CN112650335A - Intelligent energy consumption management and control system and method based on big data mining - Google Patents
Intelligent energy consumption management and control system and method based on big data mining Download PDFInfo
- Publication number
- CN112650335A CN112650335A CN202011508612.3A CN202011508612A CN112650335A CN 112650335 A CN112650335 A CN 112650335A CN 202011508612 A CN202011508612 A CN 202011508612A CN 112650335 A CN112650335 A CN 112650335A
- Authority
- CN
- China
- Prior art keywords
- information
- energy consumption
- management
- water supply
- big data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D27/00—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00
- G05D27/02—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00 characterised by the use of electric means
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses an energy consumption intelligent control system and method based on big data mining, which collects the temperature, sound, image and humidity information of each area; collecting the on-off state information of an ammeter loop, collecting pressure and flow data of a water supply loop, and detecting the state of a water supply pipeline; according to the received environmental impact parameter information and residence information, performing behavior model mining on the user, grasping and predicting the user behavior, and performing resource allocation of the corresponding space according to the prediction result; according to the resource allocation instruction, performing resource supply or interruption on the corresponding space to realize energy consumption management and control; and according to the predicted equipment operation condition, maintaining and eliminating potential faults, and realizing the operation and maintenance management of the public facilities of the building.
Description
Technical Field
The invention relates to an energy consumption intelligent management and control system and method based on big data mining.
Background
With the continuous development of various buildings, the buildings are larger and larger in scale, higher in level and higher in building standard.
For large buildings, there are many factors that affect the energy consumption of the building, such as the building type, the usage of each room, the story height of the room, the wall thickness, the room temperature, the room humidity, the density of the resident, the lighting time, the temperature and humidity of the shared space, the usage period of each resource, the energy consumption of the building or/and the heat consumption of the building, etc.
How to organically fuse or sequence the large number of influencing factors and how to comprehensively balance to obtain more preferable, economical and efficient energy consumption control is an important problem at present.
Meanwhile, how to effectively manage resources in the public space, such as lighting equipment, drinking equipment, a central air conditioner or fire extinguishing equipment, how to combine the energy consumption influence factors, scientifically distribute, update and maintain the resources in the public space is also an urgent problem to be solved.
Disclosure of Invention
The invention aims to solve the problems and provides an energy consumption intelligent control system and method based on big data mining.
The utility model provides an energy consumption intelligence management and control system based on big data mining which characterized by: the method comprises the following steps:
the environment influence parameter acquisition unit comprises corresponding sensors arranged in each area and is used for receiving acquired temperature, sound, image and humidity information;
the residential information acquisition unit comprises an electricity consumption information acquisition module for acquiring the on-off state information of an ammeter loop, a water supply information acquisition module for acquiring the pressure and flow data of a water supply loop and detecting the state of a water supply pipeline, which are arranged at each node, and a heating and ventilation information acquisition module for acquiring the working states of a central heating system and a central air-conditioning system;
the resource scheduling unit is configured to mine a behavior model of the user based on big data according to the received environment influence parameter information and the residence information, grasp and predict the user behavior, and allocate resources of corresponding spaces according to a prediction result;
the resource demand prediction module is configured to mine the logistics service demand of the building according to the received environment influence parameter information and the residence information, assist in predicting and distributing the logistics service demand in combination with user behaviors and distribution, and perform self-adaptive maintenance of the equipment and prediction of fault risks;
and the information interaction unit is configured to receive the resource allocation instruction, supply or interrupt resources to the corresponding space, realize the management and control of energy consumption, maintain and eliminate potential faults according to the predicted equipment operation condition, and realize the operation and maintenance management of the public facilities of the building.
Furthermore, the environmental impact parameter acquisition unit comprises a plurality of temperature sensors, humidity sensors, an image acquisition module, an infrared sensor, an ultraviolet sensor and a sound acquisition module which are arranged on each floor in the building.
Furthermore, the water supply information acquisition module comprises water supply overflow sensors arranged on the water supply main pipelines and sensors arranged on the water supply branch pipelines and used for acquiring the flow and pressure of the corresponding water supply branch pipelines.
Furthermore, the power utilization information acquisition module comprises an acquisition device for acquiring the loop information of the electric meter, so that the on-off state of the current electric power loop is acquired.
Furthermore, the environment influence parameter acquisition unit comprises a plurality of image acquisition modules, the image acquisition modules form a monitoring network, the pedestrian movement track can be recorded in an all-round manner, and the image acquisition modules are matched with each other to detect the human faces in different head postures.
