CN115861905A - Hotel management system based on Internet of things - Google Patents
Hotel management system based on Internet of things Download PDFInfo
- Publication number
- CN115861905A CN115861905A CN202310181202.XA CN202310181202A CN115861905A CN 115861905 A CN115861905 A CN 115861905A CN 202310181202 A CN202310181202 A CN 202310181202A CN 115861905 A CN115861905 A CN 115861905A
- Authority
- CN
- China
- Prior art keywords
- monitoring video
- operation unit
- image
- analysis
- video segment
- 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.)
- Granted
Links
- 238000012544 monitoring process Methods 0.000 claims description 143
- 238000004458 analytical method Methods 0.000 claims description 124
- 238000007726 management method Methods 0.000 claims description 27
- 238000013500 data storage Methods 0.000 claims description 18
- 238000007689 inspection Methods 0.000 claims 8
- 230000000694 effects Effects 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 239000000284 extract Substances 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 150000001875 compounds Chemical class 0.000 description 1
- 238000000034 method Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Closed-Circuit Television Systems (AREA)
- Image Analysis (AREA)
Abstract
The invention relates to the field of management systems, in particular to a hotel management system based on the Internet of things.
Description
Technical Field
The invention relates to the field of management systems, in particular to a hotel management system based on the Internet of things.
Background
Along with the development of society, people go on business and travel frequency increases, the safety level of hotel management is more and more closely related to the work and life of people, and along with the improvement of safety awareness of people, the requirement on the safety of hotel management is higher and higher, so that various hotel management digital systems come into force.
Chinese patent publication No.: CN107942893a discloses the following content, the invention discloses a hotel room management system based on internet of things and internet, which comprises a user terminal, a hotel management system and a room control system, wherein the rooms of the hotel are all provided with a room control system, the user terminal and the hotel management system are communicated through a wired network and/or a wireless network, and the user terminal and the room control system are communicated through a wired network and/or a wireless network. The hotel room control system has the advantages that hotel room equipment and service are integrally controlled through the combination of the internet, the internet of things and the database, a user can realize functions such as check-in, room control and room returning through a mobile phone, an IPAD or a notebook computer, each room is uniformly monitored by a hotel background management center, the stability and reliability of the whole room control system are ensured, and the intelligent degree is very high; in addition, the lighting module of the system is provided with an emergency module, and the emergency module also has a self-checking function, so that the condition that the lighting cannot be performed due to accidental power failure is prevented.
However, the prior art has the following problems:
due to the huge data volume of the hotel monitoring video, in the prior art, classification of the monitoring images according to the image characteristics in the monitoring video is not considered, analysis is carried out at different analysis intervals, the number of data operations is reduced on the premise of improving reliability, the system load is reduced, and the data processing efficiency of the system is improved.
Disclosure of Invention
In order to solve the problem that the data volume of hotel monitoring videos is huge, classification of monitoring images according to image features in the monitoring videos is not considered, and analysis is performed at different analysis intervals so as to reduce the number of data operations on the premise of improving reliability, the invention provides an internet-of-things-based hotel management system, which comprises:
the system comprises a data acquisition module, a monitoring module and a monitoring module, wherein the data acquisition module comprises a plurality of security cameras arranged in a hotel to acquire a monitoring video;
the data storage module is connected with the data acquisition module and used for storing the monitoring video acquired by the data acquisition module;
the data distribution module is connected with the data storage module and is used for dividing a monitoring video into a plurality of monitoring video segments and analyzing and acquiring the image complex condition of the monitoring video segments based on the image characteristics of each monitoring video segment;
a data processing module including a first arithmetic unit, a second arithmetic unit and a third arithmetic unit connected to each other,
the first operation unit is connected with the data storage module and the data distribution module and is used for acquiring a monitoring video segment of a first image complex condition and analyzing video frames in the monitoring video segment at a first analysis interval so as to analyze character information in the video frames;
the second operation unit is connected with the data storage module and the data distribution module and used for acquiring a monitoring video segment of a second image in a complex state, analyzing video frames in the monitoring video segment at a second analysis interval to analyze character information in the video frames, calibrating a plurality of sub-monitoring video segments before analysis by the second operation unit, and adjusting the second analysis interval when analyzing the video frames of the calibrated sub-monitoring video segments;
the third operation unit is connected with the data storage module and the data distribution module to acquire a monitoring video segment of a third image in a complex state, and analyzes a video frame in the monitoring video segment at a first analysis interval after image enhancement processing is performed on the video frame to analyze character information in the video frame, wherein the image enhancement processing comprises adjusting the contrast of the video frame according to the brightness value of the video frame.
Wherein the second resolution interval is greater than the first resolution interval.
Further, the data distribution module obtains image characteristics of the monitored video segments, wherein the image characteristics comprise the number Nr of the person outlines, the number Nw of the object outlines and the brightness value L of all the video frames in the monitored video segments, calculates an image characteristic parameter P according to a formula (1), calculates an average brightness value DeltaL according to a formula (2),
in the formula (1), the first and second groups of the compound,
represents the number of human profiles in an ith video frame in the monitored video segment, and +>
Representing the number of object outlines in the ith video frame in the monitoring video segment, and n representing the number of video frames in the monitoring video segment;
in formula (2), li represents the luminance value of the ith video frame in the monitoring video segment.
