Prediction model for water quality deterioration

Abstract

An embodiment provides a method for predicting water quality deterioration in a water distribution system, the method comprising: receiving a dataset of measurements including multiple components within the water distribution system at an electronic device; determining a water quality index based on algorithmic analysis of the measurements; and providing recommendations for mitigating water quality deterioration in the water distribution system based on the determined water quality index. Other aspects are described and claimed.

Description

[0001] Cross-reference to related applications

[0002] This application claims priority to U.S. Patent Application Serial No. 17 / 174,851, filed February 12, 2021, entitled “PREDICTIVE MODEL FOR WATERQUALITY DETERIORATION”, the contents of which are incorporated herein by reference. Technical Field

[0003] This application generally relates to predicting the water quality status of a water distribution system at a future point in time. Background Technology

[0004] Ensuring water quality is crucial in many industries, including pharmaceuticals and other manufacturing sectors. Furthermore, maintaining water quality is essential for the health of humans, animals, and plants that depend on water for survival. Therefore, water quality deterioration jeopardizes life and business. This deterioration can result from one or more different factors, such as nitrification, corrosion, and / or the formation of disinfectant byproducts. Based on the underlying issues, specific actions are needed to mitigate further water quality deterioration and, accordingly, ensure the viability of water distribution systems. Summary of the Invention

[0005] In general, the embodiments provide a method for predicting water quality deterioration in a water distribution system, the method comprising: receiving a dataset at an electronic device, the dataset including measurements of various chemical components within the water distribution system; determining a water quality index based on algorithmic analysis of the measurements; and providing recommendations for mitigating water quality deterioration in the water distribution system based on the determined water quality index.

[0006] Another embodiment provides an electronic device for predicting water quality deterioration in a water distribution system, the electronic device comprising: a processor; and a memory storing instructions executable by the processor to: receive a dataset including measurements of various chemical components within the water distribution system; perform algorithmic analysis based on the measurements to determine a water quality index; and provide recommendations for mitigating water quality deterioration in the water distribution system based on the determined water quality index.

[0007] Another embodiment provides a computer program product including a storage device storing code executable by a processor and including: code for receiving a dataset including measurements of various chemical components within a water distribution system; code for determining a water quality index based on algorithmic analysis of the measurements; and code for providing recommendations for mitigating water quality deterioration in the water distribution system based on the determined water quality index.

[0008] The above is a summary and may therefore contain simplifications, generalizations and omissions of details; therefore, those skilled in the art will understand that this summary is illustrative only and is not intended to be limiting in any way.

[0009] To better understand the embodiments and other and further features and advantages of the embodiments, reference is made to the following description in conjunction with the accompanying drawings. The scope of the invention will be set forth in the appended claims. Attached Figure Description

[0010] Figure 1 A flowchart for predicting water quality in a water distribution system is shown.

[0011] Figure 2 An exemplary table containing growth components and inactivation components and their necessary threshold levels, according to an embodiment, is shown.

[0012] Figure 3 Examples of several sample suggestion types according to embodiments are shown.

[0013] Figure 4(AB) shows an example of a table of action level thresholds and corresponding suggestion types for identifying various components according to an embodiment.

[0014] Figure 5 An example of a computer circuit is shown. Detailed Implementation

[0015] It will be readily understood that, in addition to the exemplary embodiments described herein, the components of the embodiments generally described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following more detailed description of the exemplary embodiments presented in the drawings is not intended to limit the scope of the embodiments as claimed, but rather represents exemplary embodiments only.

[0016] In this specification, references to "an embodiment" or "an embodiment" (or similar wording) mean that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment. Therefore, the phrases "in one embodiment" or "in an embodiment" or similar wording appearing in various places in this specification do not necessarily refer to the same embodiment.

[0017] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of the embodiments. However, those skilled in the art will recognize that various embodiments can be practiced without one or more of these specific details, or using other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail. The following description is intended only as an example and simply illustrates certain exemplary embodiments.

