CN115689821A - Students' dormitory information acquisition management system - Google Patents
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- CN115689821A CN115689821A CN202211228979.9A CN202211228979A CN115689821A CN 115689821 A CN115689821 A CN 115689821A CN 202211228979 A CN202211228979 A CN 202211228979A CN 115689821 A CN115689821 A CN 115689821A
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Abstract
The invention discloses a student dormitory information acquisition management system, relates to the technical field of student dormitory management, and solves the technical problem that the safety of students cannot be guaranteed in all directions because the illegal activity tracks of the students cannot be effectively identified when the students are managed in the dormitory in the prior art; according to the invention, basic management information of a dormitory is acquired through a data sensor, and the image data in the basic management information is combined with dormitory management requirements to acquire violation tracks of students; whether the students in the dormitory have violation behaviors or not is judged by combining the energy consumption data, and early warning control is carried out, so that the students are protected in an all-round way; according to the invention, the activity track of the monitored object is obtained through the image data, and regular work and rest of the monitored object can be ensured based on the activity track; meanwhile, whether energy consumption abnormity exists or not is analyzed according to the energy consumption change curve of the associated object, and then whether class escaping behaviors and behaviors of illegally using electric appliances exist in the monitored object or not can be judged, and student dormitory information can be comprehensively mastered.
Description
Technical Field
The invention belongs to the field of student dormitory management, relates to a student dormitory information acquisition management technology, and particularly relates to a student dormitory information acquisition management system.
Background
With the rapid development of embedded technology, communication technology and network technology, the functions of intelligent control systems are increasing, and control objects and control occasions are expanding continuously. However, the intelligent control system is not widely applied to dormitory management of an intelligent campus, so that the current efficient dormitory management system is aged and the management efficiency is low.
The prior art (patent application with publication number CN 105787835A) discloses an intelligent campus dormitory management system, which collects data in a student dormitory by arranging various sensors in the dormitory, records and analyzes the data to monitor the student dormitory, avoids resource waste and provides security. In the prior art, when students are managed in dormitories, supervision is mainly carried out from the perspective of objects, supervision is not realized from the perspective of people, and illegal activity tracks of the students cannot be effectively identified, so that the safety of the students cannot be guaranteed in all directions; therefore, a student dormitory information collection management system is needed.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art; therefore, the invention provides a student dormitory information acquisition management system, which is used for solving the technical problems that in the prior art, when student dormitory management is carried out, supervision is mainly carried out from the perspective of objects, supervision is not carried out from the perspective of people, and illegal activity tracks of students cannot be effectively identified, so that the safety of the students cannot be guaranteed in all directions.
In order to achieve the above object, a first aspect of the present invention provides a student dormitory information collection management system, which includes a central analysis module, and a plurality of edge analysis modules and an intelligent terminal connected thereto; the edge analysis module is connected with the data sensors of a plurality of types;
an edge analysis module: acquiring basic management information of the associated object through a data sensor; wherein the basic management information comprises image data and energy consumption data; and
the basic management information is sent to a central analysis module after being subjected to data processing;
a pivot analysis module: performing data interaction with a database to obtain dormitory management requirements and student course information; the dormitory management requirements comprise student work and rest time and electric appliance use requirements; and
analyzing image data based on the work and rest nodes determined by the dormitory management requirements; and judging whether the energy consumption data is abnormal or not by combining the student course information and the electric appliance use requirements, if so, controlling early warning, and otherwise, not processing.
Preferably, the central analysis module is respectively in communication and/or electrical connection with the edge analysis modules and the intelligent terminal; the intelligent terminal comprises a mobile phone and a computer and is used for displaying basic management information and carrying out early warning;
the edge analysis module is associated with at least one associated object, and data acquisition and electrical control are carried out on the associated object through the data sensor; wherein the associated object comprises a dormitory or a building.
Preferably, after the edge analysis module is matched with the associated object, the connection between the data sensor in the corresponding associated object and the edge analysis module is established; and
the data sensor comprises a smoke sensor, a temperature sensor, a camera and an energy consumption sensor; the camera is arranged outside the dormitory and is at least connected with one edge analysis module.
Preferably, the central hub analysis module analyzes the image data based on the work and rest node determined by the dormitory management requirement, and determines the suspected object, including:
extracting the work and rest time of students in the dormitory management requirement, and determining the corresponding work and rest nodes according to the work and rest time of the students; wherein, the working and rest time of students in each grade or profession is different;
determining a track sequence of each monitored object in unit time based on the image data; wherein, the unit time includes one day or one week, and the track sequence indicates whether the monitoring object is located in the corresponding associated object;
determining abnormal monitoring objects based on the work and rest time and a plurality of track sequences, and marking the abnormal monitoring objects as suspicious objects; carrying out early warning aiming at a suspected object; wherein, the monitoring object is specifically a student.
