Description:TECHNICAL FIELD
The present disclosure relates generally to liquid dispensers. More particularly, the present disclosure relates to a system and a method for precise liquid delivery.
BACKGROUND
Liquid mixing process may be characterized as a blending of different liquids in a requisite composition. A flowing current is produced when the liquids are mixed together. Precise mixing of two or more liquids finds applications in various industries such as perfume manufacturing industry, pharmaceutical industry, beverage manufacturing industry and the like.
Variation in a number of factors such as environmental factors, performance factors of the machines, different viscosity values associated with different liquids, and the like result in inefficient and inaccurate composition of liquids, when the liquid mixing process is automated. Further, an inadequate flow of liquids while mixing may further result in inaccurate composition of the liquids.
As the applications mentioned above desire highly accurate, precise and efficient liquid mixing, there is a need for an automated system and a method for accurate measurement and delivery of liquids, and thus demands a need for improvised technical solution that overcomes the aforementioned problems.
SUMMARY
In an aspect of the present disclosure, a liquid delivery system includes a sensing unit and a processing circuitry. The sensing unit is configured to determine a set of numerical values for a set of configuration parameters that corresponds to delivery of a liquid. The processing circuitry is configured receive, from the sensing unit, the set of numerical values for the set of configuration parameters. The processing circuitry is further configured to determine a flow rate of the liquid based on the set of numerical values for the set of configuration parameters. Furthermore, the processing circuitry is configured to adjust a rate of the iterative update of the set of numerical values for the set of configuration parameters based on one or more inputs from a user. Furthermore, the processing circuitry is configured to determine the threshold value based on the rate of the iterative update. Furthermore, the processing circuitry is configured to iteratively update the set of numerical values for the set of configuration parameters to iteratively update the flow rate of the liquid unless a difference between the flow rate of the liquid and a pre-defined optimum flow rate of the liquid is less than a threshold value.
In some aspects, the liquid delivery system further includes a liquid delivery device. The liquid delivery device includes a fluid inlet, a channel system, and a fluid outlet such that the channel system having a plurality of channels connects the fluid inlet to the fluid outlet by way of one or more nozzles.
In some aspects, the liquid delivery device of the liquid delivery system further includes a delivery motor that is configured to deliver the liquid from the fluid inlet to the fluid outlet via the channel system.
In some aspects, the set of configuration parameters includes at least one of, one or more environmental parameters, and one or more calibration parameters of the delivery motor.
In some aspects, to adjust the flow rate of the liquid, the processing circuitry is configured to adjust a rotational speed of the delivery motor and a duration of rotation of the delivery motor.
In some aspects, the processing circuitry is configured to adjust the rate of the iterative update of the flow rate by way of a machine learning based dynamic learning rate strategy.
In another aspect of the present disclosure, a liquid delivery method includes determining, by way of a sensing unit, a set of numerical values for a set of configuration parameters that corresponds to delivery of a liquid. The liquid delivery method further includes receiving, by way of processing circuitry, the set of numerical values for the set of configuration parameters from the sensing unit. Furthermore, the liquid delivery method includes determining, by way of the processing circuitry, a flow rate of the liquid based on the set of numerical values for the set of configuration parameters. Furthermore, the liquid delivery method includes adjusting, by way of the processing circuitry, a rate of the iterative update of the set of numerical values for the set of configuration parameters based on one or more inputs from a user. Furthermore, the liquid delivery method includes determining, by way of the processing circuitry, a threshold value based on the rate of the iterative update. Furthermore, the liquid delivery method includes updating iteratively, by way of the processing circuitry, the set of numerical values for the set of configuration parameters to iteratively update the flow rate of the liquid, unless a difference between the flow rate of the liquid and a pre-defined optimum flow rate of the liquid is less than the threshold value.
BRIEF DESCRIPTION OF DRAWINGS
The above and still further features and advantages of aspects of the present disclosure becomes apparent upon consideration of the following detailed description of aspects thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
FIG. 1 illustrates a block diagram of a precise system for liquid delivery, in accordance with an exemplary aspect of the present disclosure;
FIG. 2 illustrates a block diagram of a server of FIG. 1, in accordance with an exemplary aspect of the present disclosure; and
FIG. 3 illustrates a flow chart of a precise method for liquid, in accordance with an exemplary aspect of the present disclosure.
To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures.
DETAILED DESCRIPTION
Various aspect of the present disclosure provides a precise system for delivery of a liquid and a precise method for delivery of the liquid. The following description provides specific details of certain aspects of the disclosure illustrated in the drawings to provide a thorough understanding of those aspects. It should be recognized, however, that the present disclosure can be reflected in additional aspects and the disclosure may be practiced without some of the details in the following description.
The various aspects including the example aspects are now described more fully with reference to the accompanying drawings, in which the various aspects of the disclosure are shown. The disclosure may, however, be embodied in different forms and should not be construed as limited to the aspects set forth herein. Rather, these aspects are provided so that this disclosure is thorough and complete, and fully conveys the scope of the disclosure to those skilled in the art. In the drawings, the sizes of components may be exaggerated for clarity.
It is understood that when an element is referred to as being “on,” “connected to,” or “coupled to” another element, it can be directly on, connected to, or coupled to the other element or intervening elements that may be present. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items.
