KR102470006B1 - Data logger system and Method for Operation and Maintenance of warer quality measuring equipment - Google Patents

Abstract

The present invention relates to an intelligent data logger system which performs a maintenance function of a water quality measuring device comprising a deep learning module and an artificial intelligence control module to optimally operate and manage the water quality measuring device. The intelligent data logger system comprises: a meteorological data collection unit collecting meteorological data; a water quality data collection unit collecting operation time information and water quality data from at least one water quality measuring device; a data analysis unit analyzing data required for maintenance of the water quality measuring device for optimal water quality conditions for each water quality measuring device by using the meteorological data collected by the meteorological data collection unit and the operation time information and water quality data collected by the water quality data collection unit; a database unit databasing the data required for maintenance of each water quality measuring device in a time-series manner based on the analysis results of the data analysis unit; and a machine learning unit learning based on the data databased in the database unit. Provided are the intelligent data logger system and method performing the maintenance function of the water quality measuring device capable of collecting and managing the intelligent data which can secure the reliability of the measured values of the water quality measuring device, ease of maintenance, economic feasibility, eco-friendliness, durability, and safety.

Description

Intelligent data logger system and method for performing maintenance of water quality measuring equipment {Data logger system and method for Operation and Maintenance of warer quality measuring equipment}

The present invention relates to an intelligent data logger system and method for performing a maintenance function of water quality measurement equipment, and more particularly, to an intelligent data logger system and method including a deep learning module and an artificial intelligence control module to optimally operate and manage water quality measurement equipment. It relates to an intelligent data logger system that performs maintenance functions of measuring equipment.

In recent years, many disasters, disasters, etc. have occurred due to climate change, etc., and have caused many problems in the natural environment.

In order to detect changes in the natural environment, since the related system is installed in an area where power cannot be supplied, it is based on building a system that operates with a battery. However, in order to do so, a system control and communication method supporting low power must be provided.

Existing systems that operate with batteries mainly support only uplink data transmission for low power consumption, or provide a method of receiving downstream data by unconditionally waiting for a certain period of time at the sensor node when supporting downlink data transmission function, but this method consumes battery power. There are many, and it has the problem of having to change the battery frequently.

Therefore, by analyzing and learning/predicting real-time water quality data, meteorological information, and operation time, easiness of maintenance and economic feasibility are provided by predicting the time-by-season, year-by-month, day-of-week, time-of-day, time-by-measurement equipment item, and consumable replacement cycle by part. Needs to be.

KR 10-0419239 B1 KR 10-2016-0098731 A

The present invention was derived from such a technical background, and the reliability of the measured values of the water quality measuring equipment, the ease of maintenance, economic feasibility, eco-friendliness, durability, safety, and intelligent data collection and management that can be secured. Its purpose is to provide an intelligent data logger system and method for performing maintenance functions.

In addition, an intelligent data logger system that performs the maintenance function of water quality measuring equipment that derives data that can be used as basic data for calculating annual maintenance costs based on A/S inspection cost calculations for each water quality measuring equipment and regular replacement cycle of major parts and methods can be provided.

The present invention for achieving the above object includes the following configuration.

That is, the intelligent data logger system performing the maintenance function of the water quality measurement equipment according to an embodiment of the present invention includes a meteorological data collection unit that collects weather data, and operation time information and water quality data collected from at least one or more water quality measurement equipment. Water quality data collection unit, meteorological data collected by the meteorological data collection unit, operation time information and water quality data collected by the water quality data collection unit are used for maintenance of water quality measurement equipment for optimal water quality conditions for each water quality measurement equipment. A data analysis unit that analyzes necessary data, a database unit that time-sequentially databases data necessary for maintenance by water quality measurement equipment based on the analysis results from the data analysis unit, and a database unit based on the data databased in the database unit. Including a machine learning unit that learns as, but the data analysis unit analyzes the data based on the machine learning result from the machine learning unit.

