CN110580030A - Pharmaceutical factory environment purification control system based on Internet of things - Google Patents
Pharmaceutical factory environment purification control system based on Internet of things Download PDFInfo
- Publication number
- CN110580030A CN110580030A CN201910961003.4A CN201910961003A CN110580030A CN 110580030 A CN110580030 A CN 110580030A CN 201910961003 A CN201910961003 A CN 201910961003A CN 110580030 A CN110580030 A CN 110580030A
- Authority
- CN
- China
- Prior art keywords
- sensor
- module
- processing module
- filter screen
- control system
- 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
- 238000000746 purification Methods 0.000 title claims abstract description 40
- 238000012545 processing Methods 0.000 claims abstract description 36
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 claims abstract description 26
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims abstract description 14
- 229910002091 carbon monoxide Inorganic materials 0.000 claims abstract description 14
- FVKGRHSPCZORQC-UHFFFAOYSA-N formaldehyde;toluene Chemical compound O=C.CC1=CC=CC=C1 FVKGRHSPCZORQC-UHFFFAOYSA-N 0.000 claims abstract description 11
- 238000005286 illumination Methods 0.000 claims abstract description 11
- 239000000428 dust Substances 0.000 claims abstract description 10
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims abstract description 8
- 238000006243 chemical reaction Methods 0.000 claims abstract description 7
- 230000000007 visual effect Effects 0.000 claims abstract description 4
- 230000002159 abnormal effect Effects 0.000 claims description 6
- 239000000843 powder Substances 0.000 claims description 6
- 238000013441 quality evaluation Methods 0.000 claims description 6
- QVFWZNCVPCJQOP-UHFFFAOYSA-N chloralodol Chemical compound CC(O)(C)CC(C)OC(O)C(Cl)(Cl)Cl QVFWZNCVPCJQOP-UHFFFAOYSA-N 0.000 claims description 3
- 238000004891 communication Methods 0.000 claims description 3
- 230000006855 networking Effects 0.000 claims 1
- 238000012544 monitoring process Methods 0.000 abstract description 9
- 239000003814 drug Substances 0.000 abstract description 2
- WSFSSNUMVMOOMR-UHFFFAOYSA-N Formaldehyde Chemical compound O=C WSFSSNUMVMOOMR-UHFFFAOYSA-N 0.000 description 6
- YXFVVABEGXRONW-UHFFFAOYSA-N Toluene Chemical compound CC1=CC=CC=C1 YXFVVABEGXRONW-UHFFFAOYSA-N 0.000 description 6
- 230000007613 environmental effect Effects 0.000 description 3
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 description 2
- 230000000875 corresponding effect Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000000034 method Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000000813 microbial effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011403 purification operation Methods 0.000 description 1
- 238000001303 quality assessment method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D46/00—Filters or filtering processes specially modified for separating dispersed particles from gases or vapours
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/31—From computer integrated manufacturing till monitoring
- G05B2219/31282—Data acquisition, BDE MDE
-
- 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
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
- Y02A50/20—Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters
- Y02A50/2351—Atmospheric particulate matter [PM], e.g. carbon smoke microparticles, smog, aerosol particles, dust
-
- 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
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
the invention discloses a pharmaceutical factory environment purification control system based on the Internet of things, which comprises intelligent nodes and a purification module; the intelligent node comprises a sensing module and a processing module; the sensing module consists of a plurality of sensors and a signal conversion circuit; the processing module comprises a main controller, an audible and visual alarm module and a network layer; the network layer comprises a wireless network, a server and a computer end/mobile phone; the purification module comprises a primary filter screen, an activated carbon filter screen, a HEPA filter screen, a Heimanpu filter screen, a humidifying filter screen, an exhaust device and a shielding curtain. The sensors of the sensing module comprise a digital temperature and humidity sensor, a methane sensor, a carbon monoxide sensor, a formaldehyde toluene sensor, a dust sensor and an illumination intensity measuring instrument; the acousto-optic alarm module of the processing module, the network layer of the processing module and the purification module are connected with the output end of the main controller of the processing module. The problem of current medicine factory building to air quality monitoring incomplete and do not manage is solved.