The subject matter of example aspects, as disclosed herein, is described with specificity to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventor/inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different features or combinations of features similar to the ones described in this document, in conjunction with other technologies. Generally, the various aspects including the example aspects relate to the system, and the method for precise delivery of the liquid.
As mentioned, there is a need for an automated system and a method for accurate measurement and delivery of a liquid without adding any contamination. The present aspect, therefore: provides a precise liquid delivery system 100 and a precise liquid delivery method 300 for highly accurate liquid measurement without any contaminations and ensures highly efficient and precise delivery of the liquid.
The aspects herein and the various features and advantageous details thereof are explained more fully with reference to the non-limiting aspects that are illustrated in the accompanying drawings and detailed in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the aspects herein. The examples used herein are intended merely to facilitate an understanding of ways in which the aspects herein may be practiced and to further enable those of skill in the art to practice the aspects herein. Accordingly, the examples should not be construed as limiting the scope of the aspects herein.
FIG. 1 illustrates a block diagram of the liquid delivery system 100, in accordance with an exemplary aspect of the present disclosure. The liquid delivery system 100 (hereinafter interchangeably referred to and designated as “the system 100”) may include a user device 102, a liquid delivery device 104 and a server 106. In some aspects of the present disclosure, the user device 102 and the liquid delivery device 104 (hereinafter interchangeably referred to and designated as “the delivery device 104”) may be communicatively coupled to the server 106 by way of either of, a first wired communication medium (not shown) and a first wireless communication medium (not shown). In some aspects of the present disclosure, the user device 102, the delivery device 104 and the server 106 may be communicatively coupled to each other by way of a communication network 108.
The user device 102 may be configured to enable a user to select a liquid from a set of pre-defined liquids. The user device 102 may further be configured to enable the user to select a quantity of the selected liquid of the set of pre-defined liquids. In some aspects of the present disclosure, the user device 102 may be configured to store one or more compositions (in terms of weights, volumes, and/or one or more properties of each liquid of the set of pre-defined liquids) for mixing of the liquid. The user device 102 may further be configured to receive, from the system 100, one or more notifications related to mixing and/or delivery of the liquid. In some aspects of the present disclosure, the user device 102 may be configured to enable the user to input and/or save data related to a new liquid that may be different from the set of pre-defined liquids. In some aspects of the present disclosure, the user device 102 may be configured to facilitate the user to register on the system 100. Furthermore, the user device 102 may facilitate the user to enable a password protection for logging-in (and/or authenticate the user) to the system 100. The liquid selected by the user from either of, the pre-defined set of liquids and the new liquid input by the user, hereinafter is cumulatively referred to as “the liquid”. Furthermore, the user device 102 may be configured to enable the user to provide instruction data for selection of the liquid and/or quantity of the liquid (in terms of weight or volume of the liquid selected by the user).
In an exemplary aspect of the present disclosure, the user device 102 may include a first user interface 110, a first processing unit 112, a first memory 114, a first liquid delivery console 116, and a first communication interface 118.
The first user interface 110 may include a first input interface for receiving inputs from the user. In some aspects of the present disclosure, the first user interface 110 may be configured to enable the user to select the liquid from the set of pre-defined liquids. The first user interface 110 may further be configured to enable the user to select the quantity of the liquid. In some aspects of the present disclosure, the first user interface 110 may be configured to enable the user to input the data related to the new liquid that may be different from the set of pre-defined liquids. In some aspects of the present disclosure, the first user interface 110 may be configured to enable the user to register on the system 100. Furthermore, the first user interface 110 may be configured to enable the user to enable a password protection for logging-in (and/or authentication) to the system 100. Examples of the first input interface may include, but are not limited to, a touch interface, a mouse, a keyboard, a motion recognition unit, a gesture recognition unit, a voice recognition unit, or the like. Aspects of the present disclosure are intended to include or otherwise cover any type of the first input interface including known, related art, and/or later developed technologies. The first user interface 110 may further include a first output interface for displaying (or presenting) an output to the user. The first user interface 110 by way of the first output interface may be configured to present (or display) one or more notifications related to mixing and/or delivery of the liquid. Examples of the first output interface may include, but are not limited to, a digital display, an analog display, a touch screen display, a graphical user interface, a website, a webpage, a keyboard, a mouse, a light pen, an appearance of a desktop, and/or illuminated characters. Aspects of the present disclosure are intended to include and/or otherwise cover any type of the first output interface including known and/or related, or later developed technologies.
The first processing unit 112 may include suitable logic, instructions, circuitry, interfaces, and/or codes for executing various operations, such as the operations associated with the user device 102, or the like. In some aspects of the present disclosure, the first processing unit 112 may utilize one or more processors such as Arduino or raspberry pi or the like. Further, the first processing unit 112 may be configured to control one or more operations executed by the user device 102 in response to the input received at the first user interface 110 from the user. Examples of the first processing unit 112 may include, but are not limited to, an application-specific integrated circuit (ASIC) processor, a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a field-programmable gate array (FPGA), a Programmable Logic Control unit (PLC), and the like. Aspects of the present disclosure are intended to include or otherwise cover any type of first processing unit 112 including known, related art, and/or later developed processing units.