On the other hand, the intelligent data logger method performing the maintenance function of the water quality measuring equipment performed in the intelligent data logger system performing the maintenance function of the water quality measuring equipment is collecting meteorological data, operating time from at least one water quality measuring equipment Collecting information and water quality data; analyzing data required for maintenance of water quality measuring equipment for optimal water quality conditions for each water quality measuring equipment using the collected meteorological data, operation time information, and water quality data; Based on the results, time-sequentially creating a database of data necessary for maintenance of each water quality measurement equipment and machine learning the databased data, wherein the analyzing step is based on the machine learning result in the machine learning step. It is characterized by analyzing data based on.

According to the present invention, the reliability of the measured values of the water quality measurement equipment, ease of maintenance, economic feasibility, eco-friendliness, durability, safety, intelligent data collection and management that can be secured, and intelligent data that performs the maintenance function of the water quality measurement equipment An effect that can provide a logger system and method is derived.

In addition, an intelligent data logger system that performs the maintenance function of water quality measuring equipment that derives data that can be used as basic data for calculating annual maintenance costs based on A/S inspection cost calculations for each water quality measuring equipment and regular replacement cycle of major parts and methods can be provided.

1 is an exemplary view for explaining the overall operation of an intelligent data logger system performing a maintenance function of water quality measuring equipment according to an embodiment of the present invention.
2 is a block diagram showing the configuration of an intelligent data logger system according to an embodiment of the present invention.
3 is a flowchart of an intelligent data logger method for performing a maintenance function of water quality measuring equipment according to an embodiment of the present invention.

It should be noted that technical terms used in the present invention are only used to describe specific embodiments and are not intended to limit the present invention. In addition, technical terms used in the present invention should be interpreted in terms commonly understood by those of ordinary skill in the art to which the present invention belongs, unless specifically defined otherwise in the present invention, and are excessively inclusive. It should not be interpreted in a positive sense or in an excessively reduced sense.

Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings.

1 is an exemplary view for explaining the overall operation of an intelligent data logger system performing a maintenance function of water quality measuring equipment according to an embodiment of the present invention.

In one embodiment, the intelligent data logger system 10 may process and manage data transmitted and received from the water quality data meter and auxiliary equipment.

Specifically, the intelligent data logger system 10 according to an embodiment complies with automatic water quality measurement network communication standards (EMC 2003, EMC 2007, KECO 2013, etc.), and provides a data transmission/reception status and result inquiry function. In addition, it is equipped with a screen output function in the original text and interpretation format of data transmission and reception communication standards, and performs a function of sending status information in case of an alarm occurrence or transmission/reception failure, setting and managing measurement items, measurement stations, and auxiliary equipment status information, operation management, collection, Transmission and alarm functions can be performed.

In addition, the intelligent data logger system 10 according to an embodiment further performs a function of executing a remote command received from an external server and returning the result.

At this time, the automatic water quality measurement network communication standards (EMC 2003, EMC 2007, KECO2013, etc.) are followed, and the types of remote commands are general random sampling, VOC random sampling, instantaneous data request, stored data request, remote calibration, calibration value search, D/ It can include L initialization, water sampling pump control, microbial cell change, item status change, etc. Water quality measurement equipment using its own communication standard can be processed through consultation on work contents, and provides remote command execution contents and result inquiry function. You can output the original text of the communication standard for sending and receiving remote commands and the screen of the interpretation form. It is preferable that the remote command processing is implemented within a few seconds and the result can be checked within a few seconds by the user of the automated water quality measurement network.

In addition, the intelligent data logger system 10 according to an embodiment operates and manages a measurement station that operates water quality measurement equipment, and stores measurement results collected therefrom as data files.

To this end, in detail, the function of adding and deleting measuring stations, measuring devices and auxiliary equipment, the current status inquiry function of measured values in various formats in the form of tables and graphs, log-in to the communication server in case of inspection of measuring points and alarms, operation inspection log, emergency dispatch status and pollution warning measures function, service setting, measuring station environment setting function, quality control, quality inspection and uncertainty inquiry function, status code reclassification and inquiry function for each function of measuring station, quality control, quality inspection function, program semi-automatic and manual update using update server It performs various log storage and inquiry functions related to functions, data collection, storage, and transmission, and system status (CPU, HDD, memory usage, etc.) monitoring function.