[0018] As water flows from a treatment plant to the end user or entity, several factors can negatively impact its quality. For example, one factor might be corrosion of the water pipes. More specifically, over time, sections of the pipes may begin to shed lead, copper, or other materials, which can mix with the water they contain. Additionally or alternatively, small cracks may appear in the pipes, which can allow sediment and / or other materials to mix with the water, thus degrading its quality. Another factor that can affect water quality is the formation of disinfection byproducts from the chemicals used to treat the water. For example, chlorine is frequently used as a disinfectant in water to prevent the growth of various types of microorganisms or to eliminate their presence. While effective, excessive chlorine can react with certain organic matter in the water to form harmful byproducts that negatively impact water quality.

[0019] While each of the factors mentioned above can degrade water quality, most applications will target the negative effects of the nitrification process. However, it is important to note that this focus is not limiting, and the novel concepts described herein can be applied to predicting water quality degradation caused by other factors, such as corrosion and the formation of disinfectant byproducts.

[0020] Nitrification is a biological process. During this process, certain types of bacteria can proliferate by consuming a component of the disinfectant used to treat water. This problem typically occurs in treatment plants that use chloramine instead of chlorine to treat water. More specifically, chloramine has an inherent ability to persist longer than chlorine, making it well-suited for distribution systems serving larger populations and / or populations spread over a larger area. However, chloramine contains both chlorine and ammonia, which can separate under certain conditions, allowing ammonia to become a nutrient source for bacterial growth. When ammonia is consumed, it is converted into nitrite and nitrate, which correspondingly leads to the loss of disinfectant and subsequently degrades water quality.

[0021] Nitrification in water distribution systems is a pervasive and persistent problem, leading to long-term disinfection residue challenges that are both time-consuming and costly to address. If left unchecked, it can jeopardize individual health through drinking water, and water treatment facilities responsible for ensuring water quality may be found to be in violation of regulations. Conventional solutions to this problem are often reactive in nature; more specifically, remedial action is typically not taken until the problem becomes severe enough to warrant intervention. Therefore, predicting the risk of nitrification enables proactive measures to prevent the harmful process from occurring.

[0022] Therefore, embodiments provide a system and method for generating a water quality index value that predicts water quality at a specific future point in time. Based on this index value, customized recommendations can be provided, outlining various steps that can be taken to mitigate water quality deterioration in specific circumstances. In embodiments, a dataset containing measurements of multiple components associated with a water distribution system can be received at an electronic device. These components or variables may include chemical components (e.g., free ammonia, total chlorine, nitrite, nitrate, monochloramine, etc.) or state conditions (e.g., temperature within transport pipelines, pH of water, etc.). Embodiments can then analyze these values ​​using a specialized algorithm to determine an index classification of the water quality. The index classification can be a single numerical value that predicts water quality at a future point in time if current conditions persist. Based on the index classification, customized recommendations can be provided to users or entities, outlining one or more suggested steps that can be taken to proactively address any predicted water quality deterioration or remedy existing problems in the water distribution system.

[0023] The exemplary embodiments shown can be better understood by referring to the accompanying drawings. The following description is intended to be illustrative only and simply illustrates some exemplary embodiments.

[0024] refer to Figure 1 An example system and method for predicting water quality at future points in time are illustrated. At point 101, a dataset containing measurements of various components associated with the water distribution system can be received at the device. These components may include chemical components (i.e., free chemicals present in the water, disinfectants, disinfection byproducts, etc.) or state conditions (e.g., water temperature, temperature within the water supply pipe at a specific location, pH value of the water, etc.). Measurements of these components can be obtained in the field (i.e., within or at the water supply pipe, etc.) or at another location (e.g., a laboratory, etc.) by various conventional instruments, sensors, and / or processes.

[0025] In the embodiments, the measurements of these components may correspond to specific past dates. The “lag” between the date the measurement was obtained and the date the analysis described herein was performed may subsequently affect the extent to which future water quality can be predicted. As a non-limiting example, measurements of components from one day ago may be able to predict water quality for the next ten days.