The first memory 114 may be configured to store the logic, instructions, circuitry, interfaces, and/or codes of the first processing unit 112, data associated with the user device 102, and/or data associated with the system 100. In some aspects of the present disclosure, the first memory 114 may be configured to store the one or more compositions (in terms of the weight, the volume, and/or the one or more properties of the liquid) for mixing of the liquid. In some aspects of the present disclosure, the first memory 114 may be configured to enable the user to save the data related to the liquid. Examples of the first memory 114 may include, but are not limited to, a Read-Only Memory (ROM), a Random-Access Memory (RAM), a flash memory, a removable storage drive, a hard disk drive (HDD), a solid-state memory, a magnetic storage drive, a Programmable Read Only Memory (PROM), an Erasable PROM (EPROM), and/or an Electrically EPROM (EEPROM). Aspects of the present disclosure are intended to include or otherwise cover any type of first memory 114 including known, related art, and/or later developed memories.
The first liquid delivery console 116 may be configured as a computer-executable application, to be executed by the first processing unit 112. The first liquid delivery console 116 may include suitable logic, instructions, and/or codes for executing various operations and may be controlled by the server 106. The one or more computer executable applications may be stored in the first memory 114. Examples of the one or more computer executable applications may include, but are not limited to, an audio application, a video application, a social media application, a navigation application, or the like. Aspects of the present disclosure are intended to include or otherwise cover any type of the computer executable application including known, related art, and/or later developed computer executable applications.
The first communication interface 118 may be configured to enable the user device 102 to communicate with the delivery device 104 and the server 106. Examples of the first communication interface 118 may include, but are not limited to, a modem, a network interface such as an Ethernet card, a communication port, and/or a Personal Computer Memory Card International Association (PCMCIA) slot and card, an antenna, a radio frequency (RF) transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a coder-decoder (CODEC) chipset, a subscriber identity module (SIM) card, and a local buffer circuit. It will be apparent to a person of ordinary skill in the art that the first communication interface 118 may include any device and/or apparatus capable of providing wireless or wired communications between the user device 102, the delivery device 104, and the server 106.
In an exemplary aspect of the present disclosure, the liquid delivery device 104 (hereinafter interchangeably referred to and designated as “the delivery device 104”) may include a fluid inlet 120, a fluid outlet 122, a channel system 124, and a sensing unit 130.
The fluid inlet 120 may be configured to dispense the liquid towards the fluid outlet 122 through the channel system 124. In some aspects of the present disclosure, the channel system 124 may have a plurality of channels 126 that may connect the fluid inlet 120 to the fluid outlet 122 by way of one or more nozzles 128.
Each channel of the plurality of channels 126 may be configured to carry the liquid from the fluid inlet 120 to the fluid outlet 122. Specifically, the plurality of channels 126 may have a first channel 126a and a second channel 126b. Although FIG. 1 illustrates that the plurality of channels 126 has two channels (i.e., the first channel 126a and the second channel 126b), it will be apparent to a person skilled in the art that the scope of the present disclosure is not limited to it. In various other aspects, the plurality of channels 126 may have any number of channels, without deviating from the scope of the present disclosure. In such a scenario, each channel may be structurally and functionally similar to the first channel and/or the second channel 126b as described herein.
Each nozzle of the one or more nozzles 128 may be configured to connect the fluid inlet 120 to the fluid outlet 122 through the plurality of channels. Specifically, the one or more nozzles 128 may have a first nozzle 128a and a second nozzle 128b. Although FIG. 1 illustrates that the one or more nozzles have two nozzles (i.e., the first nozzle 128a and the second nozzle 128b), it will be apparent to a person skilled in the art that the scope of the present disclosure is not limited to it. In various other aspects, the one or more nozzles may have any number of nozzles, without deviating from the scope of the present disclosure. In such a scenario, each nozzle may be structurally and functionally similar to the first nozzle 128a and/or the second nozzle 128b as described herein.
In some aspects of the present disclosure, the liquid delivery device 104 may further include a delivery motor 156 that may be configured to deliver (or pump) the liquid from the fluid inlet 120 to the fluid outlet 122 via the plurality of channels 126 of the channel system 124.
The sensing unit 130 may be configured to determine a set of numerical values for a set of configuration parameters that may correspond to the delivery of the liquid. In some aspects of the present disclosure, the set of configuration parameters may include at least one of, one or more environmental parameters, and one or more calibration parameters of the delivery motor 156. Examples of the one or more environmental parameters such as temperature, humidity, atmospheric pressure, and the like. Aspects of the present disclosure are intended to include or otherwise cover any type of the one or more environmental parameters including known, related art, and/or based on later developed environmental sensing techniques. Examples of the one or more calibration parameters of the delivery motor 156 may include electrical load on the delivery motor 156 (i.e., electrical current and/or electrical voltage drawn by the delivery motor 156), one or more parameters related to physical condition (in terms of wear-and-tear) of the delivery motor 156, rotational speed of the delivery motor 156, performance efficiency of the delivery motor 156, and the like. Aspects of the present disclosure are intended to include or otherwise cover any type of the one or more calibration parameters including known, related art, and/or based on later developed calibration techniques.
In some aspects of the present disclosure, the delivery device 104 may further include a second user interface 134, a second processing unit 136, a second memory 138, a second liquid delivery console 140, and a second network interface 142, that may be communicatively coupled to each other by way of an internal communication bus 144.