Furthermore, the sensor or collector arranged in each area has a unique ID and an IP address, and collects the information of the environmental impact parameter collection unit of the area corresponding to the sensor or collector.
The invention also provides a method for intelligently controlling energy consumption based on big data mining, which comprises the following steps:
collecting temperature, sound, image and humidity information of each area;
collecting the on-off state information of an ammeter loop, collecting pressure and flow data of a water supply loop, and detecting the state of a water supply pipeline;
according to the received environmental impact parameter information and residence information, performing behavior model mining on the user, grasping and predicting the user behavior, and performing resource allocation of the corresponding space according to the prediction result;
according to the resource allocation instruction, performing resource supply or interruption on the corresponding space to realize energy consumption management and control; and according to the predicted equipment operation condition, maintaining and eliminating potential faults, and realizing the operation and maintenance management of the public facilities of the building.
As an alternative implementation mode, the environmental impact parameter information and the residence information are stored in the database, the uploaded data are recorded in advance, and distributed management is carried out on the data.
As an alternative embodiment, the maximum threshold value and the minimum threshold value of data of all the acquisition element parameters are configured in advance, when the received data exceed the set threshold value range, corresponding equipment alarming is carried out, and the position of the sensor is found through the ID information of the sensor.
As an alternative embodiment, the specific process of mining the behavior model of the user according to the received environmental impact parameter information and the residence information, and grasping and predicting the behavior of the user includes: determining the use habits of the corresponding users according to the received environmental influence parameter information and the residence information, depicting the specific behaviors of the users, including the electricity utilization condition, the water utilization condition and the body temperature of the corresponding users in each time period, analyzing and calculating, determining the most comfortable body temperature of the users, the peak period and the valley period of the electricity utilization and the water utilization, and adjusting the water and electricity consumption according to the determination result.
The resource consumption conditions of different buildings in one day can be obtained through the same data calculation, and through resource consumption comparison, the buildings with large use amount can be subjected to resource management and control, the electricity consumption and the water consumption can be controlled, and the like.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the intelligent control system, the state monitoring and intelligent control can be performed on public equipment and room equipment in a building based on a communication network and a terminal sensor, big data analysis is constructed, data such as user behaviors and environmental states are collected, the data are analyzed and resource allocation and management are assisted, and economic and efficient energy consumption management and control are realized;
2. the method comprises the steps of mining a public space use model of a building, performing space resource allocation based on the assistance of a user behavior model, displaying in a chart/3D mode, and outputting a reference allocation scheme;
3. the invention can carry out equipment operation and maintenance according to the characteristics of the excavated data, excavate the operation and maintenance conditions of the equipment, predict the possible failure risk of the equipment and prevent the occurrence of accidents.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application.
FIG. 1 is a diagram of a system architecture according to the present embodiment;
fig. 2 is a data processing flowchart provided in this embodiment.
The specific implementation mode is as follows:
the invention is further described with reference to the following figures and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
In the present invention, terms such as "upper", "lower", "left", "right", "front", "rear", "vertical", "horizontal", "side", "bottom", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only terms of relationships determined for convenience of describing structural relationships of the parts or elements of the present invention, and are not intended to refer to any parts or elements of the present invention, and are not to be construed as limiting the present invention.
In the present invention, terms such as "fixedly connected", "connected", and the like are to be understood in a broad sense, and mean either a fixed connection or an integrally connected or detachable connection; may be directly connected or indirectly connected through an intermediate. The specific meanings of the above terms in the present invention can be determined according to specific situations by persons skilled in the relevant scientific or technical field, and are not to be construed as limiting the present invention.
The details are described with the teaching dormitory building as the building to be managed as a specific embodiment.
Firstly, an energy consumption intelligent management and control system based on big data mining is provided, and the processing system has the following functions:
(1) human-computer interaction: interpersonal communication cost and threshold are reduced, corresponding management responsibility authorities are allocated for logistics workers with different responsibilities, barrier-free communication and man-machine interaction work of multiple levels of users is achieved, and logistics work efficiency is remarkably improved;
as shown in fig. 1, the human-computer interaction at least includes a voice communication module, specifically includes a microphone array for voice acquisition, and forms a pickup beam in the direction of a target speaker by using the spatial filtering characteristics of the microphone array, so as to suppress noise and reflected sound outside the beam.
The voice processing unit is configured to perform voice front-end processing such as noise reduction, echo cancellation and voice awakening on the collected sound, and output the noise-reduced audio signal, the sound source angle data and the awakening trigger signal.