[0026] In the embodiments, each component can be categorized into one of two groups: a growth group and an inactivation group. Regarding the former, these components, when present in water at certain levels, can promote the growth of certain bacteria, while the latter, when present at certain levels, can promote the inactivation of bacterial growth. This is a non-limiting example, and references are made to... Figure 2A table is provided showing the potential decomposition of the tested components in aqueous samples. The growth group includes disinfectant byproducts (e.g., ammonia, nitrite, nitrate, etc.), heterotrophic plate counts (HPC) (i.e., a direct measurement of bacterial growth), and the temperature at which the measurement was taken. The inactivation group includes the disinfectant itself (e.g., total chlorine, monochloramine, and free chlorine) and the pH range of the water. It is important to note that this list of components is not exhaustive, and measurements of various other components not explicitly described here are also available and can be used to predict water quality. Thresholds for each component are further shown. These thresholds define a critical point above which components associated with the growth group may begin to negatively impact water quality, and below which components associated with the inactivation group may lose their effectiveness in slowing bacterial growth.

[0027] At 102, the embodiment may determine a water quality index (“index”) based on measurements. In the embodiment, the index may represent the water quality at a specific future point in time for a given context. While such an index may be applicable to a variety of different factors (e.g., the predicted impact of corrosion on water quality, the expected impact of disinfectant byproduct formation on water quality, etc.), the balance of this disclosure involves the nitrification potential index (“NPI”), which predicts the expected onset of nitrification at a future point in time based on previously obtained measurements of components in the water distribution system.

[0028] In this embodiment, the NPI can be a single number that represents the potential nitrification state at a future point in time based on measurements. Such a number can be calculated using the following algorithm:

[0029]

[0030] The algorithm takes into account the measured values ​​of the components in the water distribution system and also balances the lag time (L) from the start of the measurement to determine the level time (H) to which NPI may be applicable.

[0031] At point 103, by using a classification based on the Water Quality Index (NPI), the embodiment can provide proactive recommendations to individuals or entities, outlining one or more steps that can be taken to mitigate water quality deterioration in a water distribution system. The urgency and / or complexity of the recommendations can be proportional to the NPI number (i.e., the higher the NPI number, the more complex the recommended strategy may be to prevent further deterioration of the nitrification process). Additionally or alternatively, the content presented within the recommendations may be influenced by other factors, as further described herein.

[0032] In this embodiment, the type of recommendation provided can be entirely based on the NPI number. More specifically, the content of the recommendation can depend on the range to which the NPI number belongs (e.g., 0.5-0.75 corresponds to type 1 recommendation, 0.75-1 corresponds to type 2 recommendation, and so on), and wherein the critical nature of each successive recommendation increases (e.g., type 4 recommendation is more severe than type 2 recommendation). This range can be initially set by the software programmer and can be adjusted later by the user. In this embodiment, the system can access this range of data from an accessible source (e.g., a database stored locally on a computer device or remotely stored on another device or server).

[0033] In this embodiment, an NPI threshold may be specified. If the NPI is below this threshold, bacterial growth is controlled, and nitrification is not expected to occur. In this case, no recommendations may be provided, or the recommendation may suggest maintaining the current process and procedures. Conversely, if the NPI is above the threshold, the initiation of nitrification is anticipated, and recommendations reflecting the severity of the anticipated initiation may be provided appropriately.

[0034] In the embodiments, the proactive or occasionally reactive steps suggested in each recommendation (depending on the severity of the predicted situation) can be categorized into different response types. For example, some steps may be specified to be performed on-site (i.e., on-site or within the re-transmission pipeline), while others may be more administrative (e.g., assessing the on-site response, communicating findings to relevant authorities, etc.). The more of these recommended steps performed on-site and administratively, the greater the likelihood that the anticipated nitrification problem may be mitigated.

[0035] Now for reference Figure 3 This provides a non-limiting, representative example of the concepts described above. In this case, the NPI threshold can be set to 0.5, the recommended range for Type 1 can be between 0.5 and 0.75, the recommended range for Type 2 can be between 0.75 and 1, the recommended range for Type 3 can be between 1 and 1.25, and the recommended range for Type 4 can be between 1.25 and higher. Therefore, if the NPI number is determined to be 0.8, a Type 2 recommendation can be given to the end user, which specifically recommends chlorination purging and valve purging on the water supply pipeline. Similarly, if the NPI number is determined to be 1.5, a Type 4 recommendation can be given to the end user, in which point chlorination should be performed on the entire water distribution system. The recommended steps for both the field and management categories are not limited to... Figure 3 The steps shown are not the same, but can be further modified by the programmer or end user. Figure 3The information in the table is obtained from Crystal Ybanez's "Tackling One City's Nitrification Action Plan", January 2020, Vol. 112, No. 1, p. 41.