Further, the data distribution module compares the image characteristic parameter P with a preset first image characteristic contrast threshold P1 and compares the average brightness value Δ L with a preset brightness contrast threshold Δ L0, and determines the image complexity of the monitored video segment according to the comparison result, wherein,
under the first comparison result, the data distribution module judges that the monitoring video segment is in a first image complex state;
under the second comparison result, the data distribution module judges that the monitoring video segment is in a second image complex state;
under a third comparison result, the data distribution module judges that the monitoring video segment is in a third image complex state;
wherein the first comparison result is that P is more than or equal to P1 and delta L is more than or equal to delta L0, the second comparison result is that P is less than P1 and delta L is more than or equal to delta L0, and the third comparison result is that delta L is less than delta L0.
Further, the second arithmetic unit obtains the number Nr of the human profiles and the number Nw of the object profiles in each video frame of the sub-monitoring video segment, calculates an image characteristic parameter P corresponding to the sub-monitoring video segment according to formula (1), and compares the image characteristic parameter P with a preset second image characteristic comparison threshold P2 to determine whether to calibrate the sub-monitoring video segment, wherein,
under the comparison result of the preset parameters, the second operation unit judges that the sub monitoring video segment needs to be calibrated;
and the preset parameter comparison result is that P is less than P2, and P2 is less than P1.
Further, the second arithmetic unit compares the image characteristic parameter P corresponding to the calibrated sub-monitoring video segment with a preset third image characteristic comparison threshold P3 and a preset fourth image characteristic comparison threshold P4, determines an adjustment mode when adjusting the second analysis interval according to the comparison result, and analyzes the calibrated sub-monitoring video segment with the adjusted second analysis interval, wherein,
the first analysis interval adjustment mode is that the second operation unit adjusts the second analysis interval to a first analysis interval adjustment value T1 according to a preset first analysis interval adjustment parameter T1;
the second analysis interval adjustment mode is that the second operation unit adjusts the second analysis interval to a second analysis interval adjustment value T2 according to a preset second analysis interval adjustment parameter T2;
the third analysis interval adjustment mode is that the second operation unit adjusts the second analysis interval to a third analysis interval adjustment value T3 according to a preset third analysis interval adjustment parameter T3;
the first analysis interval adjusting mode needs to satisfy that P is more than or equal to P4, the second analysis interval adjusting mode needs to satisfy that P3 is more than or equal to P and is less than P4, the third analysis interval adjusting mode needs to satisfy that P is less than P3, P3 is less than P4 and is less than P2, and t1 is less than t2 and is less than t3.
Further, the first operation unit, the second operation unit and the third operation unit comprise when analyzing the character information in the video frame,
acquiring face information of a figure outline in a video frame, matching the face information with data in a preset registered face information database to judge whether unregistered persons exist or not, wherein,
if the registered face information database has data matched with the face information, the first operation unit and the second operation unit obtain a first analysis result;
if no data in the registered face information database is matched with the face information, the first operation unit and the second operation unit obtain a second analysis result,
the first analysis result indicates that the face information is registered, and the second analysis result indicates that the face information is not registered.
Furthermore, the first arithmetic unit is further configured to determine whether to extract the video frames between the first parsing intervals for analysis,
under a first analysis condition, the first operation unit judges that video frames in a first analysis interval need to be extracted for analysis;
the first analysis condition is that the first operation unit continuously obtains a preset number of second analysis results.
Further, the third operation unit compares the brightness value L of the video frame with a preset first brightness enhancement contrast parameter L1 and a preset second brightness enhancement contrast parameter L2, and performs image enhancement processing on the video frame according to the comparison result, wherein,
under the condition of first brightness contrast, the third operation unit adjusts the contrast of the video frame to a first contrast value Le1 according to a first contrast adjustment parameter l1;
under the condition of second brightness contrast, the third operation unit adjusts the contrast of the video frame to a second contrast value Le2 according to a second contrast adjustment parameter l2;
under a third brightness contrast condition, the third operation unit adjusts the contrast of the video frame to a third contrast value Le3 according to a third contrast adjustment parameter l 3;
the first brightness contrast condition is that L is larger than or equal to L2, the second brightness contrast condition is that L1 is larger than or equal to L and is smaller than L2, and the third brightness contrast condition is that L is smaller than L1, L2 is larger than L1 and larger than delta L0, L1 is smaller than L2 and smaller than L3, and Le1 is smaller than Le2 and smaller than Le3.
Further, still including patrolling and examining the module, it includes patrols and examines the robot and patrols and examines data arithmetic unit to patrol and examine the data arithmetic unit and be used for acquireing each the control dead angle of security protection camera to confirm the dead angle position, it controls to patrol and examine data arithmetic unit every preset time interval patrol and examine the robot and remove to each dead angle position and patrol and examine to acquire the surveillance video of dead angle position.
Furthermore, the data acquisition module is also connected with an external display, so that the external display displays corresponding monitoring video contents.