The intended interaction range for which voice interaction is available may include: offline wake-up, room area state query, control command acceptance, control result feedback, identity verification request, dangerous person prompt, person evacuation prompt, equipment state query, equipment maintenance scheme suggestion, room resource query, energy consumption use prompt or/and attendance request of logistics personnel.
(2) Building autonomous management: and carrying out state monitoring and intelligent control on public equipment and room equipment in the building through a communication network and an end sensor.
The terminal sensor at least comprises a plurality of infrared sensors, ultraviolet sensors, temperature sensors, image acquisition modules and sound acquisition modules which are arranged at each floor in the building; the water supply system also comprises water supply overflow sensors arranged in the water supply main pipelines and current/voltage sensors arranged in the electric meter loops.
The communication network may be a wireless transmission network, or a combination of the internet of things and the wireless transmission network.
(3) And (3) machine vision recognition: identifying building personnel in real time, reading information such as identity and authority, intelligently identifying safety events such as building fire and the like, and assisting logistics service and security departments; the automatic distribution management of logistics work is assisted, fault detection and loss stopping are further achieved, and maintenance work and condition reporting are distributed based on the process.
The building personnel identification system comprises a video acquisition module, an image acquisition module and an identity identification system, wherein the video acquisition module, the image acquisition module and the identity identification system are arranged at a gate entrance guard for identifying building personnel.
The system specifically comprises a front-end image acquisition camera and a rear-end image processing system. The front end comprises a monitoring network consisting of a plurality of image acquisition cameras, the pedestrian movement track can be recorded in an all-round manner, and the human faces in different head postures can be detected more reliably and effectively by the cooperation of the plurality of cameras. The rear-end image processing system adopts machine learning to identify the detected face image, compares and confirms the identity of the pedestrian, and adopts different subsequent processing according to different personnel groups. The following processes are required for completing face recognition: the method comprises the steps of face image acquisition and detection, face image preprocessing, face image feature extraction, matching and identification. The system adopts network information encryption transmission and supports remote control and management.
Firstly, facial images of resident personnel and workers in a building are acquired through a front-end image acquisition system, and features are extracted through a deep learning algorithm to register identities. When the system works, the front-end camera collects images in real time, a deep learning algorithm is adopted to identify human bodies and human faces appearing in the images, and after human face features are obtained, retrieval comparison is carried out in registered household data tables and worker data tables.
If the face belongs to the resident list, opening an access control; if the face belongs to the staff list, checking the attendance of the staff by punching the card, and accessing a performance system of the staff; and for the dangerous personnel in the school and the suspicious personnel outside the school, calling a front-end camera to carry out seamless tracking on the pedestrian in the whole building, and sending a warning to a building security department.
(4) Event management based on specification standards: aiming at the handling condition of the emergency in logistics management, a standard event processing standard is designed, the emergency condition is detected, a solving process is automatically started, the coordination and organization personnel are used for processing, and the event processing condition is evaluated.
In order to accomplish the above functions, the necessary facilities include: smoke detector alarms, automatic spray heads, manual alarms, communication modules and expansion cameras which are arranged in various areas (particularly important areas such as residential areas, building crossings and the like) of the building; and the access control system and the human-computer interaction screen are arranged at the gate.
Specifically, a human-computer interaction system is constructed by means of voice interaction, image matching and the like during human-computer interaction. The voice interaction module adopts an intelligent voice system based on hardware recognition to realize the voice recognition of non-specific persons (SI).
The voice interaction module is provided with a VUI (Voice User interface) editor, so that a User can modify an identification process more conveniently and add and delete control instructions at any time, and the false triggering rate can be greatly reduced and the safety coefficient can be improved by an identification rejection algorithm based on identification scores; in addition, the voice interaction module increases the function of voice response, so that a user can conveniently change the content of the voice response, and the function of human-computer interaction is better realized; the man-machine interaction is provided with a graphical display interface to display man-machine interaction contents, related information in the building and the like, so that a more visual interaction effect is achieved.
In this embodiment, the human-computer interaction system is used as an information interaction unit to notify corresponding emergency information and a dispersion measure in a plan of personnel in a corresponding area, and to cooperatively process the emergency.
In the embodiment, public equipment and room equipment in the building are subjected to state monitoring and intelligent control through the communication network and the terminal sensor, and the management and control system mainly comprises an electric power system, a water supply system, a heating and ventilation system and a data acquisition system.
