CN114331000A - Wisdom garden energy consumption management system based on artificial intelligence - Google Patents
Wisdom garden energy consumption management system based on artificial intelligence Download PDFInfo
- Publication number
- CN114331000A CN114331000A CN202111414974.0A CN202111414974A CN114331000A CN 114331000 A CN114331000 A CN 114331000A CN 202111414974 A CN202111414974 A CN 202111414974A CN 114331000 A CN114331000 A CN 114331000A
- Authority
- CN
- China
- Prior art keywords
- energy consumption
- park
- equipment
- consumption data
- time
- 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
-
- 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/82—Energy audits or management systems therefor
Abstract
The invention discloses an artificial intelligence-based intelligent park energy consumption management system, which relates to the technical field of park management and comprises an energy consumption acquisition module, an energy consumption analysis module and an equipment monitoring module; the energy consumption analysis module is used for acquiring the energy consumption data of the park equipment acquired by the energy consumption acquisition module in real time, analyzing the energy consumption data in combination with historical synchronous energy consumption data of the park equipment and judging whether the energy consumption data of the park equipment is abnormal or not; all be provided with corresponding detection sensor in every garden equipment, a current operating condition information for detecting the garden equipment rather than corresponding, equipment monitoring module is used for carrying out the preliminary treatment to current operating condition information, and compare the operating condition information after the preliminary treatment with the safety criterion that the database prestores and corresponds with the garden equipment, confirm the current safety situation of garden equipment, and send it to the mobile terminal who is correlated with, in order to remind mobile terminal's managers, thereby reduce the loss of electric power in the wisdom garden, avoid the security risk.
Description
Technical Field
The invention relates to the technical field of park management, in particular to an intelligent park energy consumption management system based on artificial intelligence.
Background
In recent years, effective campus management becomes an important means for promoting the healthy development of a campus, and along with the continuous development of the campus, the traditional management mode is more and more unsuitable for the requirement of rapid development of the campus; the construction of wisdom garden is not only scientific and technological development's must, and informationization, intellectuality, wisdom are in bringing the great progress of management for the garden, and originally the garden management operation and for the angle that the park enterprise provides high-quality service that parks in, the park enterprise provides high-quality garden service through advanced scientific and technological product, also has brought the huge change of life style for the personnel who live in the garden and work simultaneously.
At present, many park enterprises still adopt a manual statistics mode to collect various energy consumption data, and adopt a manual patrol mode to check the temperature of a park machine room, and an intelligent park system in the prior art has extensive energy consumption management, does not form effective monitoring and management on energy consumption of facilities such as lighting, air conditioners, equipment and the like, cannot analyze and predict a periodic system, cannot remind about energy consumption abnormity occurring in real time, can only search reasons through data analysis afterwards, and actually cause energy waste; various solutions are proposed in the industry, but the problems that the monitoring is not timely and the management is deficient are solved.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides an intelligent park energy consumption management system based on artificial intelligence.
In order to achieve the above object, an embodiment according to a first aspect of the present invention provides an artificial intelligence-based intelligent park energy consumption management system, including an energy consumption acquisition module, an energy consumption analysis module, and an equipment monitoring module;
the energy consumption analysis module is used for acquiring energy consumption data of the park equipment acquired by the energy consumption acquisition module in real time, analyzing the energy consumption data in combination with historical synchronous energy consumption data of the park equipment, and calculating to obtain an energy consumption bias value P1; if the P1 is larger than the bias threshold, generating reminding information;
the analysis process of the energy consumption analysis module further comprises the following steps: when the park equipment is powered on and operated, establishing a curve graph of real-time energy consumption data changing along with time, and deriving the curve graph to obtain an energy consumption change rate curve graph; acquiring the real-time energy consumption change rate once every R2 time from the initial moment to obtain an energy consumption change rate information group; wherein R2 is a preset value;
calculating a standard deviation gamma of the energy consumption change rate information group according to a standard deviation formula, and counting the real-time energy consumption change rate when the standard deviation gamma reaches a standard threshold value to be B0; continuously acquiring the real-time energy consumption change rate, and sequentially marking as B1, B2, B3, … and Bi; wherein i is 1, …, n;
and evaluating the variable coefficient DF according to the B0 and the subsequently acquired real-time energy consumption change rate, and if the DF is larger than a preset coefficient threshold, generating an early warning signal.