The second user interface 134 may include a second input interface (not shown) for receiving inputs from the user. In some aspects of the present disclosure, the second input interface may be configured to enable the user to select the liquid. The second input interface may further be configured to enable the user to select the quantity of the liquid. Furthermore, the second input interface may further be configured to receive one or more notifications related to the mixing and/or the delivery of the liquid. Furthermore, the second input interface may be configured to enable the user to enable the password protection for logging-in (and/or authentication) to the system 100. In some aspects of the present disclosure, the second input interface may be configured to enable the user to register on the system 100. Examples of the second input interface may include, but are not limited to, a touch interface, a mouse, a keyboard, a motion recognition unit, a gesture recognition unit, a voice recognition unit, or the like. Aspects of the present disclosure are intended to include or otherwise cover any type of the second input interface including known, related art, and/or later developed technologies. The second user interface 134 may further include a second output interface for displaying (or presenting) outputs and/or notifications to the user. Examples of the second output interface may include, but are not limited to, a digital display, an analog display, a touch screen display, a graphical user interface, a website, a webpage, a keyboard, a mouse, a light pen, an appearance of a desktop, and/or illuminated characters. Aspects of the present disclosure are intended to include and/or otherwise cover any type of the second output interface including known and/or related, or later developed technologies.
The second processing unit 136 may include suitable logic, instructions, circuitry, interfaces, and/or codes for executing various operations, such as the operations associated with the delivery device 104, or the like. In some aspects of the present disclosure, the second processing unit 136 may be configured to receive one or more instructions from the processing circuitry 158 of the server 106. The second processing unit 136 may further be configured to alter the one or more calibration parameters of the delivery motor 156 to alter the flow rate of the liquid. In some aspects of the present disclosure, the second processing unit 136 may utilize one or more processors such as Arduino or raspberry pi or the like. Further, the second processing unit 136 may be configured to control one or more operations executed by the delivery device 104 in response to the inputs received by the user at the second user interface 134 from the user. Examples of the second processing unit 136 may include, but are not limited to, an application-specific integrated circuit (ASIC) processor, a reduced instruction set computing (RISC) processor, a complex instruction set computing (CISC) processor, a field-programmable gate array (FPGA), a Programmable Logic Control unit (PLC), and the like. Aspects of the present disclosure are intended to include or otherwise cover any type of second processing unit 136 including known, related art, and/or later developed processing units.
The second memory 138 may be configured to store the logic, instructions, circuitry, interfaces, and/or codes of the second processing unit 136, data associated with the delivery device 104, and/or data associated with the system 100. In some aspects of the present disclosure, the second memory 138 may be configured to store the one or more compositions (in terms of the weight, the volume, and/or the one or more properties of the liquid) for mixing of the liquid. In some aspects of the present disclosure, the second memory 138 may be configured to enable the user to save the data related to the liquid. Examples of the second memory 138 may include, but are not limited to, a Read-Only Memory (ROM), a Random-Access Memory (RAM), a flash memory, a removable storage drive, a hard disk drive (HDD), a solid-state memory, a magnetic storage drive, a Programmable Read Only Memory (PROM), an Erasable PROM (EPROM), and/or an Electrically EPROM (EEPROM). Aspects of the present disclosure are intended to include or otherwise cover any type of second memory 138 including known, related art, and/or later developed memories.
The second liquid delivery console 140 may be configured as a computer-executable application, to be executed by the second processing unit 136. The second liquid delivery console 140 may include suitable logic, instructions, and/or codes for executing various operations and may be controlled by the server 106. The one or more computer executable applications may be stored in the second memory 138. Examples of the one or more computer executable applications may include, but are not limited to, an audio application, a video application, a social media application, a navigation application, or the like. Aspects of the present disclosure are intended to include or otherwise cover any type of the computer executable application including known, related art, and/or later developed computer executable applications.
The second communication interface 142 may be configured to enable the delivery device 104 to communicate with the server 106 and the user device 102. Examples of the second communication interface 142 may include, but are not limited to, a modem, a network interface such as an Ethernet card, a communication port, and/or a Personal Computer Memory Card International Association (PCMCIA) slot and card, an antenna, a radio frequency (RF) transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a coder-decoder (CODEC) chipset, a subscriber identity module (SIM) card, and a local buffer circuit. It will be apparent to a person of ordinary skill in the art that the second communication interface 142 may include any device and/or apparatus capable of providing wireless or wired communications between the delivery device 104, the user device 102 and the server 106.
The server 106 may be a network of computers, a software framework, or a combination thereof, that may provide a generalized approach to create the server implementation. Examples of the server 106 may include, but are not limited to, personal computers, laptops, mini-computers, mainframe computers, any non-transient and tangible machine that can execute a machine-readable code, cloud-based servers, distributed server networks, or a network of computer systems. The server 106 may be realized through various web-based technologies such as, but not limited to, a Java web-framework, a .NET framework, a personal home page (PHP) framework, or any web-application framework. The server 106 may include processing circuitry 158 and one or more memory units (hereinafter, collectively referred to and designated as “Database 160”).
In some aspects, the processing circuitry 158 may include suitable logic, instructions, circuitry, interfaces, and/or codes for executing various operations of the system 100. The processing circuitry 158 may be configured to host and enable the first liquid delivery console 112 running on (or installed on) the user device 102 and/or the second liquid delivery console 140 running on (or installed on) the delivery device 104 to execute the operations associated with the system 100 by communicating one or more commands and/or instructions over the communication network 108.
