. When the figure analysis label is 1, the moving track and the prediction track of the corresponding suspect are obtained; when the suspect is a criminal suspect, early warning is sent to the tenants on the floor where the moving track and the predicted track pass through, and safety personnel are dispatched to arrive in time, so that the safety of the tenants is ensured; when the suspected person is the missing population, the tenants corresponding to the moving track and the predicted track can provide clues to ensure the safety of the missing population.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic diagram of the principle of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terminology used herein is for the purpose of describing embodiments and is not intended to be limiting and/or limiting of the present disclosure; it should be noted that the singular forms "a," "an," and "the" include the plural forms as well, unless the context clearly indicates otherwise; also, although the terms first, second, etc. may be used herein to describe various elements, the elements are not limited by these terms, which are only used to distinguish one element from another.
Referring to fig. 1, a smart hotel intelligent security system based on big data includes a processor and a data storage module;
the processor is respectively communicated and/or electrically connected with the data analysis module and the area early warning module;
the data acquisition module is in communication and/or electrical connection with the acquisition sensor, acquires real-time data through the acquisition sensor and sends the real-time data to the data analysis module;
the data analysis module is used for analyzing the real-time data, generating a data analysis label and carrying out early warning according to the data analysis label; wherein the data analysis tags comprise an environmental analysis tag and a human analysis tag;
the area early warning module divides the hotel into a plurality of early warning areas according to the data analysis label, and sets area early warning levels for the early warning areas; and sending a safety early warning signal to the tenant, and simultaneously dispatching safety personnel to an early warning area.
The acquisition sensor comprises a plurality of high-definition cameras, a temperature sensor, an air quality detector, a humidity sensor and a smoke alarm; the real-time data includes monitoring images, temperature, humidity and smoke concentration.
Extracting environmental data in the real-time data; wherein the environmental data comprises temperature, humidity, air quality index and smoke concentration;
generating an environment sequence according to the environment data; wherein the environmental sequence is a sequence representation of environmental data;
inputting the environment sequence into an environment evaluation model to obtain a corresponding environment analysis tag; the value of the environment analysis tag is 0 or 1, when the environment analysis tag is 1, the environment data is abnormal, and when the environment analysis tag is 0, the environment data is normal.
In the embodiment, the environment data is analyzed through the artificial intelligence model to obtain the environment analysis label; when the environmental data in the real-time data is not in the set safety range, setting the environmental analysis tag as 1; in some embodiments, different environment analysis tags may be set according to the abnormality of different parameters, such as temperature abnormality, setting the environment analysis tag to 01, humidity abnormality, setting the environment analysis tag to 02; aiming at abnormal environment, security personnel and tenants can be informed in time, and the injuries to the tenants caused by accidents like gas poisoning, fire and the like are avoided.
Extracting image data in the real-time data;
acquiring a face image of a person in image data through an image recognition technology, and analyzing and matching the face image with a face image of the person in a suspected feature library; the suspicion characteristic library is stored in the data storage module and is updated in real time, the suspicion characteristic library stores basic information of suspects, the suspects comprise criminal suspects, and the basic information comprises names, ages, sexes and face images;
when the analysis matching is successful, setting the character analysis tag as 1, marking the corresponding suspect as a target character, generating the movement track of the target character according to the time sequence, and acquiring the predicted track of the target character through a track prediction model; otherwise, the person analysis flag is set to 0.
In the embodiment, the image data in the real-time data is analyzed through an image recognition technology; matching the facial image in the image data with the facial images of the persons in the suspect feature library, marking the corresponding persons as suspects after the matching is successful, and acquiring the movement track and the prediction track of the suspects; in other embodiments, the suspect may be a missing person or a psychiatric patient; through image recognition technology, video image data of hotels are analyzed, suspicious people or missing people can be found in time, meanwhile, a suspect feature database is uploaded through a police service platform or a medical platform, and suspects can be found out in time through linkage of all hotels.