[0036] In addition to proactive mitigation of WQ deterioration, real-time mitigation recommendations may also be dynamically influenced by the identification of: A) the number of components exceeding a specific action level; and / or B) the specific action level exceeded. Now refer to Figure 4A A table is provided that identifies the threshold level for each component based on the action level. For example, if the amount of free ammonia is determined to be 0.31, then the action level corresponding to the measurement of free ammonia is action level 3. Now refer to... Figure 4B A table is provided that identifies the types of recommendations that can be made based on component measurements when they are correlated with action level thresholds. For example, a Type 1 recommendation could be made in response to the identification that two components have measurements exceeding the action level 1 threshold. For instance, a Type 1 recommendation could be made in response to the identification that the total chlorine value is 1.6 and the monochloramine value is 1.15. Such a result might mean that the amount of disinfectant in the system has fallen below a first threshold level, and that the state of the water distribution system warrants at least some consideration. In another exemplary scenario, a Type 4 recommendation could be made in response to the identification that the measurement of only a single component has exceeded the action level 4 threshold.

[0037] Therefore, the various embodiments described herein represent technical improvements over conventional techniques for addressing water quality problems in water distribution systems, particularly those caused by nitrification processes. By using the techniques described herein, the embodiments can receive measurements from multiple components associated with the water distribution system. These measurements are then used to determine a water quality index. Such an index can predict the potential onset of water quality problems due to one or more water quality deterioration factors (e.g., nitrification, corrosion, disinfection byproduct formation, etc.). Based on this determined index value, the embodiments can provide specific recommendations including one or more steps that the user can take to mitigate the onset of negative impacts on water quality.

[0038] Although various other circuits, loops, or components can be used in information processing devices, the instrument for measuring copper and zinc according to any of the various embodiments described herein is... Figure 5An example is shown. Device loop 10' may include a measurement system based on a chip design, such as a specific computing platform (e.g., mobile computing, desktop computing, etc.). Software and processor(s) are combined in a single chip 11'. As is known in the art, the processor includes an internal arithmetic unit, registers, cache memory, buses, I / O ports, etc. While the internal buses, etc., vary depending on the vendor, essentially all peripheral devices (12') can be attached to a single chip 11'. Loop 10' combines the processor, memory control, and I / O controller hub all into a single chip 11'. Moreover, this type of system 10' typically does not use SATA, PCI, or LPC. Common interfaces include SDIO and I2C, for example.

[0039] There are multiple power management chips 13', such as battery management units (BMUs), which manage power supplied, for example, via a rechargeable battery 14', which can be recharged by connection to a power source (not shown). In at least one design, a single chip (such as 11') is used to provide BIOS-like functionality and DRAM memory.

[0040] System 10' typically includes one or more of a WWAN transceiver 15' and a WLAN transceiver 16' for connecting to various networks, such as telecommunications networks and wireless internet devices, such as access points. It also typically includes devices 12', such as transmit and receive antennas, oscillators, PLLs, etc. System 10' includes input / output devices 17' for data input and display / presentation (e.g., easily accessible computing locations away from single-beam system positioning). System 10' also typically includes various memory devices, such as flash memory 18' and SDRAM 19'.

[0041] As understood from the foregoing, the electronic components of one or more systems or devices may include, but are not limited to, at least one processing unit, memory, and a communication bus or communication device that connects various components, including the memory, to the processing unit(s). The system or device may include or have access to various device-readable media. The system memory may include device-readable storage media in the form of volatile and / or non-volatile memory, such as read-only memory (ROM) and / or random access memory (RAM). By way of example and not limitation, the system memory may also include an operating system, application programs, other program modules, and program data. The disclosed system may be used in embodiments to perform measurements of copper and zinc in aqueous samples.