The processing circuitry 158 may be configured to receive the set of numerical values for the set of configuration parameters from the sensing unit 130. The processing unit 158 may further be configured to determine a flow rate of the liquid based on the set of numerical values for the set of configuration parameters. Furthermore, the processing unit 158 may be configured to adjust the rate of the iterative update of the set of numerical values for the set of configuration parameters based on the one or more inputs from the user. Furthermore, the processing unit 158 may be configured to determine the threshold value based on the rate of the iterative update. In some aspects of the present disclosure, the processing circuitry 158 may be configured to determine a difference between the flow rate of the liquid and a pre-defined optimal flow rate of the liquid. Furthermore, the processing unit 158 may be configured to iteratively update the set of numerical values for the set of configuration parameters to iteratively update the flow rate of the liquid unless the difference between the flow rate of the liquid and a pre-defined optimal flow rate of the liquid is less than a threshold value. In some aspects of the present disclosure, to adjust the flow rate of the liquid, the processing circuitry 158 may be configured to adjust a rotational speed of the delivery motor 156 and a duration of rotation of the delivery motor 156.
In some aspects of the present disclosure, the processing circuitry 158 may be configured to adjust the rate of the iterative update of the flow rate using a machine learning based dynamic learning rate strategy. In some aspects of the present disclosure, the dynamic learning rate strategy may enable different learning rates and utilize different training datasets based on the one or more inputs from the user. Examples of the processing circuitry 158 may include, but are not limited to, an ASIC processor, a RISC processor, a CISC processor, a FPGA, and the like. Aspects of the present disclosure are intended to include or otherwise cover any type of processing circuitry 158, including known, related art, and/or later developed technologies.
In some aspects, the database 160 may be configured to store the logic, instructions, circuitry, interfaces, and/or codes of the processing circuitry 158 for executing a number of operations. The database 160 may be further configured to store therein, data associated with users registered with the system 100. In some aspects of the present disclosure, the database 160 may be configured to store one or more of, user data, instructions data, training data, the set of configuration parameters, flow rate data, optimal flow rate data, and the like corresponding to the system 100. Some aspects of the present disclosure are intended to include and/or otherwise cover any type of the data associated with the users registered with the system 100. Examples of the database 160 may include but are not limited to, a ROM, a RAM, a flash memory, a removable storage drive, a HDD, a solid-state memory, a magnetic storage drive, a PROM, an EPROM, and/or an EEPROM. Aspects of the present disclosure are intended to include or otherwise cover any type of database 160, including known, related art, and/or later developed databases.
The communication network 108 may include suitable logic, circuitry, and interfaces that may be configured to provide a number of network ports and a number of communication channels for transmission and reception of data related to operations of various entities (such as the user device 102, the delivery device 104, and the server 106) of the system 100. Each network port may correspond to a virtual address (or a physical machine address) for transmission and reception of the communication data. For example, the virtual address may be an Internet Protocol Version 4 (IPV4) (or an IPV6 address) and the physical address may be a Media Access Control (MAC) address. The communication network 108 may be associated with an application layer for implementation of communication protocols based on one or more communication requests from the user device 102, the delivery device 104, and the server 106. The communication data may be transmitted or received, via the communication protocols. Examples of the communication protocols may include, but are not limited to, Hypertext Transfer Protocol (HTTP), File Transfer Protocol (FTP), Simple Mail Transfer Protocol (SMTP), Domain Network System (DNS) protocol, Common Management Interface Protocol (CMIP), Transmission Control Protocol and Internet Protocol (TCP/IP), User Datagram Protocol (UDP), Long Term Evolution (LTE) communication protocols, or any combination thereof.
In some aspects of the present disclosure, the communication data may be transmitted or received via at least one communication channel of a number of communication channels in the communication network 108. The communication channels may include, but are not limited to, a wireless channel, a wired channel, a combination of wireless and wired channel thereof. The wireless or wired channel may be associated with a data standard which may be defined by one of a Local Area Network (LAN), a Personal Area Network (PAN), a Wireless Local Area Network (WLAN), a Wireless Sensor Network (WSN), Wireless Area Network (WAN), Wireless Wide Area Network (WWAN), a metropolitan area network (MAN), a satellite network, the Internet, an optical fiber network, a coaxial cable network, an infrared (IR) network, a radio frequency (RF) network, and a combination thereof. Aspects of the present disclosure are intended to include or otherwise cover any type of communication channel, including known, related art, and/or later developed technologies.
In some aspects of the present disclosure, the system 100 may be configured as a centralized system and may not include the user device 102 and server 106. In such a scenario, the delivery device 104 may be configured to serve one or more functionalities of the user device 102 and/or the server 106. For example, the second user interface 134 may be configured to serve one or more functionalities of the first user interface 110, the second processing unit 136 may be configured to serve one or more functionalities of the processing circuitry 158 of the server and/or one or more functionalities of the first processing unit 112. The second memory 138 may be configured to serve one or more functionalities of the first memory 114 and/or one or more functionalities of the database 160.