In addition, including the monitoring station's own alarm program that automatically operates when communication with the communication server is disconnected for more than the standard time, alarm setting and inquiry functions according to management standards can be improved. Alarm and message transmission history search function and alarm notification can be notified when an abnormal specific value (zero value, holding value, etc.) continues for a certain period of time.

The intelligent data logger system 10 according to an embodiment is equipped with an AI function including a deep learning module and an artificial intelligence control module to optimally operate and manage the water quality measurement equipment.

Specifically, it is characterized by generating pattern data for each water quality measurement equipment based on real-time water quality data, weather information, and operation time, and supports AI-based failure occurrence and replacement cycle prediction to regularly perform inspection and calibration work (zero point/span calibration). can In addition, it is possible to inspect various tubes for transporting samples and reagents, and to predict the state of tubing and quantitative injection.

In addition, it predicts the state of sample and reagent injection required for water quality measurement, and predicts the light source and detector check and replacement cycle. It predicts the washing water, reagent amount, and contamination of pure water to provide replenishment time for various reactive reagents, and provides error prediction and replacement cycle information by checking various sensors.

In addition, with equipment with severe data fluctuations due to fluctuations in microvoltage (mV), it checks the grounding status and power status to perform the function of checking the power supply status, checks whether the stored values are modified, and periodically arranges and measures the slope and offset values. Data can be checked and managed.

The intelligent data logger system 10 according to an embodiment measures and monitors water pollution in real time by installing and operating an automatic water quality measurement network, that is, multiple treatment plants, in major rivers and lakes nationwide, thereby monitoring water pollution accidents It can be linked to the National Automated Water Quality Monitoring System, a comprehensive water environment monitoring system to protect water sources and manage water quality in rivers with prompt response measures in the event of a pollution accident.

And the intelligent data logger system 10 is a system that remotely monitors the status of water pollutants discharged from water quality TMS-attached workplaces across the country 24 hours a day. It can be provided to related organizations such as the Ministry of Environment.

2 is a block diagram showing the configuration of an intelligent data logger system according to an embodiment of the present invention.

As shown in FIG. 2 , the intelligent data logger system 10 according to an embodiment includes a communication unit 110, a weather data collection unit 120, a water quality data collection unit 130, a data analysis unit 140, and a database unit 150. , It includes a machine learning unit 160, an artificial intelligence control unit 170, a cost management unit 180 and a storage unit 190.

The communication unit 110 communicates with any internal component or at least one external terminal through a wired/wireless communication network. Here, wireless Internet technologies include Wireless LAN (WLAN), DLNA (Digital Living Network Alliance), Wireless Broadband (Wibro), WiMAX (World Interoperability for Microwave Access: Wimax), HSDPA (High Speed Downlink Packet Access) ), High Speed Uplink Packet Access (HSUPA), IEEE 802.16, Long Term Evolution (LTE), Long Term Evolution-Advanced (LTE-A), Wireless Mobile Broadband Service (WMBS), etc. , and the communication unit 110 transmits and receives data according to at least one wireless Internet technology within a range including Internet technologies not listed above.

In addition, short-range communication technologies include Bluetooth, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, and Near Field Communication (NFC). , Ultra Sound Communication (USC), Visible Light Communication (VLC), Wi-Fi, Wi-Fi Direct, and the like may be included. In addition, wired communication technologies may include power line communication (PLC), USB communication, Ethernet, serial communication, optical/coaxial cables, and the like.

At least one arbitrary external terminal may be one of the Environment Management Corporation server 20 , at least one treatment plant server 30 , and the manager terminal 40 .

The weather data collection unit 120 collects weather data. In an embodiment, the meteorological data collection unit 120 collects meteorological data detected by one of a wind direction sensor, a wind speed sensor, a rainfall sensor, an air circulator air temperature sensor, and a rainfall sensor. In addition, weather data may be collected from the Korea Meteorological Administration server.

The weather data collection unit 120 may collect weather information data obtained by measuring weather changes every second for 24 hours. Weather information data measured in units of a predetermined minute or hour may be received and collected.

The water quality data collection unit 130 collects operation time information and water quality data from at least one water quality measurement device. The water quality data collection unit 130 collects water quality data measured by water quality measurement equipment interlocked with each other from one or more treatment plant servers 30 .