The on-off state of the current power system can be known through the ammeter loop information collected by the collector, and automatic control can be performed by configuring automatic control parameters through an administrator, wherein the automatic control parameters comprise timing parameters, time-sharing control parameters and the like.
The power subsystems controlled in the building include the following subsystems: an indoor lighting subsystem, a public area lighting subsystem, a multimedia device subsystem, a domestic water heater subsystem, an elevator subsystem, a ventilator subsystem, and a fire fighting device subsystem.
The state of the water supply pipeline is detected through pressure and flow data collected by collectors installed at all nodes, abnormal phenomena of leakage and overflow are found in time, a large number of water leakage accidents are automatically processed, the valve is closed in time according to the node flow and the pressure data, and loss is reduced. Simultaneously carry out real-time supervision to the interior water subsystem of building, report an emergency and ask for help or increased vigilance with the water condition unusually, the subsystem includes: a cleaning water subsystem and a domestic water subsystem.
The central heating system management and control in the building mainly comprises pipeline detection based on acquired pressure and flow and automatic control of a tail end heating valve, the pipeline detection is similar to a water supply system, and the automatic control of the heating valve is mainly time-sharing temperature-division control. Central air conditioning system management and control includes central air conditioning unit control, cooling pipeline detection and terminal fan control, and unit control is mainly through setting for unit automatic operation parameter, and terminal fan control includes and carries out equipment switch and temperature setting based on indoor personnel state and temperature, to installing monomer air conditioning room, carries out remote control through infrared controlgear.
According to the running state and the network communication state of each sensor and each type of sensors, timely feeding back alarm information; identifying and transmitting the running state of the metering device, supporting fault positioning and diagnosis of the metering device connected with the sensor, and transmitting fault information to a remote control end in time; the remote upgrading and restarting of the data acquisition unit are supported, the equipment can be automatically restarted according to the fault reason, the restarting information is uploaded to the remote control terminal, and the problem of data jamming is solved; and aiming at the data which cannot be successfully transmitted due to the reasons of transmission network faults and the like, the data stored by the collector is utilized to carry out breakpoint transmission after the network to be transmitted is recovered to be normal.
As an emergency management system, the core processing system of the invention combines a building management station, machine vision and a human-computer interaction system, designates an event coping standard mechanism, assists managers to find emergency (pipeline water leakage, regional power failure and the like) based on a logistics management regulation and management professional design, autonomously starts a corresponding plan, organizes linkage of a plurality of departments of logistics service staff based on the human-computer interaction system, cooperatively processes events and feeds back processing results.
Aiming at the fire disaster situation, the automatic spraying equipment is started in time to inform building managers and higher-level security departments, and the evacuation of organization personnel, the guidance of fire fighters and the like are assisted according to a campus emergency plan;
the fire emergency treatment method specifically comprises the following steps:
emergency event discovery: and if the three values exceed the set threshold value, determining whether a fire emergency happens or not by combining the information of the image acquisition module.
Meanwhile, the smoke detector alarm and the manual alarm device are integrated, so that the fire position can be found in time, and the fire size can be estimated.
And sending a voice prompt to a duty room to inform the fire occurrence and position, and starting automatic spraying.
And starting a fire emergency plan, and sending a fire prompt to an upper-level department.
The voice prompt for evacuating the building is manually or automatically started, and the voice prompt devices arranged in all areas in the building prompt the evacuation routes and the attention items corresponding to teachers and students on the relevant floors.
And (3) aiming at events such as water leakage, tripping and the like in logistics service, loss stopping operations such as regional water break and power break are carried out in time, the details of the events and maintenance suggestions are notified to maintenance personnel for rush repair, and the maintenance conditions are fed back and recorded. And aiming at events such as equipment damage and the like, the maintenance personnel are notified in time, maintenance schemes or manufacturer personnel are provided in an auxiliary mode, and maintenance conditions are fed back and recorded.
Specifically, according to building equipment management and control system, find trouble alarm information, preliminary diagnosis analysis alarm information in time carries out the processing of cutting off the water supply to the region that leaks. And sending event information and positions to the building management attendant, and informing the attendant to process.
Aiming at the building facility upgrading construction event in the building use process, the method assists in managing constructors, checking identities and authorities, providing construction assistance such as power failure and water cut-off and the like, and recording and reporting construction progress.
The operator on duty registers the information of construction time, position, personnel and the like, verifies the identity of the operator through a video acquisition module, an image acquisition module and an identity recognition system of the access control, and gives corresponding access control authority;
and collecting construction progress and reporting the construction progress to building management personnel at regular time by using a sound sensor and an image sensor which are arranged in a building to form effective supervision.