Description
Technical Field
The invention belongs to environment monitoring equipment of pharmaceutical factory buildings, and particularly relates to a pharmaceutical factory environment purification control system based on the Internet of things.
Background
Research experience for years at home and abroad shows that one important reason for causing quality problems such as microbial pollution of medicines is that the production environment does not meet the requirements, and how to keep the air quality in a pharmaceutical factory stable and excellent for a long time is a key topic. In addition, the environmental safety of the pharmaceutical factory has a great influence on workers and people living around the factory building, and therefore, monitoring and purifying the indoor air of the pharmaceutical factory is of great significance to daily life.
In the prior art, the indoor air quality detection and regulation device of a pharmaceutical factory is single, generally only conventional temperature and humidity detection is carried out, certain harmful gases such as carbon monoxide and sulfur dioxide which exist in the factory building all the time are not involved, the reliability of data collected by sensor nodes is not evaluated, the data quality cannot be guaranteed, and the collected overproof quality data which are not qualified alive are not processed.
Therefore, the multi-node pharmaceutical factory environment purification control system based on the internet of things is provided to solve the problems, so that the environmental data in the pharmaceutical factory can be better monitored, the real-time collection and transmission of the air quality data can be realized, a user can know and control the indoor air quality condition in real time through a computer or a mobile phone, the reliability of the collected data is evaluated, and the influence of the unreliable data on the analysis work is eliminated.
disclosure of Invention
The invention aims to provide a pharmaceutical factory environment purification control system based on the Internet of things, which is used for solving the problems that the existing pharmaceutical factory building cannot monitor the air quality completely and is not treated.
In order to achieve the technical purpose, the technical scheme adopted by the invention is as follows:
A pharmaceutical factory environment purification control system based on the Internet of things comprises intelligent nodes and a purification module;
The intelligent node comprises a sensing module and a processing module; the sensing module consists of a plurality of sensors and a signal conversion circuit; the processing module comprises a main controller, an audible and visual alarm module and a network layer; the network layer comprises a wireless network, a server and a computer end/mobile phone;
The purification module comprises a primary filter screen, an activated carbon filter screen, a HEPA filter screen, a Heimanpu filter screen, a humidifying filter screen, an exhaust device and a shielding curtain.
Preferably, the sensor of the sensing module comprises a digital temperature and humidity sensor, a methane sensor, a carbon monoxide sensor, a formaldehyde and toluene sensor, a dust sensor and an illumination intensity measuring instrument; the digital temperature and humidity sensor is directly connected with the input end of the main controller of the processing module; the methane sensor, the carbon monoxide sensor, the formaldehyde toluene sensor, the dust sensor and the illumination intensity measuring instrument are connected with the input end of the processing module main controller through the A/D conversion module.
preferably, the sound and light alarm module of the processing module, the network layer of the processing module and the purification module are connected with the output end of the main controller of the processing module.
Preferably, the main controller of the processing module is a circuit module having an STM32F104 chip as a core.
preferably, the digital temperature and humidity sensor is a DHT11 temperature and humidity sensor; the methane sensor adopts an MQ-4 methane sensor; the carbon monoxide sensor adopts an MQ-9 carbon monoxide sensor; the formaldehyde toluene sensor adopts MS1100 formaldehyde toluene sensor powder; the powder sensor adopts a Sharp GP2Y1010AU dust sensor; the illumination intensity measuring instrument adopts a DT-1300 photometer.
Preferably, the network layer wireless network of the processing module adopts a LORA scheme, and the module selects an ATK-LORA-01 wireless serial port communication module SX 1278.
preferably, the processing module collects sensor data and performs quality evaluation on the air quality according to the data, and a local abnormal factor algorithm is adopted in a quality evaluation algorithm.