The water quality data collection unit 130 collects, for each treatment plant server 30, the model name, approval date and approval number of each water quality measuring device linked to the treatment plant server 30, information on the quantity of water quality measuring equipment connected to each treatment plant server 30, and the like. do.

The water quality data collection unit 130 may further collect this information when a notification is generated according to an automatic notification function from a water quality measurement device having a built-in specification information for each water quality measuring device and an automatic consumable replacement cycle notification function. In addition, self-diagnosis results and automatic dilution function execution information can be further collected from water quality measurement equipment equipped with a self-diagnosis and automatic reagent dilution function.

In addition, in the case of water quality measuring equipment that needs to maintain a temperature above a certain value, such as a volatile organic compound (VOCs) measuring equipment, temperature information of a space in which the corresponding water quality measuring equipment is installed may be further collected.

In one embodiment, the water quality data collection unit 130 basically collects measured values for water temperature, pH (hydrogen ion concentration), DO (dissolved oxygen), EC (electrical conductivity), and TOC (total organic carbon) items. . In addition, biomonitoring (daphnia, algae photosynthesis, microbial fuel cells, sulfur-oxidizing microorganisms, luminescent bacteria), VOCs (volatile organic compounds), TN (total nitrogen), NH ₃ -N ammonia nitrogen), NO ₃ -N ( Nitrate nitrogen), TP (total phosphorus), PO ₄ -P (phosphate phosphorus), Chl-a (chlorophyll-a), phenol, turbidity, or heavy metals (Cu, Pb, Zn, Cd). do.

VOCs (Volatile Organic Compounds) include Benzene, Carbon Tetrachloride, Ethylbenzene, (o,m,p)Xylene, Toluene, Dichlorometane, Tetrachloroehylene, Trichloroethylene, and 1,1,1-trichlororethane.

Preferably, factory wastewater collects measured values for VOCs, biomonitoring, heavy metals, and phenol according to settings from the manager terminal 40, and collects measured values for NH3-N and NO3-N in the case of manure and livestock wastewater In case of appeal, the measured values for Chl-a, PO4-P, T-N, and T-P are collected. However, it is not limited thereto and is interpreted to cover a technical configuration for collecting various information for measuring water quality.

Additionally, the pollutant data collection unit may further receive area information, pollutant information, and surrounding situation information in order to determine the degree of environmental pollution in a predetermined area. At this time, the pollutant information includes at least one of ozone (O3), carbon monoxide (CO), sulfur dioxide (SO ₂ ), ammonia (NH ₃ ), nitrogen oxide (NOx), nitrate (NO ₃ ), fine dust, and mercury. It may be used as a contaminant.

The pollutant data collection unit includes information on heavy metals contained in the air within a predetermined area, information on ions contained in the air within a predetermined area, information on the size of fine dust particles contained in the air within the predetermined area, and At least one piece of information about a visible distance within a predetermined area may be collected as information about a surrounding situation.

The data analysis unit 140 uses the meteorological data collected by the meteorological data collection unit 120, the operation time information and the water quality data collected by the water quality data collection unit 130, and water quality for optimum water quality conditions for each water quality measurement equipment. Analyze data required for maintenance of measuring equipment.

The data analysis unit 140 generates pattern data for each water quality meter based on real-time water quality data, meteorological information, and operation time. Span Calibration) to derive data to support.

In addition, the data analyzer 140 derives inspection data of various tubes from data necessary for maintenance for each water quality measuring equipment collected by the water quality data collection unit 130 . In addition, it inspects samples and reagent transfer tubes, and derives results capable of predicting the tubing status and whether or not to inject a fixed amount.

In addition, the data analyzer 140 predicts sample and reagent injection states through inspection of the injection device, and analyzes information for checking the light source and detector of the water quality measuring device and predicting a replacement cycle. In order to check the condition of the reaction reagent, information for confirming the amount of washing water and reagent and predicting whether pure water is contaminated may be analyzed, and replenishment timing of various reagents may be provided.

The data analyzer 140 checks the sensor, predicts the occurrence of an error and provides replacement cycle information, and analyzes information capable of confirming the grounding status and power supply status of equipment with severe data fluctuations due to fluctuations in microvoltage (mV).

