VISION-ENABLED EDGE DEVICE WITH ML AND AI RECOMMENDATIONS FOR BUSHFIRE AND DUST MONITORING IN SOLAR PLANTS USING NRF AND ZIGBEE TECHNOLOGY

Abstract

A vision-enabled edge device with ml and ai recommendations for bushfire and dust monitoring in solar plants using nrf and zigbee technology comprises VisionEdge Device is designed to allow for continuous data collection in a real time through the camera module to help detect the early stages of dust accumulation, consider the impact of wildfires in solar plant environments and the containment of bushfires, the device is composed of a Raspberry Pi board, camera module, ZigBee and PMS7003 dust particle sensor and power supply the Router Device is built with a Raspberry Pi board and its ZigBee and nRF modules serving as the primary components for facilitating power supply, the device under study incorporates long-range multihop enabling the transmission of data across long distances, receiving and transmitting networks with monitoring nodes while providing continuous data to the gateway over an expansive area of solar plants.

Specification

Description:FIELD OF THE INVENTION
This invention relates to vision-enabled edge device with ml and ai recommendations for bushfire and dust monitoring in solar plants using nrf and zigbee technology.
BACKGROUND OF THE INVENTION
An innovative approach has been developed which integrates bushfire and dust risk assessment IoT enabled edge device system with multi-environmental data for solar plants. The system under analysis comprises of several nodes, collaborating to complete the system while each is able to capture primary data in the form of images and concentration of dust and transmit such data through a reliable telemetry system for central data processing. This intelligent network uses machine learning and AI tools that are hosted in a dedicated cloud and scans the data being received for evident smoke or dust and anything out of the ordinary. Using advanced algorithms, this proactive approach can send such notifications such as, 'risk of fire' or enable the operators to act if the predicted 'dust levels' rise. A web-based application is used by authorized users to view in current time data and alerts as well as historical patterns so as to mitigate environmental hazards and ensure operational integrity and security of the facilities.
The bushfire and dust management problem in solar plants is acute, since uncontrolled flames or dust may cause a heavy loss in energy output, destruction of assets, and present high danger to safety. Standard monitoring processes are usually passive, based on periodic inspection or simple measuring devices which do not allow to and focus on most allowed warning features, particularly in large and isolated solar plants. This invention offers an integrated solution by routinely monitoring and interpreting images and other environmental aids to find existing and possible risks. Thanks to the insights from machine learning as well as the recommendations from an AI based algorithm, the system makes it possible to make swift actions, resulting to fewer operational halts, no exaggerated damages, and protection of the facilities and the environment around the facilities.
CN116094459A: The application provides a system of unmanned on duty photovoltaic power plant intelligence guarantee for including cleaning robot's photovoltaic power plant's inspection, including mount pad, arm, camera, workstation, temperature sensor, communication module and controller, the arm drives the camera with temperature sensor gathers the visible light image and the temperature data of photovoltaic panel front and back side respectively. The intelligent guarantee method for the unmanned photovoltaic power station further comprises the step of judging whether the photovoltaic panel is abnormal or not through judging temperature data of the photovoltaic panel and the connector lug or voltage of the photovoltaic panel. By adopting the intelligent guarantee method and system for the unmanned photovoltaic power station, personnel are not required to patrol, faults of the components are automatically detected, patrol and fault detection efficiency is improved, maintenance personnel are timely prompted to maintain, the fault components are prevented from influencing operation of other components, and the risk that the fault components influence safe operation of the photovoltaic power station is reduced.
RESEARCH GAP: AI-Enhanced Handheld Cloud Device for Connector Issue Detection in solar grid and panels is the novelty of the system.
CN103997298B: The invention discloses a monitoring data collecting terminal of a photovoltaic power station and a monitoring data system. The monitoring data collecting terminal comprises a data collecting module, a storage module, a data processing module, a remote communication module and a power module. The data collecting module is used for collecting working parameters of the photovoltaic power station every preset time, and the data processing module is used for conducting classified and graded storage on the data collected by the data collecting module, conducting filtering on the normal data and sending a message notice if abnormal data exist. The remote communication module sends the message notice to a remote control device. Thus, the requirement for monitoring the data of the power station remotely of a user is guaranteed, and the effect that the photovoltaic power station runs safely and stably on the unattended condition is realized; operation data of the photovoltaic power station and weather information of the photovoltaic power station are sent to the remote control device so that a user can comprehensively know and timely grasp the operation situations of all links of the photovoltaic power station, and safe operation of the photovoltaic power station can be guaranteed.
RESEARCH GAP: AI-Enhanced Handheld Cloud Device for Connector Issue Detection in solar grid and panels 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 way this innovation works is that there are several specialized nodes distributed over an area that are able to monitor and analyze relevant visuals and environmental conditions in real time to effectively manage bushfire and dust threats in solar plants. The process starts with the VisionEdge Device which is affixed at strategic locations within the solar plant to enable capturing visual data and monitoring the amount of dust present in the area using a particle's sensor. This device is actively deployed in a zone and waits for the triggering factors, like visible dust deposition or signs of fire's emergence. With a ZigBee wireless connecting module, devices adapted to this system efficiently communicate within the extended layout of a solar plant using low-power. The Router Device functions as a communication bridge. It is fitted with dual mode, ZigBee and nRF, so that data may be sent over long distances, or across rugged terrain. By deploying a multi-hop architecture, the Router Device proves that even with a wide separation, VisionEdge Device data is constantly passed to the Gateway Device. The routing ability is important for maintaining a level of corresponded information exchange and covering some possible areas in which transmission could be lost. The Router Device also integrates various streams of data from different VisionEdge Devices and helps in relaying important information to the gateway at the earliest possible 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.
The way this innovation works is that there are several specialized nodes distributed over an area that are able to monitor and analyze relevant visuals and environmental conditions in real time to effectively manage bushfire and dust threats in solar plants. The process starts with the VisionEdge Device which is affixed at strategic locations within the solar plant to enable capturing visual data and monitoring the amount of dust present in the area using a particle's sensor. This device is actively deployed in a zone and waits for the triggering factors, like visible dust deposition or signs of fire's emergence. With a ZigBee wireless connecting module, devices adapted to this system efficiently communicate within the extended layout of a solar plant using low-power. The Router Device functions as a communication bridge. It is fitted with dual mode, ZigBee and nRF, so that data may be sent over long distances, or across rugged terrain. By deploying a multi-hop architecture, the Router Device proves that even with a wide separation, VisionEdge Device data is constantly passed to the Gateway Device. The routing ability is important for maintaining a level of corresponded information exchange and covering some possible areas in which transmission could be lost. The Router Device also integrates various streams of data from different VisionEdge Devices and helps in relaying important information to the gateway at the earliest possible time.

When the data has been relayed to the Gateway Device, it will send it to a special cloud server using a GSM or Wifi network - whichever is available. This capability guarantees that data is always sent to the cloud for future analysis even in remote places where connections are weak. From the cloud server, machine learning combines the incoming data and performs analyses to discover any trends, irregularities, or threatening events. The AI-based recommendation engine identifies patterns that may suggest an impending bushfire or excessive dust build-up and issues warnings and suggestions for maintenance based on the system's recommendations. These insights help operators take action before things get out of hand, enhancing plant security as well as efficiency. The processed data is made available for viewing by the appropriate people in a secure internet-based dashboard that is able to show relevant information in natural and time-sequenced graphics that are historical as well as current. This allows the operators to control dust emissions and the risk of fire in the solar system, as well as monitor its environmental factors from a single or remote site. Such an advancement, which integrates visual and sensor data with predictive machine learning, equips solar plant owners with timely and efficient solutions to avoid risks of disruption of energy production, destruction of infrastructures, and bushfires in sensitive areas.
BEST METHOD OF WORKING
The VisionEdge Device is designed to allow for continuous data collection in a real time through the camera module to help detect the early stages of dust accumulation, consider the impact of wildfires in solar plant environments and the containment of bushfires. The device is composed of a Raspberry Pi board, camera module, ZigBee and PMS7003 dust particle sensor and power supply.
The Router Device is built with a Raspberry Pi board and its ZigBee and nRF modules serving as the primary components for facilitating powe supply. The device under study incorporates long-range multihop enabling the transmission of data across long distances, receiving and transmitting networks with monitoring nodes while providing continuous data to the gateway over an expansive area of solar plants.
The Gateway Device has a unique design which houses the Jetson Nano board the nrf module, GSM Modem, indicator LED and a power supply. This device ensures machine learning analytics and AI driven recommendations to manage bushfire and dust preemptively through data processing and connectivity to the cloud.
The Gateway Device is equipped with a GSM Modem that allows data to be sent to an online server. This device can operate without wi fi for a remote area allowing other environmental parameters to be sent live. This advanced feature enhances remote monitoring and accessibility.
With the PMS7003 Dust Particle Sensor integrated within the VisionEdge Device, on-site monitoring of dust particulate is accurately performed such that dust build up that is likely to hinder the efficacy of the solar panels and that of the plant is efficiently detected in good time.
ADVANTAGES OF THE INVENTION
1. The VisionEdge Device consists of a board, camera, and wrist munition which aims to detect and identify early signs whether this will be a problem and if a fire can occur due to excessive dust buildup on photovoltaic panels in solar plants.
2.The Gateway Device is a Router Device with Raspberry Pi board, ZigBee module and nRF module that enables large area multihop data transmission to the gateway throughout essential communication channels filled with landscapes.
3. The Gateway Device which is made up of Jetson Nano board, nRF module and GSM Modem allows users to send data to the cloud and afterwards use AI systems to generate control measures presenting users predictive maintenance and risk management means.
4. The Gateway Device with GSM Modem allows for slow but secure sending of data to the cloud, bridging the gap, and allowing for interaction and remote monitoring of team members in areas that presumably have little to no Wifi.
5. Centralized Data Access and Remote Monitoring: Using the web-hosted web dashboard, which consolidates real-time and historical information for simple visualization, authorized users of the system can view the system's data and insights and execute prompt actions no matter where they are located.
, Claims:1. A vision-enabled edge device with ml and ai recommendations for bushfire and dust monitoring in solar plants using nrf and zigbee technology comprises VisionEdge Device is designed to allow for continuous data collection in a real time through the camera module to help detect the early stages of dust accumulation, consider the impact of wildfires in solar plant environments and the containment of bushfires, the device is composed of a Raspberry Pi board, camera module, ZigBee and PMS7003 dust particle sensor and power supply.
2. The device as claimed in claim 1, wherein the Router Device is built with a Raspberry Pi board and its ZigBee and nRF modules serving as the primary components for facilitating power supply, the device under study incorporates long-range multihop enabling the transmission of data across long distances, receiving and transmitting networks with monitoring nodes while providing continuous data to the gateway over an expansive area of solar plants.
3. The device as claimed in claim 1, wherein the Gateway Device has a unique design which houses the Jetson Nano board the nrf module, GSM Modem, indicator LED and a power supply, this device ensures machine learning analytics and AI driven recommendations to manage bushfire and dust preemptively through data processing and connectivity to the cloud.
4. The device as claimed in claim 1, wherein the Gateway Device is equipped with a GSM Modem that allows data to be sent to an online server, this device can operate without wi fi for a remote area allowing other environmental parameters to be sent live, this advanced feature enhances remote monitoring and accessibility.
5. The device as claimed in claim 1, wherein with the PMS7003 Dust Particle Sensor integrated within the VisionEdge Device, on-site monitoring of dust particulate is accurately performed such that dust build up that is likely to hinder the efficacy of the solar panels and that of the plant is efficiently detected in good time.

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