the invention has the following beneficial effects:
according to the invention, through the arrangement of the acquisition sensors of the monitoring points, a plurality of air quality parameters in a factory building can be synchronously monitored in all directions, so that continuous and various monitoring data can be ensured; the main control unit outputs processed monitoring data to the server and the control terminal through a wireless network, and uses a local abnormal factor algorithm to perform quality assessment on the data, give more accurate reference value to workers, so that the purification operation can be performed manually or automatically, and the data are further output to the alarm device, so that when certain indoor air index exceeds a set threshold value, the workers can be reminded by using sound and light, in addition, the monitoring on illumination intensity is increased, the purification is realized through a shielding curtain, and when the indoor air is bad and the purification device needs a long time to purify to a certain degree, the exhaust device is started immediately, the indoor fresh air volume is increased, so that the concentration of a pollution source is reduced, and the monitoring and purification process of the indoor air quality is realized.
drawings
FIG. 1 is a system operation flow chart of an environmental purification control system of a pharmaceutical factory based on the Internet of things;
FIG. 2 is a schematic diagram of a single measurement system of the pharmaceutical factory environment purification control system based on the Internet of things according to the present invention;
FIG. 3 is a flow chart of a local abnormal factor algorithm of the pharmaceutical factory environment purification control system based on the Internet of things.
Detailed Description
Embodiments of the present invention are described in further detail below with reference to the accompanying drawings.
A pharmaceutical factory environment purification control system based on the Internet of things comprises intelligent nodes and a purification module;
The intelligent node comprises a sensing module and a processing module; the sensing module consists of a plurality of sensors and a signal conversion circuit; the processing module comprises a main controller, an audible and visual alarm module and a network layer; the network layer comprises a wireless network, a server and a computer end/mobile phone;
The purification module comprises a primary filter screen, an activated carbon filter screen, a HEPA filter screen, a Heimanpu filter screen, a humidifying filter screen, an exhaust device and a shielding curtain.
In specific implementation, the sensors of the sensing module comprise a digital temperature and humidity sensor, a methane sensor, a carbon monoxide sensor, a formaldehyde and toluene sensor, a dust sensor and an illumination intensity measuring instrument; the digital temperature and humidity sensor is directly connected with the input end of the main controller of the processing module; the methane sensor, the carbon monoxide sensor, the formaldehyde toluene sensor, the dust sensor and the illumination intensity measuring instrument are connected with the input end of the processing module main controller through the A/D conversion module.
in specific implementation, the acousto-optic alarm module of the processing module, the network layer of the processing module and the purification module are connected with the output end of the main controller of the processing module.
In a specific implementation, the main controller of the processing module is a circuit module with an STM32F104 chip as a core.
In specific implementation, the digital temperature and humidity sensor adopts a DHT11 temperature and humidity sensor; the methane sensor adopts an MQ-4 methane sensor; the carbon monoxide sensor adopts an MQ-9 carbon monoxide sensor; the formaldehyde toluene sensor adopts MS1100 formaldehyde toluene sensor powder; the powder sensor adopts a Sharp GP2Y1010AU dust sensor; the illumination intensity measuring instrument adopts a DT-1300 photometer.
In specific implementation, a network layer wireless network of the processing module adopts a LORA scheme, and the module selects an ATK-LORA-01 wireless serial port communication module SX 1278.
When the method is specifically implemented, the network layer is used for sending the acquired data to the user terminal in real time, so that the user can conveniently master the indoor environment condition at any time and make corresponding measures. The server can compare and store the data acquired in the near period of time to judge whether the purification device needs to be started or not, and judge whether the device of the purification module needs to be replaced or cleaned or not according to the purification times and the purification degree in the near period of time; the computer/mobile phone can check indoor air quality and specific data in real time, and can manually start the purification device at the computer/mobile phone end, and in addition, a certain time period can be set, and the purification module can be automatically started at the computer/mobile phone end when the indoor environment is not good and the purification device is not started.
And the sound and light alarm module is used for giving an alarm when the monitored air data exceeds a normal value so as to remind a worker.
in specific implementation, the processing module collects sensor data, quality evaluation is carried out on the air quality according to the data, a local abnormal factor algorithm is adopted by a quality evaluation algorithm, the algorithm analyzes, summarizes and summarizes the outlier degree of each data point through a series of defined point-to-point relations, a proper outlier judgment threshold value is selected according to an experimental result, and the final result of outlier analysis depends on the selection of a user on the values of relevant factors. The following introduces the relevant definition of the local anomaly factor algorithm:
definition 1: distance d of point pk(p) is defined as dk(p) ═ d (p, o), d (p, o) is the distance between two points p and o, the kth distance of p, that is, the distance from the kth point of p, excluding p, and the following two conditions are satisfied:
a) At least k points o 'epsilon C { x ≠ p } in the set, which do not include p, and d (p, o') is less than or equal to d (p, o);
b) At most k-1 points in the set, o 'epsilon C { x ≠ p } excluding p, satisfying d (p, o') < d (p, o).