Further, the specific analysis steps of the energy consumption analysis module are as follows:
s1: determining unit energy consumption data of the park equipment according to the energy consumption data of the park equipment acquired by the energy consumption acquisition module in real time, and establishing a curve graph of the unit energy consumption data changing along with time;
s2: marking unit energy consumption data of the park equipment as N1, calling historical synchronous energy consumption data of the park equipment from the cloud platform, and marking as NLm, wherein m is 1, … and g;
s3: using formulas
And calculating to obtain an energy consumption bias value P1, wherein a1 is a compensation coefficient.
Furthermore, the energy consumption acquisition module is used for acquiring energy consumption data of the park equipment in real time, periodically integrating the acquired energy consumption data, and then storing the integrated data to the cloud platform; the concrete expression is as follows: establishing a curve graph of energy consumption data changing along with time by taking 24 hours as a period; carrying out derivation and integration on the curve graph to obtain a curve graph of unit energy consumption data changing along with time; and stamping a time stamp on the obtained curve graph and storing the curve graph to the cloud platform.
Further, the energy consumption analysis module is used for sending the reminding information to the associated mobile terminal so as to remind a manager of the mobile terminal to confirm whether the energy consumption data of the park equipment is normal.
Further, the evaluation process of the variable coefficient DF is as follows:
when Bi > B (i-1), marking Bi as affecting rate; calculating the difference between the influencing rates Bi and B (i-1) to obtain a first speed change value G1, and calculating the difference between Bi and B0 to obtain a second speed change value G2; calculating a univariate value GT by using a formula GT of G1 Xg 1+ G2 Xg 2; summing all the single variable values to obtain a total variable speed value GZ; wherein g1 and g2 are coefficient factors;
the number of times of occurrence of the statistical influence rate is C1, and the energy-variable coefficient DF is calculated by using the formula DF ═ GZ × g3+ C1 × g4, wherein g3 and g4 are coefficient factors.
Furthermore, the energy consumption analysis module is used for sending the early warning signal to a management center, the management center receives the early warning signal and then controls the alarm module to give an alarm, and sends the early warning signal to the associated mobile terminal so as to remind a manager of the mobile terminal that the energy consumption of equipment in the corresponding park is abnormal.
Furthermore, each garden device is provided with a corresponding detection sensor, and the detection sensors are connected with the device monitoring modules in a distributed manner through nodes of the Internet of things; the detection sensor comprises a temperature sensor, a noise sensor and a vibration sensor.
Furthermore, the detection sensor is used for detecting the current working state information of the park equipment corresponding to the detection sensor and sending the detected current working state information to the equipment monitoring module;
the equipment monitoring module is used for preprocessing the current working state information, comparing the preprocessed working state information with a safety criterion which is prestored in a database and corresponds to the garden equipment, and determining the current safety condition of the garden equipment; the equipment monitoring module is used for sending the current safety condition of the park equipment to the management center, and the management center is used for sending the current safety condition to the associated mobile terminal so as to remind the manager of the mobile terminal.
Compared with the prior art, the invention has the beneficial effects that:
1. the energy consumption analysis module is used for acquiring energy consumption data of the park equipment acquired by the energy consumption acquisition module in real time, analyzing the energy consumption data in combination with historical contemporaneous energy consumption data of the park equipment, calculating to obtain an energy consumption bias value of the park equipment, and generating reminding information if the energy consumption bias value is greater than a bias value threshold value; when the park equipment is powered on and operated, the energy consumption analysis module is further used for establishing a curve graph of real-time energy consumption data changing along with time and obtaining a derivative to obtain an energy consumption change rate information set, counting that the real-time energy consumption change rate when the standard deviation gamma reaches a standard threshold value is B0, evaluating a variable coefficient DF according to B0 and the subsequently acquired real-time energy consumption change rate, and if the DF is larger than a preset coefficient threshold value, generating an early warning signal to remind a manager of the mobile terminal, so that the loss of electric power in the intelligent park is reduced, and the safety risk is avoided;
2. each park device is provided with a corresponding detection sensor for detecting the current working state information of the park device corresponding to the detection sensor, and the device monitoring module is used for preprocessing the current working state information, comparing the preprocessed working state information with the safety criterion which is prestored in the database and corresponds to the park device, and determining the current safety condition of the park device; the management center is used for sending the current safety condition to the associated mobile terminal so as to remind a manager of the mobile terminal that safety risks exist in the garden equipment corresponding to the manager, so that the energy consumption process and the energy consumption mode are improved, adjusted and optimized in a targeted manner, and the energy use efficiency is improved.