In operation, the system 100 by way of the sensing unit 130 may determine the set of numerical values for the set of configuration parameters that may correspond to the delivery of the liquid. The system 100 by way of the processing circuitry 158 may further receive the set of numerical values for the set of configuration parameters from the sensing unit 130. Furthermore, the system 100 by way of the processing circuitry 158 may determine the flow rate of the liquid based on the set of numerical values for the set of configuration parameters. Furthermore, the system 100 by way of the processing circuitry 158 may adjust the rate of the iterative update of the set of numerical values for the set of configuration parameters based on the one or more inputs from the user. Furthermore, the system 100 by way of the processing circuitry 158 may iteratively update the set of numerical values for the set of configuration parameters to iteratively update the flow rate of the liquid unless the difference between the flow rate of the liquid and the pre-defined optimal flow rate of the liquid is less than the threshold value. In some aspects of the present disclosure, to adjust the flow rate of the liquid, the processing circuitry 158 may be configured to adjust the rotational speed of the delivery motor 156 and the duration of rotation of the delivery motor 156.
FIG. 2 is a block diagram that illustrates the server 106 of FIG. 1, in accordance with an exemplary aspect of the present disclosure. The server 106 may include the processing circuitry 158 and the database 160. The server 106 may further include a network interface 200 and an input/output (I/O) interface 202. The processing circuitry 158, the database 160, the network interface 200, and the input/output (I/O) interface 202 may be configured to communicate with each other by way of a first communication bus 203.
In an exemplary aspect of the present disclosure, the processing circuitry 158 may include a data exchange engine 204, a registration engine 206, an authentication engine 208, a flow rate engine 210, a rate adjustment engine 212, and a notification engine 214 communicatively coupled to each other by way of a second communication bus 216. It will be apparent to a person having ordinary skill in the art that the server 106 is for illustrative purposes and not limited to any specific combination of hardware circuitry and/or software.
The data exchange engine 204 may be configured to enable transfer of data from the database 160 to various engines of the processing circuitry 158. The data exchange engine 204 may further be configured to enable transfer of data and/or instructions from the user device 102 and/or the delivery device 104 to the server 106.
The registration engine 206 may be configured to enable the users to register into the system 100 by providing registration data through a registration menu (not shown) of the first liquid delivery console 112 that may be displayed by way of the user device 102 or the second liquid delivery console 140 that may be displayed by way of the delivery device 104.
The authentication engine 208 by way of the data exchange engine 204 may be configured to fetch the registration data of the user and authenticate the registration data of the user. The authentication engine 208, upon successful authentication of the registration data of the user, may be configured to enable the user to log-in or sign up to the system 100.
The flow rate engine 210, by way of the data exchange engine may be configured to receive the set of numerical values for the set of configuration parameters from the delivery device 104. The flow rate engine 210, may further be configured to determine the flow rate for the liquid based on the set of numerical values for the set of configuration parameters. In some aspects of the present disclosure, the flow rate engine 210 may be configured to determine the flow rate for the liquid based on the set of numerical values for the set of configuration parameters using one or more artificial intelligence (AI) techniques. In such a scenario, the flow rate engine 210 may be configured to receive flow rate training dataset from the database 160. The flow rate engine 210 may be configured to adjust a first set of training parameters of the flow rate engine 210 through an iterative training based on the flow rate training dataset. In some other aspects of the present disclosure, the flow rate engine 210 may be configured to determine the flow rate for the liquid based on the set of numerical values for the set of configuration parameters using one or more model based techniques. In such a scenario, the flow rate engine 210 may generate one or more mathematical models to determine a relationship between the set of configuration parameters and the flow rate of the liquid. The flow rate engine 210 may further be configured to iteratively update the set of numerical values for the set of configuration parameters to iteratively update the flow rate of the liquid unless the difference between the flow rate of the liquid and a pre-defined optimal flow rate of the liquid is less than the threshold value.
The rate adjustment engine 212 may be configured to adjust the rate of the iterative update of the set of numerical values for the set of configuration parameters based on the one or more inputs from the user. The rate adjustment engine 212 may further be configured to determine the threshold value based on the rate of the iterative update. In some aspects of the present disclosure, the threshold value may be zero. In some other aspects of the present disclosure, the rate adjustment engine 212 may be configured to generate the machine learning based dynamic learning rate strategy to determine the threshold value and adjust the rate of the iterative update of the flow rate. In such a scenario, the rate adjustment engine 212, by way of the data exchange engine 204, may be configured to receive the flow rate training dataset and/or a rate adjustment training dataset from the database 160. The rate adjustment engine 212 may further be configured to adjust a second set of training parameters of the rate adjustment engine 212 through an iterative training based on the flow rate training dataset and/or a rate adjustment training dataset. In some aspects of the present disclosure, the dynamic learning rate strategy may enable different learning rates and utilize different training datasets and/or segments of the rate adjustment training dataset based on the one or more inputs from the user.
The notification engine 214 may be configured to generate one or more notifications for the system 100 that may be displayed (or presented) by at least one of, the user device 102 and the delivery device 104. It will be apparent to a person skilled in the art that the aspects of the present disclosure are intended to include or cover any type of notification generated by the system 100 and/or presented to the user by the system 100.
In some aspects of the present disclosure, the database 160 may be segregated into one or more repositories that may be configured to store a specific type of data. In an exemplary aspect of the present disclosure, the database 160 may include an instructions repository 218, a user data repository 220, a training data repository 222, a viscosity repository 224, a flow rate repository 226, and an optimum data repository 228.