Compared with the prior art, the data processing method and the data processing device have the advantages that the data acquisition module, the data storage module, the data distribution module and the data processing module are arranged, the data distribution module judges the image complex condition of the monitoring video segment based on the image characteristics in the monitoring video segment, the data processing module analyzes the monitoring video segment with the first image complex condition at the first analysis interval, analyzes the monitoring video segment with the second image complex condition at the second analysis interval, adjusts the second analysis interval when the monitoring video segment corresponding to the analysis is analyzed according to the image characteristics of the monitoring video segment with the second image complex condition, and analyzes the monitoring video segment with the third image complex condition at the first analysis interval after image enhancement, so that the data operation amount is reduced, the system load is reduced, and the image data processing efficiency and the image data processing effect of the system are improved on the premise of ensuring the reliability of the system.
Particularly, in the invention, the data distribution module judges the image complex condition of the monitoring video segment based on the image characteristics in the monitoring video segment, the image characteristic parameters are calculated by the number of the figure outlines and the number of the object outlines in each video frame in the monitoring video segment, the number of the figure outlines and the number of the object outlines in the video frames represent the complex condition of the real scene corresponding to the images, namely the complex condition of the images, if the number of the figure outlines and the number of the object outlines in the video frames are large, the complex condition of the corresponding images is more complex, the monitoring video segment is divided into three different image complex conditions according to the image characteristic parameters of the monitoring video segment and by combining brightness, and then corresponding adjustment and processing are carried out according to the different image complex conditions, so that the efficiency and the effect of analyzing the figure information in the video frames are ensured, and the safety of hotel management is improved.
Particularly, in the invention, the data processing module adjusts the second analysis interval when analyzing the corresponding sub-monitoring video segment according to the image characteristics of the sub-monitoring video segment of the monitoring video segment with the complex image condition, and when analyzing the corresponding monitoring video segment with a larger analysis interval under the condition of low image complexity, in practical situations, if the number of people and objects appearing in the sub-monitoring video segment in the monitoring video segment is small, the analysis waste can be caused by analyzing the video frame of the sub-monitoring video segment with the first analysis interval, and the image processing efficiency is reduced.
Particularly, in the invention, under the first image complex condition with high image complexity, when the person information in the video frame is analyzed, the video frame between the analysis intervals is extracted to be analyzed for the condition that people are not registered continuously, and in the actual situation, under the condition that the situation that people with more people are complicated, the possibility of potential safety hazard is high, and the situation needs to be further confirmed, so that the video frame between the analysis intervals needs to be extracted to be analyzed, the omission of key information is avoided, and the effect of analyzing the person information of the video frame in the monitoring video segment is effectively improved.
Particularly, in the invention, the data processing module performs image enhancement on the monitoring video segment with a third image complex condition and then analyzes the monitoring video segment with a first analysis interval, the third image complex condition is specific to the condition that the brightness of the monitoring video segment is low, in this case, the image enhancement is performed on the video frame in the monitoring video segment, the image enhancement comprises the adjustment of the contrast of the image, the identification rate of the character information is further improved, and then the character information in the video frame is analyzed with the first analysis interval, so that the omission of key information in the video frame is avoided, the reliability of the system is improved, and the effect of safe hotel management is ensured.
Drawings
Fig. 1 is a schematic structural diagram of a hotel management system based on the internet of things according to an embodiment of the present invention;
FIG. 2 is a block diagram of a data processing module according to an embodiment of the present invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principle of the present invention, and do not limit the scope of the present invention.
It should be noted that in the description of the present invention, the terms of direction or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, which are only for convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1 and 2, which are schematic structural diagrams of an internet of things-based hotel management system and a schematic structural diagram of a data processing module according to an embodiment of the present invention, the internet of things-based hotel management system includes:
the system comprises a data acquisition module, a monitoring module and a monitoring module, wherein the data acquisition module comprises a plurality of security cameras arranged in a hotel to acquire a monitoring video;
the data storage module is connected with the data acquisition module and used for storing the monitoring video acquired by the data acquisition module;
the data distribution module is connected with the data storage module and is used for dividing a monitoring video into a plurality of monitoring video segments and analyzing and acquiring the image complex condition of the monitoring video segments based on the image characteristics of each monitoring video segment;
a data processing module including a first arithmetic unit, a second arithmetic unit and a third arithmetic unit connected to each other,
the first operation unit is connected with the data storage module and the data distribution module and is used for acquiring a monitoring video segment of a first image complex condition and analyzing video frames in the monitoring video segment at a first analysis interval so as to analyze character information in the video frames;
the second operation unit is connected with the data storage module and the data distribution module and used for acquiring a monitoring video segment of a second image in a complex state, analyzing video frames in the monitoring video segment at a second analysis interval to analyze figure information in the video frames, calibrating a plurality of sub-monitoring video segments before analysis by the second operation unit, and adjusting the second analysis interval when analyzing the video frames of the calibrated sub-monitoring video segments;
the third operation unit is connected with the data storage module and the data distribution module to acquire a monitoring video segment of a third image in a complex state, and analyzes a video frame in the monitoring video segment at a first analysis interval after performing image enhancement processing on the video frame to analyze character information in the video frame, wherein the image enhancement processing comprises adjusting the contrast of the video frame according to the brightness value of the video frame;
wherein the second resolution interval is greater than the first resolution interval.
Specifically, the monitoring video segments are divided into three different image complex conditions, and the corresponding monitoring video segments under the condition of low image complex degree are analyzed at a larger analysis interval, so that the number of data operations is reduced on the premise of improving the reliability, the system load is reduced, and the data processing efficiency of the system is improved.