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 description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, an artificial intelligence-based energy consumption management system for a smart park comprises an energy consumption acquisition module, a cloud platform, an energy consumption analysis module, a management center, an alarm module and an equipment monitoring module;
the energy consumption acquisition module is used for acquiring energy consumption data of the park equipment in real time, periodically integrating the acquired energy consumption data and storing the integrated data to the cloud platform; the concrete expression is as follows: establishing a curve graph of energy consumption data changing along with time by taking 24 hours as a period; carrying out derivation and integration on the curve graph to obtain a curve graph of unit energy consumption data changing along with time; in the present embodiment, the unit energy consumption data refers to energy consumption data per unit time period, for example, energy consumption data per 2 hours; stamping a time stamp on the obtained curve graph and storing the curve graph to a cloud platform;
the energy consumption analysis module is used for obtaining the energy consumption data of the park equipment acquired by the energy consumption acquisition module in real time and analyzing the energy consumption data in the same period by combining the historical energy consumption data of the park equipment, and the specific analysis steps are as follows:
s1: determining unit energy consumption data of the park equipment according to the energy consumption data of the park equipment acquired by the energy consumption acquisition module in real time, and establishing a curve graph of the unit energy consumption data changing along with time;
s2: marking unit energy consumption data of the park equipment as N1, calling historical synchronous energy consumption data of the park equipment from the cloud platform, and marking as NLm, wherein m is 1, … and g; in the present embodiment, the historical contemporaneous energy consumption data refers to unit energy consumption data of the same time period;
s3: using formulas
Calculating to obtain an energy consumption bias value P1, wherein a1 is a compensation coefficient and takes a value of 0.358965;
comparing the energy consumption bias value P1 with a bias value threshold value, and if P1 is greater than the bias value threshold value, generating reminding information; the energy consumption analysis module is used for sending the reminding information to the associated mobile terminal so as to remind a manager of the mobile terminal to confirm whether the energy consumption data of the park equipment is normal or not;
for example: the daily operation time of a certain park device is less at ordinary times, the unit energy consumption data is lower if the operation time is fixed, short circuit leakage or forgetting to close is possible if the unit energy consumption data is higher in the same time period in a certain day, and at the moment, a reminding message is sent to the associated mobile terminal, so that energy consumption is avoided, and the energy management efficiency is effectively improved;
the analysis process of the energy consumption analysis module further comprises the following steps:
when the park equipment is powered on and operated, establishing a curve graph of real-time energy consumption data changing along with time; the energy consumption data at this time is total energy consumption data after the equipment in the park starts to operate, and theoretically, the energy consumption data is always in an ascending state;
deriving the curve graph to obtain an energy consumption change rate curve graph, and acquiring the real-time energy consumption change rate once every R2 time from the initial moment to obtain an energy consumption change rate information group; wherein R2 is a preset value;
calculating a standard deviation gamma of the energy consumption change rate information group according to a standard deviation formula, automatically calculating a new standard deviation gamma every time a new real-time energy consumption change rate is obtained, and counting the real-time energy consumption change rate when the standard deviation gamma reaches a standard threshold value to be B0; continuously acquiring the real-time energy consumption change rate, and sequentially marking as B1, B2, B3, … and Bi; 1, …, n;
when Bi is larger than B (i-1), marking Bi as an influence rate, calculating the difference between the influence rate Bi and B (i-1) to obtain a first velocity change value G1, and calculating the difference between Bi and B0 to obtain a second velocity change value G2; calculating a univariate value GT by using a formula GT of G1 Xg 1+ G2 Xg 2; summing all the single variable values to obtain a total variable speed value GZ; wherein g1 and g2 are coefficient factors;
counting the frequency of occurrence of the influence rate to be C1, and calculating an energy variable coefficient DF by using a formula DF (GZ × g3+ C1 × g 4), wherein g3 and g4 are coefficient factors;