Preferably, the central analysis module analyzes the energy consumption data, and determines whether energy consumption is abnormal according to an analysis result, including:
establishing an energy consumption change curve in unit time, and acquiring energy consumption of each time period based on the energy consumption change curve; wherein, each time period is obtained by evenly dividing unit time;
comparing the energy consumption of each time period with a corresponding energy consumption threshold; when the energy consumption exceeds the energy consumption threshold, judging that the energy consumption of the associated object is abnormal; wherein the energy consumption threshold is set empirically.
Preferably, after determining the energy consumption abnormality, determining whether a monitoring object exists in the associated objects based on the student course information and the track sequence includes:
acquiring a track sequence corresponding to the associated object, and judging whether a monitoring object exists in the associated object based on the track sequence; matching a monitored object based on student course information; if not, identifying the electric appliance;
matching in student course information based on the identified monitoring object, and identifying the electric appliance when the monitoring object has no course; otherwise, early warning is carried out.
Preferably, the hub analysis module performs appliance identification when a monitoring object exists in the related objects, and includes:
matching the energy consumption change curve in a curve database, identifying the running electric appliance in the associated object, and marking the electric appliance to be checked; wherein, the curve database comprises the energy consumption change curve of each electric appliance;
when the electric appliance to be checked meets the use requirement of the electric appliance, no treatment is carried out; otherwise, judging that the energy consumption data of the associated object is abnormal, and controlling the starting and stopping of each electric appliance of the associated object.
Preferably, the central analysis module performs appliance identification when no monitoring object exists in the associated objects, including:
identifying the electric appliance based on the energy consumption change curve, and marking the electric appliance to be checked;
when the electrical appliance to be checked meets the use requirements of the electrical appliance and belongs to dormitory basic electrical appliances, the electrical appliance is not processed; otherwise, controlling the starting and stopping of the electric appliance to be checked; wherein dormitory base appliances are set according to experience.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, basic management information of a dormitory is acquired through various types of data sensors, and the violation tracks of students can be acquired by combining image data in the basic management information with dormitory management requirements; and judging whether the students' dormitory has violation behaviors by combining the energy consumption data, and performing early warning control to further realize the omnibearing protection of the students.
2. According to the invention, the activity track of the monitored object is obtained through the image data, and regular work and rest of the monitored object can be ensured based on the activity track; meanwhile, whether energy consumption is abnormal or not is analyzed according to the energy consumption change curve of the associated object, and then whether the monitored object has a course escaping behavior and a behavior of illegally using electric appliances or not can be judged, and students' dormitory information can be comprehensively mastered.
Drawings
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 embodiments or the prior art descriptions will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic diagram of the working steps of the present invention;
fig. 2 is a schematic diagram of the system of the present invention.
Detailed Description
The technical solutions of the present invention will be described below clearly and completely in conjunction with the embodiments, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
Referring to fig. 1-2, in a first aspect of the present invention, a system for collecting and managing student dormitory information is provided, including a central analysis module, and a plurality of edge analysis modules and an intelligent terminal connected to the central analysis module; and the edge analysis module is connected with a plurality of types of data sensors:
an edge analysis module: acquiring basic management information of the associated object through a data sensor; wherein the basic management information includes image data and energy consumption data; and sending the basic management information to a central analysis module after data processing;
a central analysis module: performing data interaction with a database to obtain dormitory management requirements and student course information; analyzing the image data based on the work and rest nodes determined by the dormitory management requirements; and judging whether the energy consumption data is abnormal or not by combining the student course information and the electric appliance use requirements, if so, controlling early warning, and otherwise, not processing.
The essence of recording a student dormitory management system in the prior art is the technology transplanted from an intelligent security system, and the main realization function is to realize the safety monitoring of the student dormitory and avoid the damage of fire and the like to students. However, the student dormitory management also needs to be managed in combination with the daily behaviors of students, such as whether the activity track violates rules or whether the students escape from classes, and the like, so that the health and the safety of the students can be ensured in the whole range.
According to the invention, the basic management information of the dormitory is acquired through various types of data sensors, and the violation tracks of students can be acquired by combining the image data with the dormitory management requirements; and judging whether the students' dormitory has violation behaviors by combining the energy consumption data, and performing early warning control to further realize the omnibearing protection of the students.