Specifically, the specific form of the data storage module is not limited in the present invention, and for example, the data storage module may be a hardware storage device or a cloud database of a cloud storage platform, and only the function of storing the monitoring video needs to be completed, which is not described herein again.
Specifically, the specific form of the data offloading module is not limited in the present invention, and the data offloading module may be a functional program in a computer, or may be a computer itself, and only needs to complete functions of data processing, data receiving, and data sending, which are not described herein again for the existing mature technology.
Specifically, the specific form of the data processing module is not limited in the present invention, and the data processing module may be an external computer, and each unit therein may be a functional program in the computer, and only needs to complete the functions of data processing, data receiving, and data sending, which are not described herein again for the existing mature technology.
Specifically, the data distribution module obtains image characteristics of a monitored video segment, wherein the image characteristics comprise the number Nr of person outlines, the number Nw of object outlines and a brightness value L of each video frame in the monitored video segment, calculates an image characteristic parameter P according to a formula (1), calculates an average brightness value DeltaL according to a formula (2),
in the formula (1), the first and second groups,
represents the number of the person profile in the ith video frame in the monitoring video segment, and/or is selected>
Representing the number of object outlines in the ith video frame in the monitoring video segment, and n representing the number of video frames in the monitoring video segment;
in formula (2), li represents the luminance value of the ith video frame in the monitoring video segment.
Specifically, the specific way of obtaining the image features by the data splitting module is not limited, and of course, preferably, the image recognition model may be trained in advance, and the image recognition model is imported into the data splitting module, so that the data splitting module has an image recognition function.
Specifically, the data splitting module compares the image characteristic parameter P with a preset first image characteristic contrast threshold P1 and compares the average brightness value Δ L with a preset brightness contrast threshold Δ L0, where Δ L0 is greater than 40, and determines the image complexity of the monitoring video segment according to the comparison result, where,
under the first comparison result, the data distribution module judges that the monitoring video segment is in a first image complex state;
under a second comparison result, the data distribution module judges that the monitoring video segment is in a second image complex state;
under a third comparison result, the data distribution module judges that the monitoring video segment is in a third image complex state;
wherein the first comparison result is that P is more than or equal to P1 and delta L is more than or equal to delta L0, the second comparison result is that P is less than P1 and delta L is more than or equal to delta L0, and the third comparison result is that delta L is less than delta L0.
Specifically, when the first image feature contrast threshold P1 is determined, a complete video segment acquired by a single camera in a single month of a hotel is selected as sample data, 38880000 frames are counted, image feature parameters P corresponding to video frames of the complete video segment are calculated frame by frame, an average value of the image feature parameters is 25 after the average value is solved, and then the first image feature contrast threshold P1 is determined to be 25, where P2=0.9 × P1, P4=0.8 × P1, and P3=0.7 × P1.
Specifically, in the invention, the data distribution module judges the image complex condition of the monitoring video segment based on the image characteristics in the monitoring video segment, the image characteristic parameters are obtained by calculating the number of the figure outlines and the number of the object outlines in each video frame in the monitoring video segment, the number of the figure outlines and the number of the object outlines in the video frames represent the complex condition of a real scene corresponding to the images, namely the complex condition of the images, if the number of the figure outlines and the number of the object outlines in the video frames are large, the complex condition of the corresponding images is more complex, the monitoring video segment is divided into three different image complex conditions according to the image characteristic parameters of the monitoring video segment and by combining brightness, and corresponding adjustment and processing are subsequently performed according to the different image complex conditions, so that the efficiency and the effect of analyzing the figure information in the video frames are ensured, and the safety of hotel management is improved.
Specifically, the second arithmetic unit obtains the number Nr of the human profiles and the number Nw of the object profiles in each video frame in the sub-monitoring video segment, calculates the image characteristic parameter P corresponding to the sub-monitoring video segment according to the formula (1), and compares the image characteristic parameter P with a preset second image characteristic comparison threshold P2 to determine whether to calibrate the sub-monitoring video segment, wherein,
under the comparison result of preset parameters, the second operation unit judges that the sub monitoring video segment needs to be calibrated;
and the preset parameter comparison result is that P is less than P2, and P2 is less than P1.
Specifically, the second arithmetic unit compares the image characteristic parameter P corresponding to the calibrated sub-monitoring video segment with a preset third image characteristic comparison threshold P3 and a preset fourth image characteristic comparison threshold P4, determines an adjustment mode when adjusting the second analysis interval according to the comparison result, and analyzes the calibrated sub-monitoring video segment at the adjusted second analysis interval,
the first analysis interval adjustment mode is that the second operation unit adjusts the second analysis interval to a first analysis interval adjustment value T1 according to a preset first analysis interval adjustment parameter T1, T1= T0+ T1 is set, T0 represents an initial second analysis interval, and 100ms < T0 < 200ms;
the second analysis interval adjustment mode is that the second operation unit adjusts the second analysis interval to a second analysis interval adjustment value T2 according to a preset second analysis interval adjustment parameter T2, and sets T2= T0+ T2;
the third analysis interval adjustment mode is that the second operation unit adjusts the second analysis interval to a third analysis interval adjustment value T3 according to a preset third analysis interval adjustment parameter T3, and sets T3= T0+ T3;
the first analysis interval adjusting mode needs to satisfy that P is more than or equal to P4, the second analysis interval adjusting mode needs to satisfy that P3 is more than or equal to P and is less than P4, the third analysis interval adjusting mode needs to satisfy that P is more than or equal to P3, P3 is more than P4 and is less than P2, P3 is more than 5 and is more than P4 and is more than P2 and is less than P1 and is less than 30, t1 is more than t2 and is less than t3, t1 is more than or equal to 400ms and is less than 600ms, t2 is more than or equal to 600ms, and t3 is more than or equal to 800ms and is less than 1000ms.