Definition 2: k-th distance neighborhood N of point pk(p), all points within the kth distance of p, including the kth distance, so the number of points in the kth neighborhood of p, Nk(p)|≥k。
Definition 3: the k-th reachable distance (rd) from point o to point p is defined as:
rd＝max{k-distance(o)，d(p，o)} (1)
Is the maximum of the distance between two data points and the kth distance of data point o.
Definition 4: the local achievable density of data points p (lrd). The local reachable density of a data point p is the data point p and its Nk(p) the inverse of the mean of the reachable distances of all other data points within the set.
Definition 5: the Local Outlier Factor (LOF) for a point p represents the neighborhood of point N for point pk(p) an average of a ratio of the local achievable density of (p) to the local achievable density of point p.
as shown in equation (3), the smaller the local reachable density of the data point p is, the larger the local outlier factor is, the higher the probability that the data point is an outlier is, and vice versa. And finishing the evaluation of the data quality of the nodes by calculating the non-outlier rate of the node data.
The system comprises the following specific working steps:
Step 1, determining a target data set acquired by a number of sensors;
Selecting a proper parameter k, wherein an excessively large k value can enable normal data caused by an emergency environment event to be isolated, so that the normal data is judged to be an outlier data point, the accuracy of the data set can be lower than the actual accuracy, similarly, an excessively small k value can enable the accuracy of the data set to be higher than the actual accuracy, and the value of the k is 5% of the total amount of the target data set under a general condition;
Step 3, calculating an outlier factor of each data point in the target data set;
And 4, evaluating the reliability of the data collected by the node by integrating the non-outlier rate of different data of each node.
Compared with unprocessed data, the reliability of the data quality acquired by a certain sensor node can be preliminarily judged through a local abnormal factor algorithm, a certain reference basis is provided for the later-stage data processing of researchers, and the result can be used for reference through the design of the sensor node placement position.
The system generally monitors the concentration of each index commonly seen in the indoor space in real time, and various devices can manually or automatically make corresponding actions through network connection. When the indoor air is bad and the purifying device needs a long time for purifying to a certain degree, the exhaust device is started immediately, and the indoor fresh air quantity is increased to reduce the concentration of a pollution source, so that the monitoring and purifying process of the indoor air quality is realized.
the above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.
Claims (7)
1. The utility model provides a pharmaceutical factory environment purification control system based on thing networking which characterized in that: the control system comprises an intelligent node and a purification module;
The intelligent node comprises a sensing module and a processing module; the sensing module consists of a plurality of sensors and a signal conversion circuit; the processing module comprises a main controller, an audible and visual alarm module and a network layer; the network layer comprises a wireless network, a server and a computer end/mobile phone;
The purification module comprises a primary filter screen, an activated carbon filter screen, a HEPA filter screen, a Heimanpu filter screen, a humidifying filter screen, an exhaust device and a shielding curtain.
2. The pharmaceutical factory environment purification control system based on the Internet of things according to claim 1, wherein: the sensors of the sensing module comprise a digital temperature and humidity sensor, a methane sensor, a carbon monoxide sensor, a formaldehyde toluene sensor, a dust sensor and an illumination intensity measuring instrument; the digital temperature and humidity sensor is directly connected with the input end of the main controller of the processing module; the methane sensor, the carbon monoxide sensor, the formaldehyde toluene sensor, the dust sensor and the illumination intensity measuring instrument are connected with the input end of the processing module main controller through the A/D conversion module.
3. the pharmaceutical factory environment purification control system based on the Internet of things according to claim 1, wherein: and the acousto-optic alarm module of the processing module, the network layer of the processing module and the purification module are connected with the output end of the main controller of the processing module.