comparing the energy-variable coefficient DF with a preset coefficient threshold, if the DF is larger than the preset coefficient threshold, generating an early warning signal, sending the early warning signal to a management center by an energy consumption analysis module, controlling an alarm module to send an alarm after the management center receives the early warning signal, and sending the early warning signal to an associated mobile terminal so as to remind a manager of the mobile terminal that the energy consumption of equipment in a corresponding park is abnormal, and suggesting maintenance;
in the embodiment, each garden device is provided with a corresponding detection sensor, and the detection sensors are connected with the device monitoring modules in a distributed manner through nodes of the internet of things;
the system comprises a detection sensor, an equipment monitoring module, a database and a data base, wherein the detection sensor is used for detecting the current working state information of park equipment corresponding to the detection sensor and sending the detected current working state information to the equipment monitoring module;
the equipment monitoring module is used for sending the current safety condition of the park equipment to the management center, and the management center is used for sending the current safety condition to the associated mobile terminal so as to remind a manager of the mobile terminal that the park equipment has safety risks;
it should be noted that, in this embodiment, different park devices correspond to different detection sensors or different parts of the same device employ different detection sensors, the detection sensors include a temperature sensor, a noise sensor, a vibration sensor, and the like, and the current working state information includes the temperature, the noise decibel value, and the vibration information of the current park device; the security criteria further include a corresponding work period; for example, when the air conditioner of an office is not closed after work and the temperature of a machine room in a park is abnormal, related management personnel can be reminded, so that the loss of electric power in the intelligent park is reduced, and safety risks are avoided; according to the invention, through automatically collecting and monitoring the scattered equipment energy consumption data of the park and through counting, comparing and analyzing various real-time and historical energy consumption data change trends, a user is helped to find and solve the problems existing in the energy consumption mode and structure, so that the energy consumption process and mode are improved, adjusted and optimized in a targeted manner, and the energy use efficiency is improved.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
The working principle of the invention is as follows:
an artificial intelligence-based intelligent park energy consumption management system is characterized in that when the intelligent park energy consumption management system works, an energy consumption acquisition module is used for acquiring energy consumption data of park equipment in real time and periodically integrating the acquired energy consumption data; the energy consumption analysis module is used for acquiring energy consumption data of the park equipment acquired by the energy consumption acquisition module in real time, analyzing the energy consumption data in combination with historical contemporaneous energy consumption data of the park equipment, calculating to obtain an energy consumption bias value of the park equipment, and if the energy consumption bias value is greater than a bias value threshold value, generating reminding information; when the park equipment is powered on and operated, establishing a time-varying curve chart of real-time energy consumption data and obtaining a derivative to obtain an energy consumption change rate information group; counting the real-time energy consumption change rate when the standard deviation gamma of the energy consumption change rate information group reaches a standard threshold value as B0; continuously acquiring the real-time energy consumption change rate, comparing the real-time energy consumption change rate with B0, calculating to obtain an energy variable coefficient DF, and if the DF is greater than a preset coefficient threshold, generating an early warning signal;
each park device is provided with a corresponding detection sensor for detecting the current working state information of the park device corresponding to the detection sensor, and the device monitoring module is used for preprocessing the current working state information, comparing the preprocessed working state information with the safety criterion which is prestored in the database and corresponds to the park device, and determining the current safety condition of the park device; the management center is used for sending the current safety condition to the associated mobile terminal so as to remind a manager of the mobile terminal that safety risks exist in the garden equipment corresponding to the manager, so that the energy consumption process and the energy consumption mode are improved, adjusted and optimized in a targeted manner, and the energy use efficiency is improved.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (8)
1. An artificial intelligence-based intelligent park energy consumption management system is characterized by comprising an energy consumption acquisition module, an energy consumption analysis module and an equipment monitoring module;