Specifically, in the invention, the data processing module adjusts the second analysis interval when analyzing the corresponding sub-monitoring video segment according to the image characteristics of the sub-monitoring video segment of the monitoring video segment with the complex second image, and when analyzing the corresponding monitoring video segment with a larger analysis interval under the condition of low image complexity, in practical situations, if the number of people and objects appearing in the sub-monitoring video segment in the monitoring video segment is small, the analysis waste can be caused by analyzing the video frame of the sub-monitoring video segment with the first analysis interval, and the image processing efficiency is reduced.
Specifically, the first, second and third arithmetic units analyze the character information in the video frame,
acquiring face information of a figure outline in a video frame, matching the face information with data in a preset registered face information database to judge whether unregistered persons exist or not, wherein,
if the registered face information database has data matched with the face information, the first operation unit and the second operation unit obtain a first analysis result;
if no data in the registered face information database is matched with the face information, the first operation unit and the second operation unit obtain a second analysis result,
the first analysis result indicates that the face information is registered, and the second analysis result indicates that the face information is not registered.
Specifically, the function of identifying the face information in the video frame is completed by adopting a video frame analysis technology when the first operation unit, the second operation unit and the third operation unit analyze the video frame, which is a mature technology in the prior art and is not repeated.
Specifically, the first arithmetic unit is further configured to determine whether a video frame between the first parsing intervals needs to be extracted for analysis,
under a first analysis condition, the first arithmetic unit judges that video frames in a first analysis interval need to be extracted for analysis;
the first analysis condition is that the first operation unit continuously acquires a preset number of second analysis results, that is, the first operation unit continuously acquires the situation that a preset number of face information is not registered as the first analysis condition.
Specifically, in the invention, the registered face database can be constructed by obtaining the face information of the user after the hotel is authorized, and the corresponding data algorithm can be selected according to specific needs for the matching of the face information, and the related matching algorithm is the prior art and is not described herein again.
Specifically, in the invention, under the first image complex condition with high image complexity, when analyzing the personal information in the video frame, the data processing module extracts the video frame between the analysis intervals for analyzing the situation that no registered person continuously appears, and in the actual situation, under the situation that more persons exist, the possibility of potential safety hazard is high, and the situation needs to be further confirmed, so that the video frame between the analysis intervals needs to be extracted for analysis, thereby avoiding missing key information and effectively improving the effect of analyzing the personal information of the video frame in the monitoring video segment.
Specifically, the third operation unit compares the brightness value L of the video frame with a preset first brightness enhancement contrast parameter L1 and a preset second brightness enhancement contrast parameter L2, and performs image enhancement processing on the video frame according to the comparison result, wherein,
under the condition of first brightness contrast, the third operation unit adjusts the contrast of the video frame to a first contrast value Le1 according to a first contrast adjustment parameter L1, and sets Le1= L + L1;
under a second brightness contrast condition, the third operation unit adjusts the contrast of the video frame to a second contrast value Le2 according to a second contrast adjustment parameter L2, and sets Le2= L + L2;
under a third brightness contrast condition, the third arithmetic unit adjusts the contrast of the video frame to a third contrast value Le3 according to a third contrast adjustment parameter L3, and sets Le3= L + L3
The first brightness contrast condition is that L is more than or equal to L2, the second brightness contrast condition is that L1 is more than or equal to L and less than L2, the third brightness contrast condition is that L is less than L1, L2 is more than L1 > -delta L0, -100 < L1 < L2 < L3 < 100, le1 < Le2 < Le3 < 30.
Specifically, in order to meet the requirement of fast data processing, only three brightness adjustment value parameters are set when the brightness of an image is adjusted, and corresponding to three adjusted gears, in this embodiment, only a video frame with dark brightness is enhanced, the image contour is clearer by adjusting the contrast, and the related technology of calculating the contrast to be adjusted in real time through the brightness is mature, but if each video frame is enhanced through the above process, a large load is caused on data processing due to the huge data amount, so the invention determines three brightness intervals in advance, extracts three median brightnesses corresponding to the three brightness intervals, determines the optimal adjustment quantity when the contrast is adjusted based on the three median brightnesses, and takes the determined optimal adjustment quantity as three contrast adjustment parameters, for example, L1 takes 50, L2 takes 100, and forms three intervals [0,50] [50,100] [100,255] with the corresponding three median brightnesses of 25, 75, 178, and correspondingly obtains a first brightness adjustment parameter 1, a second brightness adjustment parameter of 15, a third brightness of 40L 2, and a third brightness adjustment parameter of 70L 3.