[0042] As those skilled in the art will understand, various aspects can be embodied as a system, method, or apparatus program product. Therefore, aspects can take the form of a completely hardware embodiment or an embodiment including software, which is generally referred to herein as a “loop,” “module,” or “system.” Furthermore, aspects can also take the form of an apparatus program product embodied in one or more apparatus-readable media having apparatus-readable program code contained therein.

[0043] It should be noted that the various functions described herein can be implemented using instructions stored on a device-readable storage medium (e.g., a non-signal storage device), wherein the instructions are executed by a processor. In the context of this document, a storage device is not a signal, and "non-transient" includes all media other than signal media.

[0044] Program code for performing operations can be written in any combination of one or more programming languages. The program code can execute entirely on a single device, partially on a single device, as a standalone software package, partially on a single device and partially on another device, or entirely on another device. In some cases, the device can be connected via any type of connection or network, including a local area network (LAN) or a wide area network (WAN), or via other devices (e.g., through the Internet provided by an Internet service provider), via a wireless connection (e.g., via near-field communication), or via a hardwired connection (e.g., via USB).

[0045] Exemplary embodiments are described herein with reference to the accompanying drawings, which illustrate example methods, apparatuses, and products according to various exemplary embodiments. It will be understood that actions and functions can be implemented at least in part by program instructions. These program instructions can be provided to the processor of an apparatus (e.g., a handheld measuring device or other programmable data processing device) to generate a machine such that the instructions, executed via the processor of the apparatus, perform the specified function / action.

[0046] Note that the values ​​provided herein should be interpreted to include equivalent values ​​indicated by the use of the term "about". While equivalent values ​​will be apparent to those skilled in the art, at least the values ​​obtained by ordinary rounding to the last significant digit are included.

[0047] While this disclosure is provided for illustrative and descriptive purposes, it is not intended to be exhaustive or limiting. Many modifications and variations will be apparent to those skilled in the art. Exemplary embodiments were chosen and described in order to explain the principles and practical applications, and to enable others skilled in the art to understand the disclosure of various embodiments with various modifications suitable for the particular intended use.

[0048] Therefore, although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that this specification is not restrictive, and various other changes and modifications may be made therein by those skilled in the art without departing from the scope or spirit of this disclosure.

Claims

1. A method for predicting water quality deterioration in a water distribution system, comprising: At least one sensor is used at an electronic device to receive a dataset, the dataset including measurements of multiple components within the water distribution system, wherein the dataset includes at least one growth group of disinfectant byproducts and at least one inactivation group of disinfectants, wherein the at least one sensor includes at least one sensor for measuring nitrite corresponding to nitrification of the water. Based on the algorithmic analysis of the measured values, a water quality index is generated, wherein the generation includes: Identify multiple action levels; Identify the threshold associated with each of the plurality of action levels; Determine which of the action levels exceeded the threshold; and Based on the measured values, determine which of the multiple components exceeds the threshold; Identify the duration from the time the measurement is received to the time when the water quality index reaches a threshold, wherein the threshold defines the point at which the effect of the growth group is greater than the effect of the inactivation group; and Based on a determined water quality index, received data from at least one sensor, and duration, recommendations for mitigating water quality deterioration in the water distribution system are adjusted. These recommendations are dynamically updated in real time by identifying component values ​​exceeding threshold levels. The recommendations include on-site responses to the water distribution system to mitigate water quality deterioration, and management responses for communicating with the recommendations. The adjustments include: The recommendation is made based on determining at least one of the following: chlorine purging and valve purging of the water supply pipeline, or interrupted chlorination of the entire water distribution system.

2. The method according to claim 1, wherein, Each of the various chemical components is associated with either bacterial growth or bacterial inactivation.

3. The method according to claim 1, wherein, Each measurement in the dataset, which includes measurements of multiple components, is selected from a group consisting of free ammonia, nitrite, nitrate, hydroxypropyl cellulose, temperature, total chlorine, monochloramine, free chlorine, and pH level.

4. The method according to claim 1, wherein, The measurement value is derived from a past time X days prior to the current time, and the water quality index classification corresponds to a future time Y days after the current time, wherein the Y days depend at least in part on the X days.

5. The method according to claim 1, wherein, The water quality index is associated with the nitrification potential of the water distribution system.