After the data analysis tag is received by the region early warning module, extracting an environment analysis tag and a character analysis tag;
when the environment analysis tag is 1 and the figure analysis tag is 0, acquiring a floor with abnormal environment in the hotel and marking the floor as a target floor, setting the regional early warning level of the target floor to be 1, and sending an environment early warning signal to the management monitoring module and the tenant of the target floor;
when the environment analysis tag is 0 and the figure analysis tag is 1, acquiring floors through which a moving track and a predicted track of a suspect pass and marking the floors as suspect floors, setting the regional early warning level of the suspect floors to be 2, and sending figure early warning signals to the management monitoring module and tenants on the suspect floors;
when the environment analysis label is 1 and the person analysis label is 1, setting the regional early warning level of the hotel to be 3, and sending a danger early warning signal to the management monitoring module and the tenants in the hotel; wherein a plurality of the early warning areas comprise target floors, suspected floors and hotels.
In the embodiment, the early warning area and the safety early warning signal are determined by analyzing the data label; when the environment is abnormal, marking the corresponding floor as an early warning area, simultaneously sending an environment early warning signal to the tenants in the early warning area, dispatching safety personnel to the early warning area by the management monitoring module for processing, and meanwhile, early warning the tenants in other areas of the hotel to report the abnormality of the early warning area; when the person is analyzed to be abnormal, marking the moving track of the suspect and the floor where the predicted track passes as an early warning area, and early warning the tenants in the early warning area or even other areas of the hotel; when the environment is abnormal and the character analysis is abnormal, marking the whole hotel as an early warning area, and sending a safety early warning signal to all the tenants in the hotel; and the classification treatment can ensure the safety of the tenants, and can fully utilize security resources to improve the system operation efficiency.
The management monitoring module performs early warning according to the safety early warning signal and dispatches security personnel; the safety early warning signals comprise environment early warning signals, people early warning signals and danger early warning signals.
In the embodiment, different security early warning signals can send different security personnel; if the environment is abnormal, 2 security personnel are dispatched, the person analysis is abnormal, 4 security personnel are dispatched, and both are abnormal, all the security personnel are dispatched.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
The working principle of the invention is as follows:
extracting environmental data in the real-time data, and generating an environmental sequence according to the environmental data; inputting the environment sequence into an environment evaluation model to obtain a corresponding environment analysis tag; extracting image data in the real-time data, acquiring a face image of a person in the image data through an image recognition technology, analyzing and matching the face image with a face image of the person in a suspected feature library, setting a person analysis tag to be 1 when the analysis and matching are successful, and otherwise, setting the person analysis tag to be 0; and generating a data analysis label and sending the data analysis label to the area early warning module.
After the data analysis tag is received by the region early warning module, extracting an environment analysis tag and a character analysis tag; when the environment analysis tag is 1 and the figure analysis tag is 0, acquiring a floor with abnormal environment in the hotel and marking the floor as a target floor, setting the regional early warning level of the target floor to be 1, and sending an environment early warning signal to the management monitoring module and the tenant of the target floor; when the environment analysis tag is 0 and the figure analysis tag is 1, acquiring floors through which a moving track and a predicted track of a suspect pass and marking the floors as suspect floors, setting the regional early warning level of the suspect floors to be 2, and sending figure early warning signals to the management monitoring module and tenants on the suspect floors; when the environment analysis label is 1 and the person analysis label is 1, the regional early warning level of the hotel is set to be 3, and a danger early warning signal is sent to the management monitoring module and the tenants in the hotel.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (6)
1. A smart hotel intelligent security system based on big data comprises a processor and a data storage module, and is characterized in that the processor is respectively communicated and/or electrically connected with a data analysis module and a region early warning module;
the data acquisition module is in communication and/or electrical connection with the acquisition sensor, acquires real-time data through the acquisition sensor and sends the real-time data to the data analysis module;
the data analysis module is used for analyzing the real-time data, generating a data analysis label and carrying out early warning according to the data analysis label; wherein the data analysis tags comprise an environmental analysis tag and a human analysis tag;
the area early warning module divides the hotel into a plurality of early warning areas according to the data analysis label, and sets area early warning grades for the early warning areas; and sending a safety early warning signal to the tenant, and simultaneously dispatching safety personnel to an early warning area.
2. The intelligent hotel security system based on big data as claimed in claim 1, wherein the collection sensor comprises a plurality of high-definition cameras, a temperature sensor, an air quality detector, a humidity sensor and a smoke alarm; the real-time data includes monitoring images, temperature, humidity and smoke concentration.