4. The pharmaceutical factory environment purification control system based on the Internet of things as claimed in claim 2, wherein: the main controller of the processing module is a circuit module taking an STM32F104 chip as a core.
5. The pharmaceutical factory environment purification control system based on the Internet of things as claimed in claim 2, wherein: the digital temperature and humidity sensor adopts a DHT11 temperature and humidity sensor; the methane sensor adopts an MQ-4 methane sensor; the carbon monoxide sensor adopts an MQ-9 carbon monoxide sensor; the formaldehyde toluene sensor adopts MS1100 formaldehyde toluene sensor powder; the powder sensor adopts a Sharp GP2Y1010AU dust sensor; the illumination intensity measuring instrument adopts a DT-1300 photometer.
6. the pharmaceutical factory environment purification control system based on the Internet of things according to claim 1, wherein: the network layer wireless network of the processing module adopts an LORA scheme, and the module selects an ATK-LORA-01 wireless serial port communication module SX 1278.
7. the pharmaceutical factory environment purification control system based on the Internet of things according to claim 1, wherein: the processing module collects sensor data and carries out quality evaluation on the air quality according to the data, and a local abnormal factor algorithm is adopted in a quality evaluation algorithm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910961003.4A CN110580030A (en) | 2019-10-11 | 2019-10-11 | Pharmaceutical factory environment purification control system based on Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910961003.4A CN110580030A (en) | 2019-10-11 | 2019-10-11 | Pharmaceutical factory environment purification control system based on Internet of things |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110580030A true CN110580030A (en) | 2019-12-17 |
Family
ID=68814493
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910961003.4A Pending CN110580030A (en) | 2019-10-11 | 2019-10-11 | Pharmaceutical factory environment purification control system based on Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110580030A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111323544A (en) * | 2020-03-27 | 2020-06-23 | 沈阳沃尔鑫环保科技有限公司 | Calibration method and system based on miniature air quality monitoring instrument |
| CN112241154A (en) * | 2020-10-15 | 2021-01-19 | 杭州澳亚生物技术有限公司 | Intelligent monitoring management system for GMP workshop |
| CN112255983A (en) * | 2020-10-24 | 2021-01-22 | 陈彦均 | Big data processing method and production data processing center based on cosmetic production |
| CN115235005A (en) * | 2022-07-15 | 2022-10-25 | 浙江日鼎涂装科技有限公司 | Air conditioning system of self-adaptation coating line environment |
| CN116045438A (en) * | 2023-01-09 | 2023-05-02 | 江苏悦达绿色建筑科技有限公司 | Fresh air system of three-constant intelligent house and control method thereof |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203376611U (en) * | 2013-05-22 | 2014-01-01 | 宁波市镇海星科智能技术有限公司 | Intelligent environmental monitoring system based on Zigbee network |
| CN104654452A (en) * | 2013-11-22 | 2015-05-27 | 西安联控电气有限责任公司 | Multifunctional indoor air quality monitoring system |
| CN105322519A (en) * | 2015-11-02 | 2016-02-10 | 湖南大学 | Big data fusion analysis and running state monitoring method for intelligent power distribution network |
| CN105737341A (en) * | 2016-03-15 | 2016-07-06 | 四川理工学院 | Indoor air detection and purification intelligent home furnishing based on internet of things and control method |
| CN107528904A (en) * | 2017-09-01 | 2017-12-29 | 星环信息科技（上海）有限公司 | Method and apparatus for data distribution formula abnormality detection |
| CN109726553A (en) * | 2019-01-03 | 2019-05-07 | 湖南大学 | A kind of Denial of Service attack detection method at a slow speed based on SNN-LOF algorithm |
| CN210776304U (en) * | 2019-10-11 | 2020-06-16 | 南京铁道职业技术学院 | Pharmaceutical factory environment purification control system based on Internet of things |
-
2019
- 2019-10-11 CN CN201910961003.4A patent/CN110580030A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN203376611U (en) * | 2013-05-22 | 2014-01-01 | 宁波市镇海星科智能技术有限公司 | Intelligent environmental monitoring system based on Zigbee network |