Specifically, in the invention, the data processing module performs image enhancement on the monitoring video segment with a third image complex condition and then analyzes the monitoring video segment with a first analysis interval, the third image complex condition is specific to the condition that the brightness of the monitoring video segment is low, in this condition, the image enhancement is performed on the video frame in the monitoring video segment, the image enhancement comprises the adjustment of the contrast of the image, the identification rate of the character information is further improved, and then the character information in the video frame is analyzed with the first analysis interval, so that the omission of key information in the video frame is avoided, the reliability of the system is improved, and the effect of safe hotel management is ensured. Particularly, still including patrolling and examining the module, it includes patrols and examines the robot and patrols and examines data arithmetic unit to patrol and examine the data arithmetic unit and be used for obtaining each the control dead angle of security protection camera to confirm the dead angle position, it controls to patrol and examine data arithmetic unit every preset time interval patrol and examine the robot and remove to each dead angle position and patrol and examine to obtain the surveillance video of dead angle position.
Specifically, the data acquisition module is further connected with an external display, so that the external display displays corresponding monitoring video contents.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
Claims (10)
1. A hotel management system based on the Internet of things is characterized by comprising:
the system comprises a data acquisition module, a monitoring module and a monitoring module, wherein the data acquisition module comprises a plurality of security cameras arranged in a hotel to acquire a monitoring video;
the data storage module is connected with the data acquisition module and used for storing the monitoring video acquired by the data acquisition module;
the data distribution module is connected with the data storage module and is used for dividing a monitoring video into a plurality of monitoring video segments and analyzing and acquiring the image complex condition of the monitoring video segments based on the image characteristics of each monitoring video segment;
a data processing module including a first arithmetic unit, a second arithmetic unit and a third arithmetic unit connected to each other,
the first operation unit is connected with the data storage module and the data distribution module and is used for acquiring a monitoring video segment of a first image complex condition and analyzing video frames in the monitoring video segment at a first analysis interval so as to analyze character information in the video frames;
the second operation unit is connected with the data storage module and the data distribution module and used for acquiring a monitoring video segment of a second image in a complex state, analyzing video frames in the monitoring video segment at a second analysis interval to analyze figure information in the video frames, calibrating a plurality of sub-monitoring video segments before analysis by the second operation unit, and adjusting the second analysis interval when analyzing the video frames of the calibrated sub-monitoring video segments;
the third operation unit is connected with the data storage module and the data distribution module to acquire a monitoring video segment of a third image in a complex state, and analyzes a video frame in the monitoring video segment at a first analysis interval after performing image enhancement processing on the video frame to analyze character information in the video frame, wherein the image enhancement processing comprises adjusting the contrast of the video frame according to the brightness value of the video frame;
wherein the second resolution interval is greater than the first resolution interval.
2. The Internet of things-based hotel management system according to claim 1, wherein the data distribution module obtains image features of a monitored video segment, the image features including the number Nr of person outlines, the number Nw of object outlines and a brightness value L of each video frame in the monitored video segment, calculates an image feature parameter P according to formula (1), calculates an average brightness value DeltaL according to formula (2),
in the formula (1), the first and second groups,
represents the number of the person profile in the ith video frame in the monitoring video segment, and/or is selected>
Representing the number of object outlines in the ith video frame in the monitoring video segment, and n representing the number of video frames in the monitoring video segment;
in formula (2), li represents the luminance value of the ith video frame in the monitoring video segment.
3. The Internet of things-based hotel management system according to claim 2, wherein the data distribution module compares the image characteristic parameter P with a preset first image characteristic contrast threshold P1 and compares the average brightness value Δ L with a preset brightness contrast threshold Δ L0, and determines the image complexity of the monitoring video segment according to the comparison result, wherein,
under the first comparison result, the data distribution module judges that the monitoring video segment is in a first image complex state;
under the second comparison result, the data distribution module judges that the monitoring video segment is in a second image complex state;
under a third comparison result, the data distribution module judges that the monitoring video segment is in a third image complex state;
wherein the first comparison result is that P is more than or equal to P1 and delta L is more than or equal to delta L0, the second comparison result is that P is less than P1 and delta L is more than or equal to delta L0, and the third comparison result is that delta L is less than delta L0.
4. The hotel management system based on the internet of things of claim 3, wherein the second operation unit obtains the number Nr of the outlines of the people and the number Nw of the outlines of the objects in each video frame of the sub-monitoring video segment, calculates an image characteristic parameter P corresponding to the sub-monitoring video segment according to a formula (1), and compares the image characteristic parameter P with a preset second image characteristic comparison threshold P2 to determine whether to calibrate the sub-monitoring video segment, wherein,
under the comparison result of preset parameters, the second operation unit judges that the sub monitoring video segment needs to be calibrated;
and the preset parameter comparison result is that P is less than P2, and P2 is less than P1.