3. The intelligent hotel security system based on big data as claimed in claim 1, wherein analyzing the real-time data acquisition environment analysis tag comprises:
extracting environmental data in the real-time data; wherein the environmental data comprises temperature, humidity, air quality index and smoke concentration;
generating an environment sequence according to the environment data; wherein the environmental sequence is a sequence representation of environmental data; inputting the environment sequence into an environment evaluation model to obtain a corresponding environment analysis tag; the value of the environment analysis tag is 0 or 1, when the environment analysis tag is 1, the environment data is abnormal, and when the environment analysis tag is 0, the environment data is normal.
4. The big-data-based intelligent hotel security system as claimed in claim 3, wherein analyzing the real-time data-capturing person analysis tag comprises:
extracting image data in the real-time data; wherein the image data is subjected to image pre-processing;
acquiring a facial image of a person in image data through an image recognition technology, and analyzing and matching the facial image with a facial image of the person in a suspected feature library; the suspicion characteristic library is stored in the data storage module and is updated in real time, and the suspicion characteristic library stores the basic information of a suspicion person, wherein the basic information comprises a name, an age, a gender and a facial image;
when the analysis matching is successful, setting the character analysis tag as 1, marking the corresponding suspect as a target character, generating the movement track of the target character according to the time sequence, and acquiring the predicted track of the target character through a track prediction model; otherwise, the person analysis flag is set to 0.
5. The intelligent hotel security system based on big data as claimed in claim 4, wherein the obtaining of the plurality of pre-warning areas comprises:
after the data analysis tag is received by the region early warning module, extracting an environment analysis tag and a character analysis tag;
when the environment analysis tag is 1 and the figure analysis tag is 0, acquiring a floor with abnormal environment in the hotel and marking the floor as a target floor, setting the regional early warning level of the target floor to be 1, and sending an environment early warning signal to the management monitoring module and the tenant of the target floor;
when the environment analysis tag is 0 and the figure analysis tag is 1, acquiring floors through which a moving track and a predicted track of a suspect pass and marking the floors as suspect floors, setting the regional early warning level of the suspect floors to be 2, and sending figure early warning signals to the management monitoring module and tenants on the suspect floors;
when the environment analysis label is 1 and the person analysis label is 1, the regional early warning level of the hotel is set to be 3, and a danger early warning signal is sent to the management monitoring module and the tenants in the hotel.
6. The intelligent hotel security system based on big data as claimed in claim 5, wherein the processor is further in communication and/or electrical connection with the management monitoring module; the management monitoring module is respectively communicated and/or electrically connected with the data storage module and the data analysis module;
the management monitoring module performs early warning according to the safety early warning signal and dispatches security personnel; the safety early warning signals comprise environment early warning signals, people early warning signals and danger early warning signals;
the data analysis module is respectively communicated and/or electrically connected with the data acquisition module and the area early warning module; the data acquisition module is in communication and/or electrical connection with the data storage module.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210272866.2A CN114613101A (en) | 2022-03-18 | 2022-03-18 | Intelligent hotel security system based on big data |
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| CN202210272866.2A CN114613101A (en) | 2022-03-18 | 2022-03-18 | Intelligent hotel security system based on big data |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115277774A (en) * | 2022-07-28 | 2022-11-01 | 合肥未来计算机技术开发有限公司 | Remote scheduling system based on Internet of things in complex environment |
| CN116030607A (en) * | 2023-03-27 | 2023-04-28 | 中国电力工程顾问集团西南电力设计院有限公司 | Intelligent power plant safety supervision reminding and early warning system |
| CN117789128A (en) * | 2023-12-28 | 2024-03-29 | 广东科技学院 | Security equipment digital management method and system based on Internet of things |
-
2022
- 2022-03-18 CN CN202210272866.2A patent/CN114613101A/en not_active Withdrawn
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115277774A (en) * | 2022-07-28 | 2022-11-01 | 合肥未来计算机技术开发有限公司 | Remote scheduling system based on Internet of things in complex environment |
| CN116030607A (en) * | 2023-03-27 | 2023-04-28 | 中国电力工程顾问集团西南电力设计院有限公司 | Intelligent power plant safety supervision reminding and early warning system |
| CN116030607B (en) * | 2023-03-27 | 2023-06-09 | 中国电力工程顾问集团西南电力设计院有限公司 | Intelligent power plant safety supervision reminding and early warning system |
| CN117789128A (en) * | 2023-12-28 | 2024-03-29 | 广东科技学院 | Security equipment digital management method and system based on Internet of things |
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