Dormitory management requirements include student work and rest time and appliance usage requirements. The regular work and rest time of students in dormitories is required, wherein the work and rest time of students mainly comprises the time of turning off lights, proper disconnection of a network and the like; the use requirements of the electric appliances mainly comprise that the electric appliances are available, the electric appliances are unavailable and the like, so that potential safety hazards caused by the fact that students use illegal electric appliances in dormitories are avoided.
The center analysis module is respectively communicated and/or electrically connected with the edge analysis modules and the intelligent terminal; the intelligent terminal comprises a mobile phone and a computer and is used for displaying basic management information and carrying out early warning; the edge analysis module is associated with at least one associated object, and data acquisition and electrical control are carried out on the associated object through a data sensor; wherein the associated object comprises a dormitory or a building.
The central analysis module is mainly responsible for processing various types of data, acquiring data from a database or a plurality of edge analysis modules and performing data interaction with the intelligent terminal; the edge analysis module collects various data of the associated object through the data sensor and preprocesses the data at the same time. Each edge analysis module is associated with at least one associated object, e.g., when the associated object is a dormitory, then the edge analysis module may be responsible for one dormitory or for multiple dormitories.
After the edge analysis module is matched with the associated object, establishing the connection between the data sensor in the corresponding associated object and the edge analysis module; the data sensor comprises a smoke sensor, a temperature sensor, a camera and an energy consumption sensor; the camera sets up outside the dormitory, and same camera is connected with an edge analysis module at least.
Data acquisition by all data sensors in the present application is performed without constituting a privacy violation for anyone. If the camera is arranged on a corridor outside the dormitory, the allowed image data is collected when students go in and out of the dormitory, and the images are matched in the access control database to determine identities. It should be understood that when the edge analysis module is responsible for one dormitory, the camera may cover several dormitories, and thus the camera may be connected to several edge analysis modules, and the other data sensors may be the same.
The method for determining the suspect object by the pivot analysis module based on the work and rest node analysis image data determined by the dormitory management requirement in the application of the invention comprises the following steps:
extracting the work and rest time of students in the dormitory management requirement, and determining corresponding work and rest nodes according to the work and rest time of the students; determining a track sequence of each monitored object in unit time based on the image data; determining an abnormal monitoring object based on the work and rest time and a plurality of track sequences, and marking the abnormal monitoring object as a suspect object; and carrying out early warning on the suspected object.
The rule of guaranteeing work and rest is one of the aspects of protecting the safety of students, and not only can guarantee that the students have good work and rest habits, but also can avoid not falling home at night. The student work and rest time is extracted from dormitory management requirements, the light-off time is used as a work and rest node, and a track sequence corresponding to the monitoring object is counted at the work and rest node, namely records of going in and out of the dormitory in the day. It should be noted that, the students in different grades or in different professional periods may have different work and rest times, so that the corresponding work and rest nodes in each dormitory may be different.
The unit time includes one day or one week. The track sequence indicates whether the monitoring object is located in the corresponding associated object, if a certain monitoring object goes out of a dormitory once in a day and returns to the dormitory before the work and rest node, the corresponding track sequence is [1,0],1 indicates the dormitory, and 0 indicates the dormitory; when a certain monitoring object goes out of the dormitory building, goes back to the dormitory, goes out of the dormitory and goes back to the dormitory in sequence in one day, the corresponding track sequence is [2,0,1,0], and 2 represents the dormitory building.
When the work and rest node arrives or before the work and rest node arrives, the central hub analysis module calls track sequences of all the monitored objects, when the last number in the track sequences is 0, the monitored objects are shown not to return to the dormitory, the monitored objects are suspected objects, early warning can be automatically sent to the suspected objects through the central hub analysis module, and early warning can be sent to dormitory management personnel and corresponding tutors.
Energy consumption analysis to the students 'dormitory is another aspect of guaranteeing the students' safety. The method for analyzing the energy consumption data by the central pivot analysis module and judging whether the energy consumption is abnormal according to the analysis result comprises the following steps:
establishing an energy consumption change curve in unit time, and acquiring the energy consumption of each time period based on the energy consumption change curve; comparing the energy consumption of each time period with a corresponding energy consumption threshold; when the energy consumption exceeds the energy consumption threshold, judging that the energy consumption of the associated object is abnormal; wherein the energy consumption threshold is set empirically.