5. The hotel management system according to claim 4, wherein the second computing unit compares the image characteristic parameter P corresponding to the calibrated sub-monitoring video segment with a preset third image characteristic comparison threshold P3 and a preset fourth image characteristic comparison threshold P4, determines an adjustment mode when adjusting the second resolution interval according to the comparison result, and analyzes the calibrated sub-monitoring video segment with the adjusted second resolution interval, wherein,
the first analysis interval adjustment mode is that the second operation unit adjusts the second analysis interval to a first analysis interval adjustment value T1 according to a preset first analysis interval adjustment parameter T1;
the second analysis interval adjustment mode is that the second operation unit adjusts the second analysis interval to a second analysis interval adjustment value T2 according to a preset second analysis interval adjustment parameter T2;
the third analysis interval adjustment mode is that the second operation unit adjusts the second analysis interval to a third analysis interval adjustment value T3 according to a preset third analysis interval adjustment parameter T3;
the first analysis interval adjusting mode needs to satisfy that P is more than or equal to P4, the second analysis interval adjusting mode needs to satisfy that P3 is more than or equal to P and P4 is less than or equal to P, the third analysis interval adjusting mode needs to satisfy that P is less than P3, P3 is less than P4 and P2, and t1 is less than t2 and t3.
6. The Internet of things-based hotel management system of claim 5, wherein the first, second and third computing units comprise a first computing unit and a second computing unit, wherein the first, second and third computing units are configured to analyze the personal information in the video frame,
acquiring face information of a figure outline in a video frame, matching the face information with data in a preset registered face information database to judge whether unregistered persons exist or not, wherein,
if the registered face information database has data matched with the face information, the first operation unit, the second operation unit and the third operation unit obtain a first analysis result;
if no data in the registered face information database is matched with the face information, the first operation unit, the second operation unit and the third operation unit obtain a second analysis result,
the first analysis result indicates that the face information is registered, and the second analysis result indicates that the face information is not registered.
7. The Internet of things-based hospitality management system of claim 6, wherein the first arithmetic unit is further configured to determine whether video frames of the first resolution interval need to be extracted for analysis,
under a first analysis condition, the first arithmetic unit judges that video frames in a first analysis interval need to be extracted for analysis;
the first analysis condition is that the first operation unit continuously obtains a preset number of second analysis results.
8. The Internet of things-based hotel management system of claim 7, wherein the third operation unit compares a brightness value L of a video frame with a preset first brightness enhancement contrast parameter L1 and a preset second brightness enhancement contrast parameter L2, and performs image enhancement processing on the video frame according to the comparison result, wherein,
under the condition of first brightness contrast, the third operation unit adjusts the contrast of the video frame to a first contrast value Le1 according to a first contrast adjustment parameter l1;
under the condition of second brightness contrast, the third operation unit adjusts the contrast of the video frame to a second contrast value Le2 according to a second contrast adjustment parameter l2;
under a third brightness contrast condition, the third operation unit adjusts the contrast of the video frame to a third contrast value Le3 according to a third contrast adjustment parameter l 3;
the first brightness contrast condition is that L is larger than or equal to L2, the second brightness contrast condition is that L1 is larger than or equal to L and smaller than L2, and the third brightness contrast condition is that L is smaller than L1, L2 is larger than L1 and larger than Delta L0, L1 is smaller than L2 and smaller than L3, and Le1 is smaller than Le2 and smaller than Le3.
9. The hotel management system based on the internet of things of claim 1, further comprising an inspection module, wherein the inspection module comprises an inspection robot and an inspection data operation unit, the inspection data operation unit is used for acquiring monitoring dead angles of the security cameras and determining dead angle positions, and the inspection data operation unit controls the inspection robot to move to each dead angle position for inspection at preset time intervals so as to acquire monitoring videos of the dead angle positions.
10. The internet of things-based hotel management system of claim 1, wherein the data acquisition module is further connected with an external display to enable the external display to display corresponding monitoring video content.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310181202.XA CN115861905B (en) | 2023-03-01 | 2023-03-01 | Hotel management system based on internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310181202.XA CN115861905B (en) | 2023-03-01 | 2023-03-01 | Hotel management system based on internet of things |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115861905A true CN115861905A (en) | 2023-03-28 |
| CN115861905B CN115861905B (en) | 2023-06-16 |
Family
ID=85659421
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310181202.XA Active CN115861905B (en) | 2023-03-01 | 2023-03-01 | Hotel management system based on internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115861905B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117132936A (en) * | 2023-08-31 | 2023-11-28 | 北京中电拓方科技股份有限公司 | Data carding and data access system of coal plate self-building system |
| CN118396809A (en) * | 2024-02-06 | 2024-07-26 | 广州地铁集团有限公司 | Carbon emission analysis system for rail transit construction |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10053683A1 (en) * | 2000-10-28 | 2002-05-08 | Alcatel Sa | Image monitoring |
