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PLUGIN ADD-ON DEVICE FOR FLOW MONITORING, CONTROL, AND HEALTH PREDICTION WITH RECOMMENDATIONS IN INDUSTRIAL CARBONATED BEVERAGE FILLING MACHINES USING NRF AND XBEE MULTI-PRIVATE NETWORK GATEWAY

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PLUGIN ADD-ON DEVICE FOR FLOW MONITORING, CONTROL, AND HEALTH PREDICTION WITH RECOMMENDATIONS IN INDUSTRIAL CARBONATED BEVERAGE FILLING MACHINES USING NRF AND XBEE MULTI-PRIVATE NETWORK GATEWAY

ORDINARY APPLICATION

Published

date

Filed on 22 November 2024

Abstract

A plugin add-on device for flow monitoring, control, and health prediction with recommendations in industrial carbonated beverage filling machines using nrf and xbee multi-private network gateway comprises FMDSTS Node, equipped with the Cortex A710 Processor Board, XBee Module, actuator, current sensor, temperature sensor, vibration sensor, LED , and the power supply is utilized to remotely monitor and effectively control operational parameters of carbonated beverage filling machines for industrial purposes, improving operational efficiency and reducing interruptions the FMDSRS Node, comprising a Cortex-A710 Processor Board, XBee Module, nRF Module, 7” capacitive touch display, buzzer and power supply, adds functions by allowing the staff to visualize data, receive notifications and interact with the private network, allowing them to address the problems immediately.

Patent Information

Application ID202411090831
Invention FieldCOMPUTER SCIENCE
Date of Application22/11/2024
Publication Number49/2024

Inventors

NameAddressCountryNationality
DR. KAILASH CHANDRA JUGLANLOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
SUMIT MITTULOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
DR. SHAILESH KUMAR SINGHLOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
GAURAV GUPTALOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
DR. SACHIN KUMAR SINGHLOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
DR. (AR.) ATUL KUMAR SINGLALOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia

Applicants

NameAddressCountryNationality
LOVELY PROFESSIONAL UNIVERSITYJALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia

Specification

Description:FIELD OF THE INVENTION
This invention relates to plugin add-on device for flow monitoring, control, and health prediction with recommendations in industrial carbonated beverage filling machines using nrf and xbee multi-private network gateway.
BACKGROUND OF THE INVENTION
The novel device is a plug-in variant which improves, regulates and conducts predictive maintenance of the industrial equipment used for filling carbonated beverages. The system implements a distributed multi-node architecture for networked acquisition, processing, and communication in real-time. Key measures like flow, current, temperature, and vibrations are monitored to facilitate the control and safeguard the equipment from defects at an early stage. The data serves the system and is relayed to the specific cloud containing advanced analytics and monitoring technologies based on machine learning and artificial intelligence, able to offer practical suggestions and suggest where problems will occur. The solution is presented using a simple interface of a touch display and a web dashboard that allows the operators and other authorized users to have real-time operational views, performance forecasts and maintenance notifications to reduce downtime and improve operational flexibility.
The project considers the modern threats in the scope of carbonated beverage filling process, where equipment being idle, inefficiency, and faulty machinery functioning untraced may incur high production and operational losses. Systems in use nowadays are mostly devoid of features for real-time monitoring, predictive maintenance, or automated capabilities which make it rather hard to prevent issues from developing into critical failures. This innovation closes the gap by facilitating real time tracking of critical machine parameters, predicting possible failures, and providing recommendations using artificial intelligence. This system provides a safe approach to beverage filling by reducing the risk of unplanned machine failures, enhancing equipment utilization and reducing maintenance expenses, thus improving performance and reliability of the process.
CN113404325B: The invention provides an intelligent grouting joint filling machine for single-port wall cracks and a construction method, comprising a bottom plate, wherein lifting mechanisms are symmetrically fixed on the upper surface of the bottom plate, a connecting beam is fixed between the two lifting mechanisms, the middle part of the connecting beam is connected with a horizontal moving device in a sliding manner, a grouting mechanism is fixed on the top of the horizontal moving device, a screeding mechanism is fixed on the top of the grouting mechanism, and self-locking universal wheels are symmetrically fixed on the lower surface of the bottom plate. According to the invention, the single grouting mechanism is arranged, the grouting mechanism is driven to move through the lifting mechanism and the horizontal moving mechanism, grouting is carried out on the cracks, the use cost is low, the grouting mechanism is flexible to use, the grouting mechanism is suitable for most grouting occasions, the rotating rod is driven to rotate through the fourth servo motor, the second T-shaped block is driven to slide through the first shifting column, further reciprocating sliding of the screeding head is realized, the screeding head screeds the slurry on the cracks, and the attractiveness is improved.
RESEARCH GAP: Multi-private network integration using XBee and nRF modules for real-time monitoring, predictive maintenance, and AI-driven recommendations in carbonated beverage filling machines is the novelty of the system.
US11103899B2: An apparatus for filling a drink including a drink supply pipe line for supplying a drink to a filling machine, the drink supply pipe line including at least two supply pipe lines of a first supply pipe line for supplying a non-sterilized carbonated drink, a second supply pipe line for supplying a high acidic carbonated drink or a low acidic carbonated drink and a third supply pipe line for supplying a high acid beverage or a low acid beverage, and an aseptic chamber surrounding at least the apparatus for filling the drink.
RESEARCH GAP: Multi-private network integration using XBee and nRF modules for real-time monitoring, predictive maintenance, and AI-driven recommendations in carbonated beverage filling machines is the novelty of the system.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
The innovation works as an independent unit intended to assess the operating condition as well as the measuring and technical elements of industrial equipment for the filling of carbonated soft drinks. It is composed of a number of interrelated nodes whose functions are related to data collection, data processing and data communication. The first node, which is located inside the filling machine housing, monitors hydrophysical parameters, which are such operational characteristics as flow rates, current, temperature and vibrations. This node makes it possible to ensure the necessary quality of data acquisition, which in turn is important in the purpose of real time anomaly detection. The second node presents collected data and processes it and also presents a screen interface for the "machine performance" level and interacts with its operator. This node also presents the communication network while transferring the data securely to the center node. The operator can visually review on-site the constraints and via the display interface receive warnings when on-site action is necessary. In addition, other nodes can be connected to the assembly node in order to exchange information.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a"," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", "third", and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The innovation works as an independent unit intended to assess the operating condition as well as the measuring and technical elements of industrial equipment for the filling of carbonated soft drinks. It is composed of a number of interrelated nodes whose functions are related to data collection, data processing and data communication. The first node, which is located inside the filling machine housing, monitors hydrophysical parameters, which are such operational characteristics as flow rates, current, temperature and vibrations. This node makes it possible to ensure the necessary quality of data acquisition, which in turn is important in the purpose of real time anomaly detection. The second node presents collected data and processes it and also presents a screen interface for the "machine performance" level and interacts with its operator. This node also presents the communication network while transferring the data securely to the center node. The operator can visually review on-site the constraints and via the display interface receive warnings when on-site action is necessary. In addition, other nodes can be connected to the assembly node in order to exchange information.
The second node is the bridge to the cloud which sends aggregated information to a state-of-the-art machine learning and AI analytics server. This server further analyzes the data gathered to offer actionable insights, predict intensive maintenance periods, and advise on how to optimize the performance of the machine. The analysis and conclusions drawn can be communicated to operators using a web dashboard or touch display integrated with the system. As a result, the end-users will have timely information to help them make effective decisions. With AI as well as machine learning integrated within the system, it generates alerts on possible failures before they even take place therefore enhancing optimal operations. The new technology has revolutionized the operations of carbonated soft drink filling machines by facilitating real-time monitoring, proactive fault identification and intelligent recommendations for improved operational dependability and productivity.
BEST METHOD OF WORKING
The FMDSTS Node, equipped with the Cortex A710 Processor Board, XBee Module, actuator, current sensor, temperature sensor, vibration sensor, LED , and the power supply is utilized to remotely monitor and effectively control operational parameters of carbonated beverage filling machines for industrial purposes, improving operational efficiency and reducing interruptions.
The FMDSRS Node, comprising a Cortex-A710 Processor Board, XBee Module, nRF Module, 7" capacitive touch display, buzzer and power supply, adds functions by allowing the staff to visualize data, receive notifications and interact with the private network, allowing them to address the problems immediately.
The FMDSRGS Node, combined with a Cortex-A710 processor board, nRF Module, GSM modem, LED indicator and rechargeable battery, assists with sending data to the customer made cloud server remotely for enabling predictive analysis and remote monitoring for better operations management.
The XBee Module operated on the FMDSTS and FMDSRS Nodes provide effective wireless communication of data across the private network so as to be able to communicate for real time machine monitoring and control.
Operators can use the 7" Capacitive Touch Display, hosted within the FMDSRS Node, operating housing and interface which allows them to obtain alerts and other information in addition to AI to make timely effective decisions in the field.
As a part of the FMDSRGS Node, the modem with a SIM card slot is specifically within an interfaced with the custom cloud server for data transmission allowing machine management control outside the site and enhancing operational versatility.
The nRF Module, featured in both FMDSRS and FMDSRGS Nodes, provides reliable communication features for the private multi-network and maintains data transfer and system integration throughout the system for vision turning reliability.
ADVANTAGES OF THE INVENTION
1. Using the temperature, vibration and current sensors, the system enables real time monitoring of machine functions and facilitates automatic deviation detection.
2. Maintenance, as such, can be performed in a timely manner with the integration of advanced AI analytics via the Cortex-A710 processor board reducing the chances of unexpected interruptions.
3. The XBee and nRF modules form a strong multi-private network for the efficient and effective transmission of data between nodes which allows non-stop operations and rapid response times.
4. Operators can easily access the vital information, alerts, and recommendations using the 7" capacitive touch display that also enhances the efficiency of operations and decision makin
5. The GSM modem makes it possible to send data to a personalized cloud server allowing remote access and control as well as providing insights to allowed users from anywhere in the world.
6. The system enables control of the filling process eliminating chances of over/under-filling during the process and wastage by automating flow control through the actuator and giving feedback through the sensors.
, C , Claims:1. A plugin add-on device for flow monitoring, control, and health prediction with recommendations in industrial carbonated beverage filling machines using nrf and xbee multi-private network gateway comprises FMDSTS Node, equipped with the Cortex A710 Processor Board, XBee Module, actuator, current sensor, temperature sensor, vibration sensor, LED , and the power supply is utilized to remotely monitor and effectively control operational parameters of carbonated beverage filling machines for industrial purposes, improving operational efficiency and reducing interruptions.
2. The device as claimed in claim 1, wherein the FMDSRS Node, comprising a Cortex-A710 Processor Board, XBee Module, nRF Module, 7" capacitive touch display, buzzer and power supply, adds functions by allowing the staff to visualize data, receive notifications and interact with the private network, allowing them to address the problems immediately.
3. The device as claimed in claim 1, wherein the FMDSRGS Node, combined with a Cortex-A710 processor board, nRF Module, GSM modem, LED indicator and rechargeable battery, assists with sending data to the customer made cloud server remotely for enabling predictive analysis and remote monitoring for better operations management.
4. The device as claimed in claim 1, wherein the XBee Module operated on the FMDSTS and FMDSRS Nodes provide effective wireless communication of data across the private network so as to be able to communicate for real time machine monitoring and control.
5. The device as claimed in claim 1, wherein operators can use the 7" Capacitive Touch Display, hosted within the FMDSRS Node, operating housing and interface which allows them to obtain alerts and other information in addition to AI to make timely effective decisions in the field.
6. The device as claimed in claim 1, wherein as a part of the FMDSRGS Node, the modem with a SIM card slot is specifically within an interfaced with the custom cloud server for data transmission allowing machine management control outside the site and enhancing operational versatility.
7. The device as claimed in claim 1, wherein the nRF Module, featured in both FMDSRS and FMDSRGS Nodes, provides reliable communication features for the private multi-network and maintains data transfer and system integration throughout the system for vision turning reliability.