Aiming at the regular and irregular polling work of logistics management personnel, polling schedule items are arranged in an auxiliary mode, related departments and personnel are notified in time, partial contents such as building areas, equipment conditions and the like are automatically polled through a video means, and polling effects are evaluated and fed back.
And arranging inspection time for security, cleaning and maintenance personnel by combining video or image acquisition information, and sending a prompt instruction.
In the event processing, the collection of big data means that data transmitted from a client (Web, App, sensor, or the like) is received by using a plurality of databases, and simple query and processing work can be performed by using these databases. The data type, the data size, the read-write magnitude, the read-write proportion, the concurrency number, the consistency, the delay degree, the analysis complexity of the relational emergency management and control system are discriminated even without introducing a complex data mining algorithm and the like, data acquisition hardware, data transmission hardware and data acquisition detection software meeting the requirements of the energy consumption management and control system are constructed, and large data acquisition is achieved.
Since the big data of the collected environment information and the personnel information may be composed of TB level (or even PB level) information, including structured data (database, log, SQL, etc.) and unstructured data (sensor, multimedia data). The data lack of indexes or other organizational structures and may be composed of many different file types, so that the cost of storing the data is continuously increased, the data storage capacity is explosively increased and difficult to predict, the stored data cannot be managed due to the increasingly complex environment, and the storage function of the database is challenged.
As shown in fig. 2, the system performs partition operation on the data in the processing process, increases virtual memory and batch processing by establishing a wide indexing and caching mechanism, optimizes query statements by using a temporary table and a middle table, performs processing by using a text format, customizes a cleaning rule and an error processing mechanism, and completes data storage by using a data warehouse and a multidimensional database.
Storing all sensor information data in a building into a hadoop database, inputting uploaded data in advance, performing distributed management by adopting an HDFS (Hadoop distributed file system), setting data maximum threshold and data minimum threshold of all sensor parameters, sending out an equipment alarm through a real-time data platform when received data exceed a set threshold range, finding the position of a sensor through the sensor information input in advance, and further determining problem position information. In the process that the database is continuously called and new data is continuously stored, whether the sensor has problems or not can be predicted through the data trend uploaded by the sensor in real time.
In the data processing process, corresponding data processing system architecture software and system integration software are designed on the data acquisition, data conversion, data grouping, data organization, data calculation, data storage, data retrieval and data sorting rules, and the data are recorded in the preparation stage of the data. After the data are recorded, the data are processed according to the indication and the requirement of the program, and finally effective information meeting the requirement is output, so that the data processing based on the big data technology is completed.
And analyzing and refining data based on a data mining algorithm by segmenting, clustering and isolating points, and mining the value. And then prediction analysis is carried out, data mining can carry out digestion and understanding on data bearing information more quickly and better, the accuracy of judgment is further improved, and finally energy supply auxiliary decision is formed. And excavating the energy consumption use condition in the campus, predicting the energy consumption use condition, assisting in making an energy supply decision, showing in a chart/3D form, and outputting a reference distribution scheme.
For example, specific behaviors of different users can be depicted according to using habits of different users, power consumption conditions and water consumption conditions of the users are determined, change data of body temperature of the users detected by infrared rays at the same time in different days are recorded, the most comfortable body temperature of the users is obtained through analysis and calculation of the data, and the peak time and the valley time of the power consumption and the water consumption are respectively at the same time in the day, so that the water and electricity consumption can be automatically adjusted according to the time, and the effects of enabling the users to be satisfied and reducing energy consumption are achieved.
Of course, the following functions may also be provided:
and forecasting the logistics service demand. The logistics service requirements such as cleaning and security in the campus are mined, the user behaviors and distribution are combined, the logistics service requirements are subjected to prediction and distribution in an auxiliary mode, the prediction and distribution are displayed in a chart/3D mode, and a reference distribution scheme is output.
And (4) predicting an emergency. The operation and maintenance conditions of the equipment are excavated, the possible fault risk of the equipment is predicted, the robot system is informed of the personnel allocation in time, and relevant strategies for event processing and man-machine cooperative processing are provided.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (10)
1. The utility model provides an energy consumption intelligence management and control system based on big data mining which characterized by: the method comprises the following steps:
the environment influence parameter acquisition unit comprises corresponding sensors arranged in each area and is used for receiving acquired temperature, sound, image and humidity information;
the residential information acquisition unit comprises an electricity consumption information acquisition module for acquiring the on-off state information of an ammeter loop, a water supply information acquisition module for acquiring the pressure and flow data of a water supply loop and detecting the state of a water supply pipeline, which are arranged at each node, and a heating and ventilation information acquisition module for acquiring the working states of a central heating system and a central air-conditioning system;
the resource scheduling unit is configured to mine a behavior model of the user based on big data according to the received environment influence parameter information and the residence information, grasp and predict the user behavior, and allocate resources of corresponding spaces according to a prediction result;
the resource demand prediction module is configured to mine the logistics service demand of the building according to the received environment influence parameter information and the residence information, assist in predicting and distributing the logistics service demand in combination with user behaviors and distribution, and perform self-adaptive maintenance of the equipment and prediction of fault risks;
and the information interaction unit is configured to receive the resource allocation instruction, supply or interrupt resources to the corresponding space, realize the management and control of energy consumption, maintain and eliminate potential faults according to the predicted equipment operation condition, and realize the operation and maintenance management of the public facilities of the building.
2. The intelligent energy consumption management and control system based on big data mining as claimed in claim 1, characterized in that: the environment influence parameter acquisition unit comprises a plurality of temperature sensors, humidity sensors, an image acquisition module, an infrared sensor, an ultraviolet sensor and a sound acquisition module which are arranged on each floor in a building.
3. The intelligent energy consumption management and control system based on big data mining as claimed in claim 1, characterized in that: the water supply information acquisition module comprises water supply overflow sensors arranged on each water supply main pipeline and sensors arranged on each water supply branch and used for acquiring flow and pressure of the corresponding water supply branch.
4. The intelligent energy consumption management and control system based on big data mining as claimed in claim 1, characterized in that: the power utilization information acquisition module comprises an acquisition device for acquiring the loop information of the electric meter, and the on-off state of the current electric power loop is acquired.
5. The intelligent energy consumption management and control system based on big data mining as claimed in claim 1, characterized in that: the environment influence parameter acquisition unit comprises a plurality of image acquisition modules, the image acquisition modules form a monitoring network, the pedestrian movement track can be recorded in an all-round mode, and the image acquisition modules are matched with one another to detect faces in different head postures.
6. The intelligent energy consumption management and control system based on big data mining as claimed in claim 1, characterized in that: the sensor or collector arranged in each area has a unique ID and an IP address, and collects the information of the environmental impact parameter collection unit of the area corresponding to the sensor or collector.
7. An energy consumption intelligent control method based on big data mining is characterized in that: the method comprises the following steps:
collecting temperature, sound, image and humidity information of each area;
collecting the on-off state information of an ammeter loop, collecting pressure and flow data of a water supply loop, and detecting the state of a water supply pipeline;
according to the received environmental impact parameter information and residence information, performing behavior model mining on the user, grasping and predicting the user behavior, and performing resource allocation of the corresponding space according to the prediction result;
according to the resource allocation instruction, performing resource supply or interruption on the corresponding space to realize energy consumption management and control; and according to the predicted equipment operation condition, maintaining and eliminating potential faults, and realizing the operation and maintenance management of the public facilities of the building.
8. The intelligent energy consumption control method based on big data mining as claimed in claim 7, characterized in that: and storing the environmental impact parameter information and the residence information into a database, inputting the uploaded data in advance, and performing distributed management on the data.
9. The intelligent energy consumption control method based on big data mining as claimed in claim 7, characterized in that: and presetting the maximum threshold and the minimum threshold of data of all acquisition element parameters, alarming corresponding equipment when the received data exceeds the set threshold range, and finding the position of the sensor according to the ID information of the sensor.
10. The intelligent energy consumption control method based on big data mining as claimed in claim 7, characterized in that: the specific process of mining the behavior model of the user according to the received environmental impact parameter information and the residence information, mastering and predicting the behavior of the user comprises the following steps: determining the use habits of the corresponding users according to the received environmental influence parameter information and the residence information, depicting the specific behaviors of the users, including the electricity utilization condition, the water utilization condition and the body temperature of the corresponding users in each time period, analyzing and calculating, determining the most comfortable body temperature of the users, the peak period and the valley period of the electricity utilization and the water utilization, and adjusting the water and electricity consumption according to the determination result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011508612.3A CN112650335A (en) | 2020-12-18 | 2020-12-18 | Intelligent energy consumption management and control system and method based on big data mining |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011508612.3A CN112650335A (en) | 2020-12-18 | 2020-12-18 | Intelligent energy consumption management and control system and method based on big data mining |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112650335A true CN112650335A (en) | 2021-04-13 |
Family
ID=75355028
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011508612.3A Pending CN112650335A (en) | 2020-12-18 | 2020-12-18 | Intelligent energy consumption management and control system and method based on big data mining |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112650335A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115356977A (en) * | 2022-10-19 | 2022-11-18 | 苏州新算力科技研发有限公司 | Artificial intelligence energy-saving monitoring system and method |
| CN117235672A (en) * | 2023-11-14 | 2023-12-15 | 北京市科学技术研究院 | Comprehensive pipe gallery fault diagnosis method and device based on multi-source data |
Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202772987U (en) * | 2012-09-21 | 2013-03-06 | 上海幻装信息科技有限公司 | Wireless network monitoring camera applied to building and decoration construction site |
| CN104134100A (en) * | 2014-07-22 | 2014-11-05 | 香港佳能通节能科技有限公司 | Energy-saving management system based on cloud computing |
| CN105135623A (en) * | 2015-09-17 | 2015-12-09 | 国网天津市电力公司 | Central air-conditioner deloading control method capable of meeting power grid peak shaving and user comfort level |
| US20160047568A1 (en) * | 2014-08-15 | 2016-02-18 | Delta Electronics, Inc. | Intelligent air-conditioning controlling system and intelligent controlling method for the same |
| CN106504501A (en) * | 2016-12-02 | 2017-03-15 | 陈彦舟 | The monitoring of long-distance intelligent comprehensive energy consumption and metering system |
| CN206100315U (en) * | 2016-10-18 | 2017-04-12 | 武汉大学深圳研究院 | Monitored control system is trailed in security protection of three dimensions sound source |
| CN106765957A (en) * | 2016-12-23 | 2017-05-31 | 新智能源系统控制有限责任公司 | Water supply variable temperature control system based on load prediction and comfort level feedback |
| CN107525236A (en) * | 2017-08-18 | 2017-12-29 | 青岛海尔空调器有限总公司 | Air-conditioner control method and air conditioner based on human comfort |
| CN107560113A (en) * | 2017-08-18 | 2018-01-09 | 青岛海尔空调器有限总公司 | A kind of intelligent air conditioner control method and air conditioner |
| CN107741710A (en) * | 2017-10-16 | 2018-02-27 | 深圳技师学院 | A kind of building energy consumption intelligent cloud management control system and method |
| CN109213033A (en) * | 2018-08-23 | 2019-01-15 | 深圳供电局有限公司 | A kind of building wisdom energy management method and system |
| CN109885118A (en) * | 2019-03-15 | 2019-06-14 | 中国建筑科学研究院有限公司 | Environmental control system |
| US20190199685A1 (en) * | 2017-12-21 | 2019-06-27 | Bce Inc. | Smart Building Agent |
| KR102067110B1 (en) * | 2019-06-20 | 2020-01-15 | (주)씨이랩 | Energy data processing apparatus and method with high accuracy for constructed building |
| CN110864414A (en) * | 2019-10-30 | 2020-03-06 | 郑州电力高等专科学校 | Air conditioner power utilization load intelligent control scheduling method based on big data analysis |
-
2020
- 2020-12-18 CN CN202011508612.3A patent/CN112650335A/en active Pending
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202772987U (en) * | 2012-09-21 | 2013-03-06 | 上海幻装信息科技有限公司 | Wireless network monitoring camera applied to building and decoration construction site |
| CN104134100A (en) * | 2014-07-22 | 2014-11-05 | 香港佳能通节能科技有限公司 | Energy-saving management system based on cloud computing |
| US20160047568A1 (en) * | 2014-08-15 | 2016-02-18 | Delta Electronics, Inc. | Intelligent air-conditioning controlling system and intelligent controlling method for the same |
| CN105135623A (en) * | 2015-09-17 | 2015-12-09 | 国网天津市电力公司 | Central air-conditioner deloading control method capable of meeting power grid peak shaving and user comfort level |
| CN206100315U (en) * | 2016-10-18 | 2017-04-12 | 武汉大学深圳研究院 | Monitored control system is trailed in security protection of three dimensions sound source |
| CN106504501A (en) * | 2016-12-02 | 2017-03-15 | 陈彦舟 | The monitoring of long-distance intelligent comprehensive energy consumption and metering system |
| CN106765957A (en) * | 2016-12-23 | 2017-05-31 | 新智能源系统控制有限责任公司 | Water supply variable temperature control system based on load prediction and comfort level feedback |
| CN107525236A (en) * | 2017-08-18 | 2017-12-29 | 青岛海尔空调器有限总公司 | Air-conditioner control method and air conditioner based on human comfort |
| CN107560113A (en) * | 2017-08-18 | 2018-01-09 | 青岛海尔空调器有限总公司 | A kind of intelligent air conditioner control method and air conditioner |
| CN107741710A (en) * | 2017-10-16 | 2018-02-27 | 深圳技师学院 | A kind of building energy consumption intelligent cloud management control system and method |
| US20190199685A1 (en) * | 2017-12-21 | 2019-06-27 | Bce Inc. | Smart Building Agent |
| CN109213033A (en) * | 2018-08-23 | 2019-01-15 | 深圳供电局有限公司 | A kind of building wisdom energy management method and system |
| CN109885118A (en) * | 2019-03-15 | 2019-06-14 | 中国建筑科学研究院有限公司 | Environmental control system |
| KR102067110B1 (en) * | 2019-06-20 | 2020-01-15 | (주)씨이랩 | Energy data processing apparatus and method with high accuracy for constructed building |
| CN110864414A (en) * | 2019-10-30 | 2020-03-06 | 郑州电力高等专科学校 | Air conditioner power utilization load intelligent control scheduling method based on big data analysis |
Non-Patent Citations (2)
| Title |
|---|
| 张涛: "《机器人概论》", 31 October 2019, 机械工业出版社 * |
| 贝内斯特: "《麦克风陈列信号处理》", 31 January 2016, 国防工业出版社 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115356977A (en) * | 2022-10-19 | 2022-11-18 | 苏州新算力科技研发有限公司 | Artificial intelligence energy-saving monitoring system and method |
| CN117235672A (en) * | 2023-11-14 | 2023-12-15 | 北京市科学技术研究院 | Comprehensive pipe gallery fault diagnosis method and device based on multi-source data |
| CN117235672B (en) * | 2023-11-14 | 2024-03-08 | 北京市科学技术研究院 | Comprehensive pipe gallery fault diagnosis method and device based on multi-source data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112578690B (en) | Intelligent building energy consumption management and control system and method | |
| CN110158648A (en) | A kind of Urban Underground pipe gallery O&M monitoring management system | |
| CN109065135B (en) | Hospital logistics equipment full-life-cycle management cloud platform, method and system | |
| CN112488898B (en) | Emergency handling system and method based on intelligent building management and control | |
| CN110798344A (en) | Intelligent power distribution operation and maintenance system | |
| CN110933376A (en) | Fire-fighting Internet of things unified supervision system and method | |
| CN112650335A (en) | Intelligent energy consumption management and control system and method based on big data mining | |
| CN107947362A (en) | Electric railway traction supply intelligent auxiliary system | |
| CN109493985A (en) | Nuclear power plant digitizes auxiliary control panel system, design method and control system | |
| KR102440097B1 (en) | System for predicting and preventing disaster for electric power facilities and operation method thereof | |
| CN107015548A (en) | Archive office's intelligent environment detecting and controlling system | |
| CN109685482B (en) | Intelligent building management method, system and application of human, machine and object information fusion | |
| CN105320093A (en) | Intelligent building monitoring system and method | |
| CN105632127A (en) | Cell security system based on internet of things | |
| CN109746893A (en) | Intelligence O&M robot, data center | |
| KR102399268B1 (en) | Method for artificial intelligence connected intelligent disaster safety management and system for performing the method | |
| CN113053053A (en) | Interval demonstration multi-sensor fusion disaster cellular alarm linkage system based on particle swarm optimization | |
| CN112800910A (en) | Communication machine room maintenance operation efficiency evaluation method and system | |
| JPH096428A (en) | Plant monitoring equipment | |
| Xu et al. | Effectiveness study of artificial intelligent facility system in maintaining building fire safety (case study: typical public building cases of fire-fighting facilities management in China) | |
| CN112288155B (en) | Security plan generation scheduling method and system based on machine learning and collaborative filtering | |
| CN111582165B (en) | Monitoring system for power distribution station room | |
| CN113955594A (en) | Elevator control method and device, computer equipment and storage medium | |
| CN112700772A (en) | Intelligent voice system and method based on hardware identification | |
| CN206292788U (en) | Communal bathroom management system based on Internet of Things |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210413 |
|
| RJ01 | Rejection of invention patent application after publication |