The instructions repository 218 may be configured to store instructions data corresponding to the server 106. The instructions data may include data and metadata of one or more instructions corresponding to the various entities of the server 106 such as the processing circuitry 156, the I/O interface 200 and/or the network interface 202. It will be apparent to a person skilled in the art that the aspects of the present disclosure are intended to include or cover any type of instructions data of the server 106, and thus must not be considered as a limitation of the present disclosure.
The user data repository 220 may be configured to store user data of the system 100. The user data may include data and metadata of the data of authenticated users that are registered on the system 100. In some aspects of the present disclosure, the user data repository 220 may further be configured to store partial data and/or partial metadata of the user data corresponding to users that fail to register and/or authenticate on the system 100. It will be apparent to a person skilled in the art that the aspects of the present disclosure are intended to include or cover any type of user data and/or metadata of the user data of the system 100, and thus must not be considered as a limitation of the present disclosure.
The training data repository 222 may be configured to store one or more training datasets such as the flow rate training dataset and/or the rate adjustment training dataset for training of the flow rate engine 210 and/or the rate adjustment engine 212. In some aspects of the present disclosure, the one or more training datasets of training data repository 222 may be initially generated or pre-set datasets. In some other aspects of the present disclosure, the one or more training datasets may be iteratively updated by the system 100 based on a learning of the system 100. In some aspects of the present disclosure, the training data repository 222 may include the rate adjustment training dataset segregated into a number of segments such that one or more segments of the rate adjustment training dataset may be used by the rate adjustment engine 212 based on the one or more inputs from the user.
The parameter repository 224 may be configured to store the numerical value of the set of configuration parameters corresponding to the delivery of the liquid. The flow rate repository 226 may be configured to store the flow rates of the liquid. The optimum data repository 228 may be configured to store the optimum flow rate of the liquid.
FIG. 3 illustrates a flow chart of the liquid delivery method 300, in accordance with an exemplary aspect of the present disclosure.
At step 302, the system 100 by way of the sensing unit 130 may determine the set of numerical values for the set of configuration parameters that may correspond to the delivery of the liquid.
At step 304, the system 100 by way of the processing circuitry 158 may receive the set of numerical values for the set of configuration parameters from the sensing unit 130.
At step 306, the system 100 by way of the processing circuitry 158 may determine the flow rate of the liquid based on the set of numerical values for the set of configuration parameters.
At step 308, the system 100 by way of the processing circuitry 158 may adjust the rate of the iterative update of the set of numerical values for the set of configuration parameters based on the one or more inputs from the user.
At step 310, the system 100 by way of the processing circuitry 158 may determine the threshold value based on the rate of the iterative update.
At step 312, the system 100 by way of the processing circuitry 158 may iteratively update the set of numerical values for the set of configuration parameters to iteratively update the flow rate of the liquid unless the difference between the flow rate of the liquid and the pre-defined optimal flow rate of the liquid is less than the threshold value. In some aspects of the present disclosure, to adjust the flow rate of the liquid, the processing circuitry 158 may be configured to adjust the rotational speed of the delivery motor 156 and the duration of rotation of the delivery motor 156.
Aspects of the present disclosure are disclosed in perspective of a single liquid (i.e., the liquid), however it will be apparent to a person skilled in the art that the scope of the present disclosure is not limited to it. In various other aspects, the liquid delivery system 100 may to perform mixing and delivery more than one liquids, without deviating from the scope of the present disclosure. In such a scenario, the system 100 may be configured to perform one or more functionalities similar to those aforementioned for delivery of the liquid.
Thus, the liquid delivery system 100 and the liquid delivery method 300 of the present disclosure enables an accurate liquid measurement without any contaminations and ensures highly efficient and accurate liquid delivery. The system 100 by way of the processing circuitry 158 provides an iterative learning based approach for accurate measurement of quantity of the liquid based on set of numerical values for the set of configuration parameters that corresponds to the delivery of the liquid. Further, the system 100 by way of the processing circuitry enables a control of the learning (i.e., rate of iterative update) based on the one or more inputs received from the user based on the machine learning based dynamic learning rate strategy that enables the user to control the learning rate of the system 100 and further enables the user to train the system 100 based on the criticality of the accuracy in measurement of the liquid. Furthermore, the system 100 by way of the delivery motor 156 delivers the liquid from the fluid inlet 120 to the fluid outlet 122 through the channel system 124 at a very high flow such that the chances of contamination of the liquid can be minimized.
The foregoing discussion of the present disclosure has been presented for purposes of illustration and description. It is not intended to limit the present disclosure to the form or forms disclosed herein. In the foregoing Detailed Description, for example, various features of the present disclosure are grouped together in one or more aspects, configurations, or aspects for the purpose of streamlining the disclosure. The features of the aspects, configurations, or aspects may be combined in alternate aspects, configurations, or aspects other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention the present disclosure requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed aspect, configuration, or aspect. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate aspect of the present disclosure.
Moreover, though the description of the present disclosure has included description of one or more aspects, configurations, or aspects and certain variations and modifications, other variations, combinations, and modifications are within the scope of the present disclosure, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative aspects, configurations, or aspects to the extent permitted, including alternate, interchangeable and/or equivalent structures, functions, ranges or steps to those claimed, whether or not such alternate, interchangeable and/or equivalent structures, functions, ranges or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter.