Documents

NameDate
202411090831-COMPLETE SPECIFICATION [22-11-2024(online)].pdf22/11/2024
202411090831-DECLARATION OF INVENTORSHIP (FORM 5) [22-11-2024(online)].pdf22/11/2024
202411090831-DRAWINGS [22-11-2024(online)].pdf22/11/2024
202411090831-EDUCATIONAL INSTITUTION(S) [22-11-2024(online)]-1.pdf22/11/2024
202411090831-EDUCATIONAL INSTITUTION(S) [22-11-2024(online)].pdf22/11/2024
202411090831-EVIDENCE FOR REGISTRATION UNDER SSI [22-11-2024(online)]-1.pdf22/11/2024
202411090831-EVIDENCE FOR REGISTRATION UNDER SSI [22-11-2024(online)].pdf22/11/2024
202411090831-EVIDENCE FOR REGISTRATION UNDER SSI(FORM-28) [22-11-2024(online)].pdf22/11/2024
202411090831-FORM 1 [22-11-2024(online)].pdf22/11/2024
202411090831-FORM FOR SMALL ENTITY(FORM-28) [22-11-2024(online)].pdf22/11/2024
202411090831-FORM-9 [22-11-2024(online)]-1.pdf22/11/2024
202411090831-FORM-9 [22-11-2024(online)].pdf22/11/2024
202411090831-POWER OF AUTHORITY [22-11-2024(online)].pdf22/11/2024
202411090831-REQUEST FOR EARLY PUBLICATION(FORM-9) [22-11-2024(online)].pdf22/11/2024

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