In addition, the data analyzer 140 may check measurement data pre-stored in the storage 190, check whether values are modified, and periodically arrange slope and offset values.

Additionally, the data analyzer 140 may further analyze the information received by the pollutant data collection unit to further analyze data required for maintenance of the air pollution measurement equipment. In addition, the performance or lifespan of the water quality measurement equipment can be more accurately analyzed by further reflecting the degree of air pollution.

In one aspect of the present invention, the data analysis unit 140 generates pattern data for each water quality measuring device using collected weather data, operation time information, and water quality data.

In addition, using the generated pattern data, it is possible to perform analysis on whether or not a failure has occurred, the replacement cycle of parts and samples, and whether or not the time for calibration work has arrived.

The data analysis unit 140 is not simply limited to the consumables replacement cycle or inspection items basically provided by the manufacturer of the water quality measurement equipment, but rather reflects the meteorological data of the location where the water quality measurement equipment is installed, the water pollution status, or the air pollution status to exchange consumables. Accuracy for periodic or inspection items can be further improved.

The data analysis unit 140 may provide the analyzed results to the Environment Management Corporation server 20 .

In a characteristic aspect of the present invention, the data analysis unit 140, as a result of self-analysis, determines whether the water quality data deviate from the preset standards, whether there is a failure, the replacement cycle of parts and samples, and the calibration period of the corresponding water quality measurement equipment. A notification message is sent to the manager terminal 40 possessed by the manager in charge.

The database unit 150 builds a database of data necessary for maintenance of each water quality measurement equipment in a time-series manner based on the analysis result of the data analysis unit 140 .

In one embodiment, the database unit 150 stores calibration work time arrival information for each water quality measurement equipment, consumables, parts, or sample replacement cycle information, water quality data measurement result values, and information on whether or not a failure has occurred to form a database. ) is stored in

At this time, information on time units or necessary items to be converted into a database may be set from the manager terminal 40 . Items for each equipment can be added or deleted.

The machine learning unit 160 learns based on data databased in the database unit 150. And the data analysis unit 140 may analyze the data based on the machine learning result in the machine learning unit.

The machine learning unit 160 may classify parts included in the water quality measurement equipment, charging of reagents, etc., weather conditions, and performance information of the water quality measurement equipment by parts and reagents to learn.

That is, it is possible to learn the change in the performance state of the water quality measurement equipment according to the temperature and humidity conditions. In addition, the machine learning unit 160 uses the collected weather data, water quality data, air pollution data, etc. as learning data to determine the correlation between air pollution and water pollution, air pollution correlation according to temperature and humidity conditions, temperature and Various results such as water pollution correlation according to humidity conditions can be repeatedly learned. The machine learning unit 160 continuously utilizes the data analyzed by the data analysis unit 140 as learning data, and the data analysis unit 140 reflects the contents learned in the machine learning unit 160 and performs analysis. The accuracy of analysis results can be improved.

The machine learning unit 160 may derive a relationship between the meteorological data and performance of the water quality measuring device by comparing the weather data with a result of monitoring the operating state of the water quality measuring device. Accordingly, it is possible to provide an intelligent data logger system (10) that can secure reliability, ease of maintenance, economic feasibility, eco-friendliness (waste generation amount, consumable replacement cycle, etc.) effect is derived.

The artificial intelligence control unit 170 transmits a control signal to one of the water quality measuring equipment based on the data required for maintenance of the water quality measuring equipment for the optimal water quality condition for each water quality measuring equipment according to the analysis result of the data analysis unit 140. .

For example, when replenishment of reagents or replacement of parts is required, the artificial intelligence control unit 170 may transmit a control signal to one of the water quality measuring devices to notify the manager. The artificial intelligence control unit 170 may directly provide information on the control signal to the manager terminal 40 of the corresponding water quality measurement equipment. The artificial intelligence control detail information performed by the artificial intelligence control unit 170 is provided to the manager terminal 40 so that the manager of the water quality measuring equipment can immediately recognize it.

The artificial intelligence control unit 170 may transmit a control signal to perform self-replacement, self-recharge, and self-check to the water quality measurement equipment equipped with self-replacement, self-recharge, and self-check functions.