As one skilled in the art will appreciate, the system 100 includes a number of functional blocks in the form of a number of units and/or engines. The functionality of each unit and/or engine goes beyond merely finding one or more computer algorithms to carry out one or more procedures and/or methods in the form of a predefined sequential manner, rather each engine explores adding up and/or obtaining one or more objectives contributing to an overall functionality of the system 100. Each unit and/or engine may not be limited to an algorithmic and/or coded form, rather may be implemented by way of one or more hardware elements operating together to achieve one or more objectives contributing to the overall functionality of the system 100. Further, as it will be readily apparent to those skilled in the art, all the steps, methods and/or procedures of the system 100 are generic and procedural in nature and are not specific and sequential.
Certain terms are used throughout the following description and claims to refer to particular features or components. As one skilled in the art will appreciate, different persons may refer to the same feature or component by different names. This document does not intend to distinguish between components or features that differ in name but not structure or function. While various aspects of the present disclosure have been illustrated and described, it will be clear that the present disclosure is not limited to these aspects only. Numerous modifications, changes, variations, substitutions, and equivalents will be apparent to those skilled in the art, without departing from the spirit and scope of the present disclosure, as described in the claims. , Claims:1. A liquid delivery system (100) comprising:
a sensing unit (130) configured to determine a set of numerical values for a set of configuration parameters that corresponds to delivery of a liquid;
processing circuitry (158) that is coupled to the sensing unit (130), and configured to:
receive, from the sensing unit (130), the set of numerical values for the set of configuration parameters;
determine a flow rate of the liquid based on the set of numerical values for the set of configuration parameters; and
iteratively update the set of numerical values for the set of configuration parameters to iteratively update the flow rate of the liquid unless a difference between the flow rate of the liquid and a pre-defined optimal flow rate of the liquid is less than a threshold value;
wherein, the processing circuitry (158) is configured to (i) adjust a rate of the iterative update of the set of numerical values for the set of configuration parameters based on one or more inputs from a user, and (ii) determine the threshold value based on the rate of the iterative update.

2. The liquid delivery system (100) as claimed in claim 1 further comprising a liquid delivery device (104) comprising (i) a fluid inlet (120), (ii) a fluid outlet (122), and (iii) a channel system (124) such that the channel system (124) having a plurality of channels (126) connects the fluid inlet (120) to the fluid outlet (122) by way of one or more nozzles (128).

3. The liquid delivery system (100) as claimed in claim 2, wherein the liquid delivery device (104) further comprising a delivery motor (156) that is configured to deliver the liquid from the fluid inlet (120) to the fluid outlet (122) via the channel system (124).
4. The liquid delivery system (100) as claimed in claim 3, wherein the set of configuration parameters comprising at least one of, one or more environmental parameters, and one or more calibration parameters of the delivery motor (156).

5. The liquid delivery system (100) as claimed in claim 3, wherein, to adjust the flow rate of the liquid, the processing circuitry (158) is configured to adjust a rotational speed of the delivery motor (156) and a duration of rotation of the delivery motor (156).

6. The liquid delivery system (100) as claimed in claim 1, wherein the processing circuitry (158) is configured to adjust the rate of the iterative update of the flow rate by way of a machine learning based dynamic learning rate strategy.

7. A liquid delivery method (300) comprising:
determining, by way of a sensing unit (130), a set of numerical values for a set of configuration parameters that corresponds to delivery of a liquid;
receiving, by way of processing circuitry (158), the set of numerical values for the set of configuration parameters from the sensing unit (130);
determining, by way of the processing circuitry (158), a flow rate of the liquid based on the set of numerical values for the set of configuration parameters;
adjusting, by way of the processing circuitry (158), a rate of the iterative update of the set of numerical values for the set of configuration parameters based on one or more inputs from the user;
determining, by way of the processing circuitry (158), a threshold value based on the rate of the iterative update; and
updating iteratively, by way of the processing circuitry (158), the set of numerical values for the set of configuration parameters to iteratively update the flow rate of the liquid, unless a difference between the flow rate of the liquid and a pre-defined optimum flow rate of the liquid is less than the threshold value.
8. The liquid delivery method (300) as claimed in claim 7 further comprising connecting a fluid inlet (120) to a fluid outlet (122) through a plurality of channels of a channel system (124) by way of one or more nozzles (126).

9. The liquid delivery method (300) as claimed in claim 8, wherein upon connecting the fluid inlet to the fluid outlet, the method (300) further comprising delivering, by way of a delivery motor (156), the liquid from the fluid inlet (120) to the fluid outlet (122) via the channel system (124).

10. The liquid delivery method (300) as claimed in claim 9, wherein the set of configuration parameters comprising at least one of, one or more environmental parameters, and one or more calibration parameters of the delivery motor (156).

11. The liquid delivery method (300) as claimed in claim 9, wherein, for adjusting the flow rate of the liquid, the liquid delivery method (300) comprising adjusting, by way the processing circuitry (158) (i) a rotational speed of the delivery motor (156) and (ii) a duration of rotation of the delivery motor (156).

12. The liquid delivery method (300) as claimed in claim 7, wherein, for adjusting the rate of the iterative update of the flow the method (300) comprising a machine learning based dynamic learning rate strategy.