6. The method according to claim 1, wherein, The water quality index corresponds to a single value.

7. The method according to claim 6, wherein, The critical properties associated with the recommendation are proportional to the magnitude of the single numerical value.

8. The method according to claim 1, wherein, The recommendations include multiple recommended actions, wherein a portion of the multiple recommended actions is designated as field actions, and wherein another portion of the recommended actions is designated as management actions.

9. An electronic device for predicting water quality deterioration in a water distribution system, comprising: processor; as well as A memory storing instructions that can be executed by the processor to: At least one sensor is used at an electronic device to receive a dataset, the dataset including measurements of multiple components within the water distribution system, wherein the dataset includes at least one growth group of disinfectant byproducts and at least one inactivation group of disinfectants, wherein the at least one sensor includes at least one sensor for measuring nitrite corresponding to nitrification of the water. Based on the algorithmic analysis of the measured values, a water quality index is generated, wherein the generation includes: Identify multiple action levels; Identify the threshold associated with each of the plurality of action levels; Determine which of the action levels exceeded the threshold; and Based on the measured values, determine which of the multiple components exceeds the threshold; Identify the duration from the time the measurement is received to the time when the water quality index reaches a threshold, wherein the threshold defines the point at which the effect of the growth group is greater than the effect of the inactivation group; and Based on a determined water quality index, received data from at least one sensor, and duration, recommendations for mitigating water quality deterioration in the water distribution system are adjusted. These recommendations are dynamically updated in real time by identifying component values ​​exceeding threshold levels. The recommendations include on-site responses to the water distribution system to mitigate water quality deterioration, and management responses for communicating with the recommendations. The adjustments include: The recommendation is made based on determining at least one of the following: chlorine purging and valve purging of the water supply pipeline, or interrupted chlorination of the entire water distribution system.

10. The electronic device according to claim 9, wherein, Each of the multiple components is associated with either bacterial growth or bacterial inactivation.

11. The electronic device according to claim 9, wherein, Each measurement in the dataset, which includes measurements of multiple components, is selected from a group consisting of free ammonia, nitrite, nitrate, hydroxypropyl cellulose, temperature, total chlorine, monochloramine, free chlorine, and pH level.

12. The electronic device according to claim 9, wherein, The measurement value is derived from a past time X days prior to the current time, and the water quality index classification corresponds to a future time Y days after the current time, wherein the Y days depend at least in part on the X days.

13. The electronic device according to claim 9, wherein, The water quality index corresponds to a single value.

14. The electronic device according to claim 9, wherein, The priority associated with the recommendation is proportional to the magnitude of the individual numerical value.

15. The electronic device according to claim 9, wherein, The recommendations include multiple recommended actions, wherein a portion of the multiple recommended actions is designated as field actions, and wherein another portion of the recommended actions is designated as management actions.

16. A computer program product comprising: A storage device storing code executable by a processor and comprising: A code that receives a dataset at an electronic device using at least one sensor, the dataset including measurements of multiple components within a water distribution system, wherein the dataset includes at least one growth group of disinfectant byproducts and at least one inactivation group of disinfectants, wherein the at least one sensor includes at least one sensor for measuring nitrite corresponding to nitrification of the water. A code that generates a water quality index based on algorithmic analysis of the measured values, wherein the generation includes: Identify multiple action levels; Identify the threshold associated with each of the plurality of action levels; Determine which of the action levels exceeded the threshold; and Based on the measured values, determine which of the multiple components exceeds the threshold; Identify the duration from the time the measurement is received to the time when the water quality index reaches a threshold, wherein the threshold defines the point at which the effect of the growth group is greater than the effect of the inactivation group; and A code that, based on a determined water quality index, received data from at least one sensor, and duration, adjusts recommendations to mitigate water quality deterioration in a water distribution system. These recommendations are dynamically updated in real time by identifying components exceeding threshold levels. The recommendations include on-site responses to the water distribution system to mitigate water quality deterioration, and administrative responses for communicating with the recommendations. The adjustments include: The recommendation is made based on determining at least one of the following: chlorine purging and valve purging of the water supply pipeline, or interrupted chlorination of the entire water distribution system.

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