In an additional aspect of the present invention, the cost management unit 180 collects cost information when a replacement or maintenance cost occurs according to whether a failure occurs, a part and sample replacement cycle, and whether a calibration operation time has arrived, and collects cost information based on the collected cost information. Based on this, a maintenance cost report and a budget plan for maintenance are derived periodically.

At this time, format information of the report and the budget may be input from the manager terminal 40 . When the cost management unit 180 recognizes whether or not a failure has occurred in the draft of the report and budget proposal format received from the manager terminal 40, the parts and sample replacement cycle, and whether or not the calibration work time has arrived, the cost management unit 180 determines the corresponding cost and stores the data in the corresponding data location. can be implemented to insert In addition, the cost management unit 180 may provide the report and the budget bill generated according to the manager setting to the manager terminal 40 or the like.

3 is a flowchart of an intelligent data logger method for performing a maintenance function of water quality measuring equipment according to an embodiment of the present invention.

The intelligent data logger system performing the maintenance function of the water quality measurement equipment according to an embodiment collects meteorological data (S300).

In an embodiment, the meteorological data collection step collects meteorological data detected by one of a wind direction sensor, a wind speed sensor, a rainfall sensor, an air circulator air temperature sensor, and a rainfall sensor. In addition, weather data may be collected from the Korea Meteorological Administration server.

Operation time information and water quality data are collected from at least one water quality measurement device (S310).

In one embodiment, the water quality data collection unit 130 basically collects measured values for water temperature, pH (hydrogen ion concentration), DO (dissolved oxygen), EC (electrical conductivity), and TOC (total organic carbon) items. . In addition, biomonitoring (daphnia, algae photosynthesis, microbial fuel cells, sulfur-oxidizing microorganisms, luminescent bacteria), VOCs (volatile organic compounds), TN (total nitrogen), NH ₃ -N ammonia nitrogen), NO ₃ -N ( Nitrate nitrogen), TP (total phosphorus), PO ₄ -P (phosphate phosphorus), Chl-a (chlorophyll-a), phenol, turbidity, or heavy metals (Cu, Pb, Zn, Cd). do.

Then, data required for maintenance of the water quality measurement equipment for optimum water quality conditions is analyzed by using the collected meteorological data, operation time information, and water quality data (S320).

In one aspect of the present invention, the analyzing step is to generate pattern data for each water quality measurement equipment using the collected weather data, operation time information, and water quality data, and use the generated pattern data to determine whether a failure has occurred, parts, and samples. Perform analysis on the replacement cycle and judgment on whether or not the time for calibration work has arrived.

The analysis step is not simply limited to the consumables replacement cycle or inspection items provided by manufacturers of water quality measurement equipment, but rather reflects the meteorological data of the location where the water quality measurement equipment is installed, water pollution status, or air pollution status to further reflect the replacement cycle or inspection of consumables. You can increase the accuracy of items.

In addition, when the water quality data deviate from the preset standard, whether a failure occurs, the parts and sample replacement cycle, and the calibration period arrives, a notification message is sent to the manager terminal.

After that, based on the analysis result, data required for maintenance of each water quality measurement equipment is time-series databased (S330).

In one embodiment, in the step of creating a database, information on the arrival of calibration work for each water quality measuring device, information on the replacement cycle of consumables, parts, or samples, water quality data measurement results, and information on whether or not a failure has occurred are converted into a database and stored.

At this time, information on a time unit or necessary items to be converted into a database may be set from an administrator terminal. Items for each equipment can be added or deleted.

Then, machine learning is performed on the databased data (S340).

At this time, the analyzing step analyzes the data based on the machine learning result in the machine learning step.

That is, it is possible to learn the change in the performance state of the water quality measurement equipment according to the temperature and humidity conditions. In addition, by using the collected meteorological data, water quality data, and air pollution data as learning data, correlation between air pollution and water pollution, air pollution correlation according to temperature and humidity conditions, and water pollution correlation according to temperature and humidity conditions Various results such as relationships can be repeatedly learned. The accuracy of the analysis result can be improved by using the data analyzed in the continuous analysis step as learning data and performing the analysis by reflecting the contents learned in the machine learning step in the analysis step.