| JP2018093324A (en) * | 2016-12-01 | 2018-06-14 | 株式会社日立製作所 | Video surveillance system, video surveillance system control method, and video surveillance apparatus |
| US20180197576A1 (en) * | 2015-06-17 | 2018-07-12 | Beijing Kingsoft Internet Security Software Co., Ltd. | Method and device for processing video |
| CN110446061A (en) * | 2019-07-04 | 2019-11-12 | 深圳壹账通智能科技有限公司 | Video data acquisition methods, device, computer equipment and storage medium |
| CN112381859A (en) * | 2020-11-20 | 2021-02-19 | 公安部第三研究所 | System, method, device, processor and storage medium for realizing intelligent analysis, identification and processing for video image data |
| CN112699270A (en) * | 2020-12-31 | 2021-04-23 | 招明香 | Monitoring security data transmission and storage method and system based on cloud computing, electronic equipment and computer storage medium |
| CN115550710A (en) * | 2022-08-30 | 2022-12-30 | 海南视联通信技术有限公司 | Data processing method and device, terminal equipment and storage medium |
| CN115687051A (en) * | 2022-12-30 | 2023-02-03 | 西安纽扣软件科技有限公司 | Log analysis system based on point position analysis |
-
2023
- 2023-03-01 CN CN202310181202.XA patent/CN115861905B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10053683A1 (en) * | 2000-10-28 | 2002-05-08 | Alcatel Sa | Image monitoring |
| US20180197576A1 (en) * | 2015-06-17 | 2018-07-12 | Beijing Kingsoft Internet Security Software Co., Ltd. | Method and device for processing video |
| JP2018093324A (en) * | 2016-12-01 | 2018-06-14 | 株式会社日立製作所 | Video surveillance system, video surveillance system control method, and video surveillance apparatus |
| CN110446061A (en) * | 2019-07-04 | 2019-11-12 | 深圳壹账通智能科技有限公司 | Video data acquisition methods, device, computer equipment and storage medium |
| CN112381859A (en) * | 2020-11-20 | 2021-02-19 | 公安部第三研究所 | System, method, device, processor and storage medium for realizing intelligent analysis, identification and processing for video image data |
| CN112699270A (en) * | 2020-12-31 | 2021-04-23 | 招明香 | Monitoring security data transmission and storage method and system based on cloud computing, electronic equipment and computer storage medium |
| CN115550710A (en) * | 2022-08-30 | 2022-12-30 | 海南视联通信技术有限公司 | Data processing method and device, terminal equipment and storage medium |
| CN115687051A (en) * | 2022-12-30 | 2023-02-03 | 西安纽扣软件科技有限公司 | Log analysis system based on point position analysis |
Non-Patent Citations (2)
| Title |
|---|
| TOSHIE MISU等: "Real-time implementation of UHDTV video coding system with super-resolution techniques", 2013 PICTURE CODING SYMPOSIUM (PCS) * |
| 王晨 等: "IP化超高清视频解析和监测系统设计及实现", 中国传媒大学学报(自然科学版) * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117132936A (en) * | 2023-08-31 | 2023-11-28 | 北京中电拓方科技股份有限公司 | Data carding and data access system of coal plate self-building system |
| CN117132936B (en) * | 2023-08-31 | 2024-07-30 | 北京中电拓方科技股份有限公司 | Data carding and data access system of coal plate self-building system |
| CN118396809A (en) * | 2024-02-06 | 2024-07-26 | 广州地铁集团有限公司 | Carbon emission analysis system for rail transit construction |
| CN118396809B (en) * | 2024-02-06 | 2024-12-10 | 广州地铁集团有限公司 | A carbon emission analysis system for rail transit construction |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115861905B (en) | 2023-06-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115861905A (en) | Hotel management system based on Internet of things | |
| KR101215948B1 (en) | Image information masking method of monitoring system based on face recognition and body information | |
| CN106027978A (en) | Video monitoring abnormal behavior system and method for smart home old people care | |
| CN106412501B (en) | A kind of the construction safety behavior intelligent monitor system and its monitoring method of video | |
| CN109484935A (en) | A kind of lift car monitoring method, apparatus and system | |
| CN106600888B (en) | Automatic forest fire detection method and system | |
| KR101245057B1 (en) | Method and apparatus for sensing a fire | |
| CN108364374A (en) | Face access control device based on deep learning and method | |
| CN112487891B (en) | Visual intelligent dynamic identification model construction method applied to electric power operation site | |
| CN112560745B (en) | Method for discriminating personnel on electric power operation site and related device | |
| KR101092472B1 (en) | Video indexing system using surveillance camera and indexing method | |
| CN107426533A (en) | A kind of video monitoring image recognition system based on video-encryption compression and image identification | |
| CN111488803A (en) | Airport target behavior understanding system integrating target detection and target tracking | |
| CN111695512B (en) | Unattended cultural relic monitoring method and unattended cultural relic monitoring device | |
| CN116343419B (en) | Intelligent video monitoring alarm management system | |
| CN111191507A (en) | Safety early warning analysis method and system for smart community | |
| CN112183219A (en) | Public safety video monitoring method and system based on face recognition | |
| CN113793366B (en) | Image processing method, device, equipment and storage medium | |
| CN205184784U (en) | Machine people goes on patrol | |
| CN114120597A (en) | Public place epidemic situation normalized prevention and control system based on machine vision | |
| CN111400415B (en) | Personnel management method and related device | |
| CN117372968A (en) | Electric vehicle home-entering monitoring method based on Internet of things | |
| CN115346170B (en) | Intelligent monitoring method and device for gas facility area | |
| CN116912758A (en) | A target image recognition method and device for safety hazard monitoring | |
| CN112804492B (en) | Communication prompting method and device for electronic peepholes |
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 | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230525 Address after: Room 207-208, Building 2, No. 608 Shengxia Road, China (Shanghai) Pilot Free Trade Zone, Pudong New Area, Shanghai, 201201 Applicant after: LUMOUS INTELLIGENT TECHNOLOGY (SHANGHAI) Co.,Ltd. Address before: Room A288, 2nd Floor, No. 88 Xuzhou Road, Shinan District, Qingdao, Shandong 266000 Applicant before: Qingdao Jingyou Elephant Technology Co.,Ltd. |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |