VISION-ENABLED PREDICTIVE DEVICE WITH ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING INNOVATION FOR INDUSTRIAL PACKAGING SHREDDERS USING XBEE AND LORA RF GATEWAY TECHNOLOGY

Abstract

A vision-enabled predictive device with artificial intelligence and machine learning innovation for industrial packaging shredders using xbee and lora rf gateway technology comprises VPDTxS Node, in which a Cortex-A710 Processor Board, a Camera Module, an Xbee Module, an Inertial Measurement Unit, a Current Sensor, a Temperature Sensor, a Buzzer and a Power Supply compatible with all preceding components are assembled, talks of real-time camera monitoring and sensor-based information collection with guaranteed performance parameter tracing and quick forwarding of the information to the next network node for processing the VPDTrS Node also equipped with a Cortex-A710 Processor Board features XBee and LoRa RF Modules as well as an HMI Display and Indicator LED with power supply enabling long range communication, data observation on the spot and influence on the work performed at one go with real life situations at the fingertips which enhances the operators decision making process.

Specification

Description:FIELD OF THE INVENTION
This invention relates to vision-enabled predictive device with artificial intelligence and machine learning innovation for industrial packaging shredders using xbee and lora rf gateway technology.
BACKGROUND OF THE INVENTION
This new predictively-oriented camera technology improves performance and supervision of industrial packaging shredders, introducing a new predictive device into the packaging processes. It incorporates modern vision directed techniques for counting and tracking in real time and combines the use of several sensors to gather important operational parameters such as motion, current, and temperature. This information is transferred via a wireless communication network to a remote server, and machine learning algorithms installed on this server process this information and return recommendations, alerts about the need for preventive maintenance, and plans. The system is equipped with a more user-friendly interface, so it is easy for the operators and authorized persons, who are based, for example, on the cloud, to process the secured information via the Meta-DS or locally, in the display device, peripherals, and boards, enabling timely monitoring, recognition, and decision. Such an integrated system improves the way cutting operations should be carried out and also alters the downtimes, thereby improving management in the processes of industrial shredding.
Quite standard practice nowadays is to use industrial packaging shredders to efficiently reduce packaging and other materials into smaller sizes for easier storage and transportation. However, certain operational constraints appear to limit not only the reliability of shredders but also their effectiveness, and those limitations are the lack of efficient operational monitoring, help in real-time situation analysis, and decision-making systems for plenty of different unforeseen events. Unfortunately, this type of machinery is often not actively supervised due to the realities of traditional systems that perform monitoring almost entirely manually, resulting in slower fault identification, increased maintenance costs and downtime of production. This invention addresses these issues by defying traditional spaces and offering an application that predicts faults by running Vision-Based and Sensor-Based analytics. The system makes use of the Internet of Things and machine learning and AI models to enhance equipment functioning by offering alerts, insights, and instructions, therefore risk of equipment failure and degradation of operational efficiency is effectively mitigated allowing for better management of companies' resources and industrial activities.
KR102264246B1: The present invention relates to a shredder for individually packaging and discharging shredded plastics, and a recycling system for recycling shreds delivered by collecting and crushing waste plastics. The present invention crushes only the shreds related to transparent plastics.
RESEARCH GAP: Vision-enabled predictive monitoring and AI-driven optimization of industrial packaging shredders using XBee and LoRa RF communication is the novelty of the system.
ES2607797T3: Method for the manufacture of paper, tissue, cardboard or the like, using recycled fiber material as raw material, a method that comprises the following steps: - manufacture recycled paper pulp, cardboard or the like in a shredder and obtain a pulp stream comprising (i) an aqueous phase and (ii) at least recycled fibers and low molecular weight starch, which are dispersed in the aqueous phase; characterized in that - a coagulating agent is added to the pasta stream or to an aqueous process stream comprising low molecular weight starch; - the coagulating agent is allowed to interact with the low molecular weight starch and optionally form aggregates; and - at least one flocculating agent is added, after addition of the coagulating agent, to any stream, comprising interacting coagulating agent, and a starch-treated stream comprising agglomerate (s) is formed; - at least part of said aggregates and / or said agglomerates is retained to the fibers or to a fabric, which is formed.
RESEARCH GAP: Vision-enabled predictive monitoring and AI-driven optimization of industrial packaging shredders using XBee and LoRa RF communication 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.
This innovation functions as a complete predictive reconnaissance and optimisation panacea for the industrial packaging shredding machine that incorporates data collection, transmission, and processes in the cloud. The system consists of three separate nodes, each performing clearly defined functions regarding data collection, data processing and data transmissions. To begin with, the first node out of all three, visual data relating to the current operational activities such as package and stead count as well as monitoring the shredder is gathered by the camera system. At that stage, also, some sensors measure the motion, current consumption and temperature. All this information is collected and sent wirelessly through efficient communication channels to the next level of processing. On the next node within these three, further processing and subsequent transmission of the data via long range modem takes place. The aim of this node is to act as a link connecting the center and the two other nodes providing appropriate means towards achieving this task. The HMI features the operational parameters that expose surprises to the operators in the area who are responsible for the shredder's workload and are there to do whatever is necessary at the time.
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.