In the machine learning step, a relationship between the meteorological data and performance of the water quality measuring device may be derived by comparing the meteorological data with the operational state monitoring result of the water quality measuring device. Accordingly, it is possible to provide an intelligent data logger system (10) that can secure reliability, ease of maintenance, economic feasibility, eco-friendliness (waste generation amount, consumable replacement cycle, etc.) effect is derived.

Afterwards, an artificial intelligence control signal is transmitted to one of the water quality measuring devices based on the data required for maintenance of the water quality measuring devices for optimal water quality conditions according to the analysis result of the step of analyzing (S350).

For example, when reagents need to be supplemented or parts need to be replaced, an artificial intelligence control signal can be sent to one of the water quality measurement devices to notify the manager. In addition, the performed artificial intelligence control detail information is provided to the manager terminal 40 so that the manager of the water quality measuring equipment can immediately recognize it.

It is also possible to send artificial intelligence control signals to perform self-replacement, self-recharge, and self-check with water quality measurement equipment equipped with self-replacement, self-recharge, and self-check functions.

In a further aspect of the present invention, cost information is collected when a replacement or repair cost is incurred according to whether a failure occurs in the analysis step, a part and sample replacement cycle, and whether or not the calibration work time has arrived, and based on the collected cost information Therefore, a maintenance cost report and a budget plan for maintenance are periodically derived (S360).

At this time, format information of the report and the budget may be input from the manager terminal. The cost management step can be implemented to identify the cost incurred and insert it into the corresponding data location when it is recognized whether there is a failure in the draft of the report and budget proposal format input from the manager terminal, the replacement cycle of parts and samples, and whether or not the time for calibration work has arrived. have. In the cost management step, a report and a budget bill generated according to a manager setting may be provided to a manager terminal or the like.

The above method may be implemented as an application or implemented in the form of program instructions that can be executed through various computer components and recorded on a computer readable recording medium. The computer readable recording medium may include program instructions, data files, data structures, etc. alone or in combination.

Program instructions recorded on the computer-readable recording medium may be those specially designed and configured for the present invention, or those known and usable to those skilled in the art of computer software.

Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, and magneto-optical media such as floptical disks. media), and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like.

Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter or the like as well as machine language codes such as those produced by a compiler. The hardware device may be configured to act as one or more software modules to perform processing according to the present invention and vice versa.

Although the above has been described with reference to embodiments, it will be understood that those skilled in the art can variously modify and change the present invention without departing from the spirit and scope of the present invention described in the claims below. You will be able to.

10: intelligent data logger system 20: environment management corporation server
30: treatment plant server 40: manager terminal
110: communication unit 120: weather data collection unit
130: water quality data collection unit 140: data analysis unit
150: database unit 160: machine learning unit
170: artificial intelligence control unit 180: cost management unit
190: storage unit

Claims (4)