the energy consumption analysis module is used for acquiring energy consumption data of the park equipment acquired by the energy consumption acquisition module in real time, analyzing the energy consumption data in combination with historical synchronous energy consumption data of the park equipment, and calculating to obtain an energy consumption bias value P1; if the P1 is larger than the bias threshold, generating reminding information;
the analysis process of the energy consumption analysis module further comprises the following steps: when the park equipment is powered on and operated, establishing a curve graph of real-time energy consumption data changing along with time, and deriving the curve graph to obtain an energy consumption change rate curve graph; acquiring the real-time energy consumption change rate once every R2 time from the initial moment to obtain an energy consumption change rate information group; wherein R2 is a preset value;
calculating a standard deviation gamma of the energy consumption change rate information group according to a standard deviation formula, and counting the real-time energy consumption change rate when the standard deviation gamma reaches a standard threshold value to be B0; continuously acquiring the real-time energy consumption change rate, and sequentially marking as B1, B2, B3, … and Bi; wherein i is 1, …, n;
and evaluating the variable coefficient DF according to the B0 and the subsequently acquired real-time energy consumption change rate, and if the DF is larger than a preset coefficient threshold, generating an early warning signal.
2. The intelligent park energy consumption management system based on artificial intelligence of claim 1, wherein the specific analysis steps of the energy consumption analysis module are as follows:
s1: determining unit energy consumption data of the park equipment according to the energy consumption data of the park equipment acquired by the energy consumption acquisition module in real time, and establishing a curve graph of the unit energy consumption data changing along with time;
s2: marking unit energy consumption data of the park equipment as N1, calling historical synchronous energy consumption data of the park equipment from the cloud platform, and marking as NLm, wherein m is 1, … and g;
s3: using formulas
Calculating to obtain an energy consumption bias value P1, wherein a1 is a compensation systemAnd (4) counting.
3. The intelligent park energy consumption management system based on artificial intelligence of claim 1, wherein the energy consumption acquisition module is used for acquiring energy consumption data of park equipment in real time and periodically integrating the acquired energy consumption data, and then storing the integrated data to the cloud platform; the concrete expression is as follows: establishing a curve graph of energy consumption data changing along with time by taking 24 hours as a period; carrying out derivation and integration on the curve graph to obtain a curve graph of unit energy consumption data changing along with time; and stamping a time stamp on the obtained curve graph and storing the curve graph to the cloud platform.
4. The intelligent park energy consumption management system based on artificial intelligence of claim 1, wherein the energy consumption analysis module is configured to send a reminding message to an associated mobile terminal to remind a manager of the mobile terminal to confirm whether the energy consumption data of the park equipment is normal.
5. The intelligent park energy consumption management system based on artificial intelligence of claim 1, wherein the evaluation process of the energy variable coefficient DF is as follows:
when Bi > B (i-1), marking Bi as affecting rate; calculating the difference between the influencing rates Bi and B (i-1) to obtain a first speed change value G1, and calculating the difference between Bi and B0 to obtain a second speed change value G2; calculating a univariate value GT by using a formula GT of G1 Xg 1+ G2 Xg 2; summing all the single variable values to obtain a total variable speed value GZ; wherein g1 and g2 are coefficient factors;
the number of times of occurrence of the statistical influence rate is C1, and the energy-variable coefficient DF is calculated by using the formula DF ═ GZ × g3+ C1 × g4, wherein g3 and g4 are coefficient factors.
6. The intelligent park energy consumption management system based on artificial intelligence as claimed in claim 1, wherein the energy consumption analysis module is used for sending an early warning signal to the management center, the management center controls the alarm module to send out an alarm after receiving the early warning signal, and sends the early warning signal to the associated mobile terminal so as to remind the manager of the mobile terminal that the energy consumption of the corresponding park equipment is abnormal.
7. The intelligent park energy consumption management system based on artificial intelligence of claim 1, wherein each park equipment is provided with a corresponding detection sensor, and the detection sensors are connected with the equipment monitoring modules in a distributed manner through nodes of the internet of things; the detection sensor comprises a temperature sensor, a noise sensor and a vibration sensor.