| CN104654452A (en) * | 2013-11-22 | 2015-05-27 | 西安联控电气有限责任公司 | Multifunctional indoor air quality monitoring system |
| CN105322519A (en) * | 2015-11-02 | 2016-02-10 | 湖南大学 | Big data fusion analysis and running state monitoring method for intelligent power distribution network |
| CN105737341A (en) * | 2016-03-15 | 2016-07-06 | 四川理工学院 | Indoor air detection and purification intelligent home furnishing based on internet of things and control method |
| CN107528904A (en) * | 2017-09-01 | 2017-12-29 | 星环信息科技（上海）有限公司 | Method and apparatus for data distribution formula abnormality detection |
| CN109726553A (en) * | 2019-01-03 | 2019-05-07 | 湖南大学 | A kind of Denial of Service attack detection method at a slow speed based on SNN-LOF algorithm |
| CN210776304U (en) * | 2019-10-11 | 2020-06-16 | 南京铁道职业技术学院 | Pharmaceutical factory environment purification control system based on Internet of things |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111323544A (en) * | 2020-03-27 | 2020-06-23 | 沈阳沃尔鑫环保科技有限公司 | Calibration method and system based on miniature air quality monitoring instrument |
| CN112241154A (en) * | 2020-10-15 | 2021-01-19 | 杭州澳亚生物技术有限公司 | Intelligent monitoring management system for GMP workshop |
| CN112255983A (en) * | 2020-10-24 | 2021-01-22 | 陈彦均 | Big data processing method and production data processing center based on cosmetic production |
| CN112255983B (en) * | 2020-10-24 | 2021-12-21 | 陈彦均 | Big data processing method and production data processing center based on cosmetic production |
| CN115235005A (en) * | 2022-07-15 | 2022-10-25 | 浙江日鼎涂装科技有限公司 | Air conditioning system of self-adaptation coating line environment |
| CN116045438A (en) * | 2023-01-09 | 2023-05-02 | 江苏悦达绿色建筑科技有限公司 | Fresh air system of three-constant intelligent house and control method thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110580030A (en) | Pharmaceutical factory environment purification control system based on Internet of things | |
| CN201594088U (en) | Novel indoor wireless air quality monitor | |
| CN110675006A (en) | Indoor air quality real-time monitoring and formaldehyde attenuation prediction system | |
| CN109827298B (en) | Intelligent control method of fresh air fan and fresh air fan system | |
| CN108168022A (en) | intelligent air purifying system | |
| CN113110080B (en) | Household environment intelligent monitoring, regulation and control management cloud system based on Internet of things and cloud computing | |
| CN111238574A (en) | Environmental monitoring system based on Internet of things | |
| CN212538183U (en) | Movable intelligent room air purification system | |
| CN110864938A (en) | Intelligent air environment monitoring management system for building | |
| CN110108010A (en) | Dense crowd indoor air quality-monitoring and improvement system | |
| CN210776304U (en) | Pharmaceutical factory environment purification control system based on Internet of things | |
| CN109282427A (en) | A kind of detection method and device in strainer service life | |
| CN113687609A (en) | Intelligent monitoring system and monitoring method for Internet of things applied to abnormal environment | |
| CN107168095A (en) | A kind of intelligent housing system | |
| CN111010681B (en) | Intelligent medical monitoring system based on ZigBee network | |
| CN207585659U (en) | A kind of house air monitoring device based on Zigbee networkings | |
| CN116933951A (en) | Low-carbon park carbon emission monitoring system and method based on big data | |
| CN206057275U (en) | A kind of room air detection means | |
| CN108966171B (en) | Regional air pollutant concentration standard exceeding early warning system | |
| CN206399481U (en) | Automatic water quality monitoring system | |
| CN202838615U (en) | Gas alarm | |
| CN114995256A (en) | Workshop environment monitoring device and monitoring method based on digital twins | |
| CN113726559A (en) | Artificial intelligence network-based security analysis early warning model | |
| CN207963055U (en) | A kind of broken smoke contamination monitoring processing system of office operation | |
| CN209623773U (en) | A kind of social worker's service management system for service platform of supporting parents |
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 |