Each time period is obtained by evenly dividing the unit time, and if one unit time is one day, each time period may be one hour. And calculating the energy consumption of each time period, and comparing the energy consumption with the corresponding energy consumption threshold value to judge whether the energy consumption is abnormal. It should be noted that the energy consumption threshold may be understood as the lowest energy consumption of the associated object in the time period, that is, the energy consumption is not particularly large, so that the abnormal energy consumption data indicates that there are other electrical appliances working.
By way of example: if routers, computers and the like which can constantly work in the associated object are assumed, the energy consumption of the electrical appliances in the time period is the energy consumption threshold, and when the energy consumption exceeds the energy consumption threshold, it is indicated that other electrical appliances work besides the basic electrical appliances, and at this time, it is necessary to further analyze which electrical appliances are working and whether the electrical appliances should work.
After the abnormal energy consumption is determined, whether the monitoring object exists in the associated object is judged based on the student course information and the track sequence, wherein the method comprises the following steps of:
acquiring a track sequence corresponding to the associated object, and judging whether a monitoring object exists in the associated object based on the track sequence; matching a monitored object based on student course information; if not, identifying the electric appliance; matching in student course information based on the identified monitoring object, and identifying the electric appliance when the monitoring object has no course; otherwise, early warning is carried out.
The energy consumption abnormality is divided into two cases: one is that the monitoring object can cause abnormal energy consumption when other equipment such as an air conditioner and the like is started in a dormitory; the other is to monitor that the subject is not in the dormitory, such as forgetting to turn off the air conditioner. On the basis of abnormal energy consumption, the first step of further analysis is to judge whether a monitoring object exists in a related object (dormitory), and if the monitoring object does not exist, the electric appliance identification is carried out according to an energy consumption change curve; and if the monitoring object exists, judging whether the behavior of escaping from the lesson and the behavior of using the illegal electric appliance exist or not by combining the course information of the student.
When the monitoring object is determined to exist, the identity of the monitoring object is identified, and whether course escaping behavior exists is judged by combining the course information of the student; and if the course escaping behavior exists, giving an early warning to the tutor of the teacher, and if the course escaping behavior does not exist, identifying whether the illegal electric appliance is used or not.
The central analysis module identifies the electric appliance when the monitoring object exists in the associated objects, and comprises the following steps:
matching the energy consumption change curve in a curve database, identifying the running electric appliance in the associated object, and marking as an electric appliance to be checked; when the electric appliance to be checked meets the use requirement of the electric appliance, no treatment is carried out; otherwise, judging that the energy consumption data of the associated object is abnormal, and controlling the starting and stopping of each electric appliance of the associated object.
The curve database comprises energy consumption change curves of all the electric appliances. When the electrical appliance is identified according to the energy consumption change curve, the curve can be simply decomposed to determine the electrical appliance, and the energy consumption change curve can be analyzed through an artificial intelligence model to determine the electrical appliance. It is noted that the energy consumption profile may also be replaced by a power profile.
The central analysis module identifies the electric appliance when no monitoring object exists in the associated objects, and comprises the following steps:
identifying the electric appliance based on the energy consumption change curve, and marking the electric appliance to be checked; when the electrical appliance to be checked meets the use requirements of the electrical appliance and belongs to dormitory basic electrical appliances, the electrical appliance is not processed; otherwise, controlling the starting and stopping of the electric appliance to be checked; wherein dormitory base appliances are set according to experience.
The working principle of the invention is as follows:
the edge analysis module collects basic management information of the associated object through the data sensor, processes the data of the basic management information and sends the basic management information to the central analysis module.
The central pivot analysis module analyzes the image data based on the work and rest nodes determined by the dormitory management requirements; and judging whether the energy consumption data is abnormal or not by combining the student course information and the use requirements of the electric appliances, if so, controlling early warning, and otherwise, not processing.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the present invention.
Claims (8)
1. The student dormitory information acquisition management system comprises a central analysis module, a plurality of edge analysis modules and an intelligent terminal, wherein the edge analysis modules and the intelligent terminal are connected with the central analysis module; and the edge analysis module is connected with a plurality of types of data sensors, and is characterized in that:
an edge analysis module: acquiring basic management information of the associated object through a data sensor; wherein the basic management information includes image data and energy consumption data; and
the basic management information is sent to a central analysis module after being subjected to data processing;
a central analysis module: performing data interaction with a database to obtain dormitory management requirements and student course information; the dormitory management requirements comprise student work and rest time and electric appliance use requirements; and
analyzing image data based on the work and rest nodes determined by the dormitory management requirements; and judging whether the energy consumption data is abnormal or not by combining the student course information and the electric appliance use requirements, if so, controlling early warning, and otherwise, not processing.