8. The intelligent park energy consumption management system based on artificial intelligence of claim 7, wherein the detection sensor is used for detecting the current working state information of the park equipment corresponding to the detection sensor and sending the detected current working state information to the equipment monitoring module;
the equipment monitoring module is used for preprocessing the current working state information, comparing the preprocessed working state information with a safety criterion which is prestored in a database and corresponds to the garden equipment, and determining the current safety condition of the garden equipment; the equipment monitoring module is used for sending the current safety condition of the park equipment to the management center, and the management center is used for sending the current safety condition to the associated mobile terminal so as to remind the manager of the mobile terminal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111414974.0A CN114331000A (en) | 2021-11-25 | 2021-11-25 | Wisdom garden energy consumption management system based on artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111414974.0A CN114331000A (en) | 2021-11-25 | 2021-11-25 | Wisdom garden energy consumption management system based on artificial intelligence |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114331000A true CN114331000A (en) | 2022-04-12 |
Family
ID=81046046
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111414974.0A Pending CN114331000A (en) | 2021-11-25 | 2021-11-25 | Wisdom garden energy consumption management system based on artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114331000A (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115079589A (en) * | 2022-08-24 | 2022-09-20 | 深圳泛和科技有限公司 | Park management method, device, system, electronic equipment and computer readable medium |
| CN115619593A (en) * | 2022-12-16 | 2023-01-17 | 山东恒迈信息科技有限公司 | Wisdom power consumption management cloud platform |
| CN115689095A (en) * | 2022-12-30 | 2023-02-03 | 广东美的制冷设备有限公司 | Equipment energy consumption analysis method and device, production system and storage medium |
| CN115755738A (en) * | 2022-11-22 | 2023-03-07 | 湘煤立达矿山装备股份有限公司 | Mining intelligent power monitoring system |
| CN115796716A (en) * | 2023-02-13 | 2023-03-14 | 易通远见(北京)科技有限公司 | Building energy-saving management system based on Internet of things |
| CN115883779A (en) * | 2022-10-13 | 2023-03-31 | 湖北公众信息产业有限责任公司 | Smart park information safety management system based on big data |
| CN116029866A (en) * | 2023-02-20 | 2023-04-28 | 南京鲜玩网络科技有限公司 | Intelligent park management system and method based on Internet |
| CN116610921A (en) * | 2023-06-14 | 2023-08-18 | 深圳市顶尖传诚科技有限公司 | Intelligent park information management system and method based on big data |
| CN116846892A (en) * | 2023-07-04 | 2023-10-03 | 内蒙古达闻电子科技有限责任公司 | Intelligent energy consumption supervision system and method applying edge computing |
| CN117077899A (en) * | 2023-10-16 | 2023-11-17 | 四川邕合科技有限公司 | Intelligent park energy consumption anomaly monitoring and analyzing method, system, terminal and medium |
| CN117406685A (en) * | 2023-12-14 | 2024-01-16 | 无锡泰禾宏科技有限公司 | Intelligent control optimizing management system of building equipment suitable for green low-carbon building |
-
2021
- 2021-11-25 CN CN202111414974.0A patent/CN114331000A/en active Pending
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115079589A (en) * | 2022-08-24 | 2022-09-20 | 深圳泛和科技有限公司 | Park management method, device, system, electronic equipment and computer readable medium |
| CN115079589B (en) * | 2022-08-24 | 2022-11-11 | 深圳泛和科技有限公司 | Park management method, device, system, electronic equipment and computer readable medium |
| CN115883779B (en) * | 2022-10-13 | 2023-08-04 | 湖北公众信息产业有限责任公司 | Intelligent park information safety management system based on big data |
| CN115883779A (en) * | 2022-10-13 | 2023-03-31 | 湖北公众信息产业有限责任公司 | Smart park information safety management system based on big data |
| CN115755738A (en) * | 2022-11-22 | 2023-03-07 | 湘煤立达矿山装备股份有限公司 | Mining intelligent power monitoring system |
| CN115619593A (en) * | 2022-12-16 | 2023-01-17 | 山东恒迈信息科技有限公司 | Wisdom power consumption management cloud platform |