a weather data collection unit that collects weather data;
a water quality data collection unit that collects operation time information and water quality data from at least one water quality measurement device;
Analyzing data required for maintenance of water quality measuring equipment for optimal water quality conditions for each water quality measuring equipment using the meteorological data collected by the meteorological data collection unit and the operation time information and water quality data collected by the water quality data collecting unit data analysis unit;
a database unit for time-sequentially creating a database of data necessary for maintenance of each water quality measurement equipment based on the analysis result of the data analysis unit; and
An intelligent data logger system that performs a maintenance function of water quality measurement equipment including; a machine learning unit that learns based on data compiled in the database unit;
The data analysis unit analyzes data based on a machine learning result from the machine learning unit,
The data analysis unit,
Using the collected meteorological data, operating time information, and water quality data, pattern data for each water quality measurement equipment is generated,
Using the generated pattern data, analyzes are performed to determine whether a failure has occurred, parts and sample replacement cycles, and calibration work timing has arrived.
An artificial intelligence control unit for transmitting a control signal to one of the water quality measuring devices based on data required for maintenance of the water quality measuring devices for optimal water quality conditions for each water quality measuring device according to the analysis result of the analyzing unit,
The data analysis unit,
A notification message is sent to the administrator's terminal when water quality data deviate from the preset standards, failures, parts and sample replacement cycles, and calibration time have arrived.
Cost information is collected when replacement or repair costs are incurred according to failure occurrence, parts and sample replacement cycle, and calibration work timing, and based on the collected cost information, a maintenance cost report and a budget for maintenance are periodically prepared. A cost management unit to derive; further comprising,
The water quality data collection unit,
For each treatment plant server, collect the model name, approval date and approval number of each water quality measuring device linked to the treatment plant server, and quantity information of the water quality measuring device connected to each treatment plant server,
This information is further collected when a notification occurs according to the automatic notification function from the water quality measurement equipment equipped with the specification information for each water quality measuring device and the self-consumable replacement cycle automatic notification function,
Self-diagnosis results and automatic dilution function performance information are further collected from water quality measurement equipment equipped with self-diagnosis and reagent automatic dilution functions.
In the case of volatile organic compound (VOCs) measuring equipment that needs to maintain a temperature above a certain value, the temperature information of the space where the water quality measuring equipment is installed is further collected,
After collecting measured values for water temperature, pH (hydrogen ion concentration), DO (dissolved oxygen), EC (electric conductivity), and TOC (total organic carbon), additional biological monitoring (water flea, algae photosynthesis, microbial fuel cell) , sulfur-oxidizing microorganisms, luminescent bacteria), VOCs (volatile organic compounds), TN (total nitrogen), NH ₃ -N ammonia nitrogen), NO ₃ -N (nitric acid nitrogen), TP (total phosphorus), PO ₄ -P (phosphate), Chl-a (chlorophyll-a), phenol, turbidity, and one of the heavy metals (Cu, Pb, Zn, Cd) are collected,
The intelligent data logger system further includes a pollutant data collection unit,
The pollutant data collection unit,
In order to determine the degree of environmental pollution for a predetermined area, regional information, information on pollutants, and information on surrounding conditions are further received, but the pollutant information is ozone (O3), carbon monoxide ( _CO ), ), ammonia (NH ₃ ), nitrogen oxides (NOx), nitrates (NO ₃ ), using at least one of fine dust and mercury as a pollutant,
Information on heavy metals contained in the atmosphere within a predetermined area, information on ions contained in the atmosphere within a predetermined area, information on the size of fine dust particles contained in the atmosphere within the predetermined area, and visibility within the predetermined area An intelligent data logger system that performs a maintenance function of water quality measurement equipment, collecting at least one of information about distance as information about a surrounding situation.
delete In the intelligent data logger method for performing the maintenance function of the water quality measuring equipment performed in the intelligent data logger system performing the maintenance function of the water quality measuring equipment according to claim 1,
collecting meteorological data;
Collecting operation time information and water quality data from at least one water quality measurement device;
analyzing data necessary for maintenance of water quality measuring equipment for optimum water quality conditions for each water quality measuring equipment using the collected meteorological data, operation time information, and water quality data;
Time-sequentially creating a database of data required for maintenance for each water quality measuring equipment based on the analysis result in the analyzing step; and
machine learning the databased data; Including,
The analyzing step analyzes the data based on the machine learning result in the machine learning step,
The analysis step is
Using the collected meteorological data, operating time information, and water quality data, pattern data for each water quality measurement equipment is generated,
Using the generated pattern data, analyzes are performed to determine whether a failure has occurred, parts and sample replacement cycles, and calibration work timing has arrived.
An artificial intelligence control step of transmitting a control signal to one of the water quality measuring equipment based on the data required for maintenance of the water quality measuring equipment for the optimal water quality condition for each water quality measuring equipment according to the analysis result of the analyzing step; and ,
The analysis step is
A notification message is sent to the administrator's terminal when water quality data deviate from the preset standards, failures, parts and sample replacement cycles, and calibration time have arrived.
Cost information is collected when replacement or repair costs are incurred according to whether failures occur during the analysis stage, parts and sample replacement cycles, and calibration work timing, and based on the collected cost information, periodic maintenance cost reports and maintenance Intelligent data logger method for performing the maintenance function of the water quality measurement equipment further comprising; cost management step of deriving a budget for management.
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