2. The students' dormitory information collection management system according to claim 1, wherein the center analysis module is respectively in communication and/or electrical connection with a plurality of edge analysis modules and an intelligent terminal; the intelligent terminal comprises a mobile phone and a computer and is used for displaying basic management information and carrying out early warning;
the edge analysis module is associated with at least one associated object, and data acquisition and electrical control are carried out on the associated object through the data sensor; wherein the associated object comprises a dormitory or a building.
3. The student dormitory information collection management system according to claim 2, wherein after the edge analysis module is matched to an associated object, a connection between the data sensor in the corresponding associated object and the edge analysis module is established; and
the data sensor comprises a smoke sensor, a temperature sensor, a camera and an energy consumption sensor; the camera is arranged outside the dormitory and is at least connected with one edge analysis module.
4. The student dormitory information collection management system according to claim 1, wherein the hub analysis module analyzes the image data based on the work and rest node determined by the dormitory management requirement, and determines a suspected object, and includes:
extracting the work and rest time of the students in the dormitory management requirement, and determining the corresponding work and rest nodes according to the work and rest time of the students; wherein, the working and rest time of students in each grade or profession is different;
determining a track sequence of each monitored object in unit time based on the image data; wherein, the unit time includes one day or one week, and the track sequence indicates whether the monitoring object is located in the corresponding associated object;
determining an abnormal monitoring object based on the work and rest time and a plurality of track sequences, and marking the abnormal monitoring object as a suspect object; carrying out early warning aiming at a suspected object; wherein, the monitoring object is specifically a student.
5. The student dormitory information collection management system according to claim 4, wherein the central analysis module analyzes the energy consumption data and determines whether energy consumption is abnormal according to an analysis result, and the central analysis module comprises:
establishing an energy consumption change curve in unit time, and acquiring the energy consumption of each time period based on the energy consumption change curve; wherein, each time period is obtained by evenly dividing unit time;
comparing the energy consumption of each time period with a corresponding energy consumption threshold; when the energy consumption exceeds the energy consumption threshold, judging that the energy consumption of the associated object is abnormal; wherein the energy consumption threshold is set empirically.
6. The student dormitory information collection management system according to claim 5, wherein after determining the energy consumption abnormality, determining whether a monitoring object exists in the associated objects based on the student course information and the trajectory sequence comprises:
acquiring a track sequence corresponding to a related object, and judging whether a monitoring object exists in the related object based on the track sequence; matching a monitored object based on student course information; if not, identifying the electric appliance;
matching in student course information based on the identified monitoring object, and identifying the electric appliance when the monitoring object has no course; otherwise, early warning is carried out.
7. The student dormitory information collection management system according to claim 6, wherein the hub analysis module performs appliance identification when a monitoring object is present in the associated objects, comprising:
matching the energy consumption change curve in a curve database, identifying the running electric appliance in the associated object, and marking the electric appliance to be checked; wherein, the curve database comprises the energy consumption change curve of each electric appliance;
when the electric appliance to be checked meets the use requirement of the electric appliance, no treatment is carried out; otherwise, judging that the energy consumption data of the associated object is abnormal, and controlling the starting and stopping of each electric appliance of the associated object.
8. The student dormitory information collection management system according to claim 6, wherein the hub analysis module performs appliance identification when the monitoring object is not present in the associated objects, comprising:
identifying the electric appliance based on the energy consumption change curve, and marking the electric appliance to be checked;
when the electric appliance to be verified meets the use requirements of the electric appliance and belongs to dormitory basic electric appliances, the electric appliance is not processed; otherwise, controlling the starting and stopping of the electric appliance to be checked; wherein dormitory base appliances are set according to experience.
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| CN202211228979.9A CN115689821A (en) | 2022-10-09 | 2022-10-09 | Students' dormitory information acquisition management system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117666449A (en) * | 2024-01-31 | 2024-03-08 | 四川水利职业技术学院 | Based on computer data acquisition analysis monitored control system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117666449A (en) * | 2024-01-31 | 2024-03-08 | 四川水利职业技术学院 | Based on computer data acquisition analysis monitored control system |
| CN117666449B (en) * | 2024-01-31 | 2024-04-12 | 四川水利职业技术学院 | Based on computer data acquisition analysis monitored control system |
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Application publication date: 20230203 |