| CN115689095A (en) * | 2022-12-30 | 2023-02-03 | 广东美的制冷设备有限公司 | Equipment energy consumption analysis method and device, production system and storage medium |
| CN115796716A (en) * | 2023-02-13 | 2023-03-14 | 易通远见(北京)科技有限公司 | Building energy-saving management system based on Internet of things |
| CN116029866A (en) * | 2023-02-20 | 2023-04-28 | 南京鲜玩网络科技有限公司 | Intelligent park management system and method based on Internet |
| CN116610921A (en) * | 2023-06-14 | 2023-08-18 | 深圳市顶尖传诚科技有限公司 | Intelligent park information management system and method based on big data |
| CN116610921B (en) * | 2023-06-14 | 2024-02-09 | 深圳市顶尖传诚科技有限公司 | Intelligent park information management system and method based on big data |
| CN116846892A (en) * | 2023-07-04 | 2023-10-03 | 内蒙古达闻电子科技有限责任公司 | Intelligent energy consumption supervision system and method applying edge computing |
| CN117077899A (en) * | 2023-10-16 | 2023-11-17 | 四川邕合科技有限公司 | Intelligent park energy consumption anomaly monitoring and analyzing method, system, terminal and medium |
| CN117077899B (en) * | 2023-10-16 | 2023-12-22 | 四川邕合科技有限公司 | Intelligent park energy consumption anomaly monitoring and analyzing method, system, terminal and medium |
| CN117406685A (en) * | 2023-12-14 | 2024-01-16 | 无锡泰禾宏科技有限公司 | Intelligent control optimizing management system of building equipment suitable for green low-carbon building |
| CN117406685B (en) * | 2023-12-14 | 2024-03-08 | 无锡泰禾宏科技有限公司 | Intelligent control optimizing management system of building equipment suitable for green low-carbon building |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN114331000A (en) | Wisdom garden energy consumption management system based on artificial intelligence | |
| CN109670795B (en) | Engineering management system based on big data | |
| WO2023040575A1 (en) | Internet-of-things-based abnormality early warning analysis system and method for special operation site | |
| CN106655522B (en) | A kind of main station system suitable for electric grid secondary equipment operation management | |
| CN114063507B (en) | Remote equipment control system based on intelligent agriculture and control method thereof | |
| CN103903408B (en) | Method for early warning and system are investigated in equipment fault | |
| CN108024207A (en) | Flow of the people monitoring method based on three layers of prevention and control circle | |
| CN111830925B (en) | Intelligent energy consumption supervisory systems based on regeneration metal is smelted | |
| CN107748546A (en) | A kind of factory's intelligent inspection system based on LoRa technologies | |
| CN114239972A (en) | Campus energy efficiency and electrical safety management method and system based on artificial intelligence technology | |
| CN114565327B (en) | Wisdom energy management and control system based on thing networking | |
| CN112947328A (en) | Automatic control system for industrial furnace group | |
| CN112150335A (en) | Intelligent fire-fighting data visual monitoring system and monitoring method thereof | |
| CN111935219B (en) | Community Internet of things management system | |
| CN110751338A (en) | Construction and early warning method for heavy overload characteristic model of distribution transformer area | |
| CN116341796A (en) | Energy consumption monitoring and evaluating system and method | |
| CN117078017A (en) | Intelligent decision analysis system for monitoring power grid equipment | |
| CN109507960A (en) | A kind of integral intelligent manufacture system based on cloud platform | |
| CN110989042A (en) | Intelligent prediction method for highway fog-clustering risk | |
| CN116050716B (en) | Intelligent park management control platform based on Internet | |
| CN115858281A (en) | Energy consumption management system and method based on Internet of things | |
| CN114002965B (en) | Intelligent building's property management system based on thing networking | |
| CN113408764B (en) | Product online technical state management and control system based on digital twins | |
| CN112255959B (en) | Intelligent building safety management system based on big data | |
| CN114662058A (en) | Wireless station monitoring method and device |
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 |