This innovation functions as a complete predictive reconnaissance and optimisation panacea for the industrial packaging shredding machine that incorporates data collection, transmission, and processes in the cloud. The system consists of three separate nodes, each performing clearly defined functions regarding data collection, data processing and data transmissions. To begin with, the first node out of all three, visual data relating to the current operational activities such as package and stead count as well as monitoring the shredder is gathered by the camera system. At that stage, also, some sensors measure the motion, current consumption and temperature. All this information is collected and sent wirelessly through efficient communication channels to the next level of processing. On the next node within these three, further processing and subsequent transmission of the data via long range modem takes place. The aim of this node is to act as a link connecting the center and the two other nodes providing appropriate means towards achieving this task. The HMI features the operational parameters that expose surprises to the operators in the area who are responsible for the shredder's workload and are there to do whatever is necessary at the time.
Through the final node, the system can be connected to a cloud server where machine learning and artificial intelligence perform forensic data analytics. The cloud server assimilates the data and spots trends, anticipates probable failures, and provides recommendations for action based on the analysis. This filtered data is available for actuators and authorized users via the web to interface with the controlling and monitoring of chain shredder business processes. The different components of the dashboard are able to demonstrate historical data, schedules of maintenance work that need to be carried out in the future, and operational parameters, thereby making it possible to make informed decisions in order to reduce idle time and increase efficiency. There are significant operation improvements that result from the interplay of visual technology alongside the IoT communication and the AI powered analytics.
BEST METHOD OF WORKING
The VPDTxS Node, in which a Cortex-A710 Processor Board, a Camera Module, an Xbee Module, an Inertial Measurement Unit, a Current Sensor, a Temperature Sensor, a Buzzer and a Power Supply compatible with all preceding components are assembled, talks of real-time camera monitoring and sensor-based information collection with guaranteed performance parameter tracing and quick forwarding of the information to the next network node for processing.
The VPDTrS Node also equipped with a Cortex-A710 Processor Board features XBee and LoRa RF Modules as well as an HMI Display and Indicator LED with power supply enabling long range communication, data observation on the spot and influence on the work performed at one go with real life situations at the fingertips which enhances the operators decision making process.
The VPDRsGS Node contains a Raspberry Pi Board, a LoRa RF Module, a GSM modem with an LED power indicator and a rechargeable battery. This unit presents the possibility of performing powerful cloud communication and transmitting of data to the designed server so that data with predictive analytics and system performance can be accessed remotely by authorized users.
The Camera Module, incorporated in the VPDTxS Node, provides the capability of advanced vision-based systems to perform functions such as package counting, or shredder monitoring, which improves organizational efficiency and reduces the need of manual labor in the process.
The XBee and LoRa RF Modules, installed on the VPDTxS as well as the VPDTrS Nodes, facilitate effective wireless communication, providing a seamless transfer of information between nodes as well as the cloud server, irrespective of industrial interference effects.
The HMI Display that is hosted within the VPDTrS Node assists in updating the site personnel on important issues such as the status of shredders enabling operators to determine Shredder effectiveness and variation quickly.
ADVANTAGES OF THE INVENTION
1. The camera module provides the required real time monitoring of the visual based operation and counting of the packages ensuring no manual supervison is required.
2. The accelerometer, current sensor, and temperature sensor are needed in order to routinely and remotely monitor critical elements to help detect and prevent unexpected outages.
3. Null modem cables are not needed for both modules since the XBee and LoRa RF modules provide feasible communication systems with data transmission over some distances that are Zyquite useful over ordinary radio waves scram.
4. XBee module interfaced to raspberry board internet server via gsm modem assists operators check machine performance from remote locations through the web.
5. The HMI display and indicator LEDs are useful for displaying feedback regarding the operational status of the equipment which on-site personnel can take note and take appropriate actions.
6. A custom cloud server IoT platform helps in improving decisions and operational planning by providing relevant insights and predictive recommendations made possible by AI and ML based analytics.
, Claims:1. A vision-enabled predictive device with artificial intelligence and machine learning innovation for industrial packaging shredders using xbee and lora rf gateway technology comprises VPDTxS Node, in which a Cortex-A710 Processor Board, a Camera Module, an Xbee Module, an Inertial Measurement Unit, a Current Sensor, a Temperature Sensor, a Buzzer and a Power Supply compatible with all preceding components are assembled, talks of real-time camera monitoring and sensor-based information collection with guaranteed performance parameter tracing and quick forwarding of the information to the next network node for processing.
2. The device as claimed in claim 1, wherein the VPDTrS Node also equipped with a Cortex-A710 Processor Board features XBee and LoRa RF Modules as well as an HMI Display and Indicator LED with power supply enabling long range communication, data observation on the spot and influence on the work performed at one go with real life situations at the fingertips which enhances the operators decision making process.
3. The device as claimed in claim 1, wherein the VPDRsGS Node contains a Raspberry Pi Board, a LoRa RF Module, a GSM modem with an LED power indicator and a rechargeable battery, this unit presents the possibility of performing powerful cloud communication and transmitting of data to the designed server so that data with predictive analytics and system performance can be accessed remotely by authorized users.
4. The device as claimed in claim 1, wherein the Camera Module, incorporated in the VPDTxS Node, provides the capability of advanced vision-based systems to perform functions such as package counting, or shredder monitoring, which improves organizational efficiency and reduces the need of manual labor in the process.
5. The device as claimed in claim 1, wherein the XBee and LoRa RF Modules, installed on the VPDTxS as well as the VPDTrS Nodes, facilitate effective wireless communication, providing a seamless transfer of information between nodes as well as the cloud server, irrespective of industrial interference effects.
6. The device as claimed in claim 1, wherein the HMI Display that is hosted within the VPDTrS Node assists in updating the site personnel on important issues such as the status of shredders enabling operators to determine Shredder effectiveness and variation quickly.

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