PLUG-AND-PLAY EDGE DEVICE FOR PRECISE PLANT HEALTH MONITORING WITH AI RECOMMENDATIONS USING HYBRID NRF AND LORA INTRANET COMMUNICATION

Abstract

A plug-and-play edge device for precise plant health monitoring with ai recommendations using hybrid nrf and lora intranet communication comprises Raspberry Pi Board (101), nRF Module (102), ADS1117 Module (104), Soil Sensor (103), NPK Sensor (105), Temperature Sensor (107) and Power Supply (106), the PlantHealth Node (100) allows for the monitoring of vital soil and environment parameters with the level of accuracy and focus of time necessary for effective plant health monitoring and anticipatory crop management the Communication Node, with an integrated STM32 Board, nRF Module, LoRa RF Module, LED Indicator and Power Supply is able to provide a data relay in an intranet configuration offering seamless communication of plant health data across large farm areas.

Specification

Description:FIELD OF THE INVENTION
This invention relates to plug-and-play edge device for precise plant health monitoring with ai recommendations using hybrid nrf and lora intranet communication.
BACKGROUND OF THE INVENTION
This innovation is an edge device, which is considered a very easy-to-use system, as it allows the user to monitor the health of a plant and combine it with data collection, transmission, and analysis all on the cloud. It consists of several nodes that measure important climatic and soil characteristics, and features hybrid intranet interconnecting them for smooth data transfer. These data are sent to cloud systems in a several relay manner for centralized analysis and back to the users after carrying out the AI and machine learning based image processing and interpretation to form information and recommendations. Built system permits to the interact with the real time graphics and updates the authorized users about the functioning of the system, which helps users in the efficient management of the plant in a wide variety of agricultural environments.
The invention relates to the growing shortage of data received within an agricultural farm and the lack of automatic multispectral images of the plants. Efficient agriculture production is only possible with timely estimation of conditions of the soil and the plants growing on the territory of the farm. Farmers tend to evaluate conditions once a month at certain times with specific technologies. The rest of the time, it's hard for them to determine the exact conditions and factors. Given the continuous development of new technologies, efficiency should also increase. By continuously tracking and analyzing the health parameters of the plants, and providing recommendations based on artificial intelligence, farmers and farm managers can avoid inefficient management techniques. The results will improve the operational performance of the agriculture industry. The toolkit assists in promoting timely action, reducing resource overuse, and improving efficiency, which leads to the use of more sustainable farming practices.
CN109298697B: The invention relates to a method for evaluating the state of each component of a thermal power plant system based on a dynamic baseline model, which belongs to the technical field of thermal power generation and comprises the steps of establishing a system health state model by adopting a multivariate state estimation technology; establishing a dynamic baseline, monitoring and early warning the working state of each component of the system, and determining the abnormal working state of each component of the system; and carrying out deep analysis on the abnormal working state to determine abnormal measuring points, the time when the abnormal measuring points appear and abnormal components in the system. The method can effectively solve the problems of uncertainty and hysteresis existing in the setting of the fixed base line, the established dynamic base line model has definite physical significance and simple modeling, and the evaluation method can better grasp the overall operation state condition of the system, track the fault development process, timely find the system abnormity and the main measuring point information causing the abnormity, and evaluate the abnormal state of each part of the system, thereby assisting the operation and maintenance personnel of the thermal power plant to carry out state monitoring and early warning of the subsystem and having better practical value.
RESEARCH GAP: Hybrid nRF and LoRa-based communication for real-time, AI-driven plant health monitoring and recommendations, accessible via a custom cloud dashboard, is the uniqueness of this innovation.
CN104573850B: The invention discloses a kind of Power Plant Equipment state evaluating method, step includes:Power Plant Equipment layering is divided into unit, device cluster or system and equipment, and monitoring of equipment model is set up for equipment;Normal operation history data is filtered out from historical data base and obtains normal condition data set;The regression model based on generalized moment algorithm for estimating is set up, carrying out model training using normal condition data set obtains trained values;From real-time data base obtain monitoring of equipment supplemental characteristic and screened successively, state estimation, finally according to the hierarchical mode stratified calculation evaluation status value and state of monitoring of equipment model.The present invention can realize the state estimation of the equipment, system and unit of thermal power plant and the early warning of device object incipient fault change, and pass through the parameter state appraisal procedure based on different type of alarm, prompting causes the monitoring parameter of equipment, system and machine group alarm, helps thermal power plant's concern equipment early stage deterioration, analyzing failure cause and accumulation diagnostic experiences.
RESEARCH GAP: Hybrid nRF and LoRa-based communication for real-time, AI-driven plant health monitoring and recommendations, accessible via a custom cloud dashboard, is the uniqueness of this innovation.
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 is a plug-and-play edge device system that combines the unique features of different communication technologies with cloud-based analytics tools for the optimal real-time monitoring of diverse plant's health. This system comprises three core nodes, each with a specific function that assists in collecting and transmitting data on health attributes of plants, soil and the surrounding. Thereafter, the data is amalgamated and interpreted in a cloud environment through artificial intelligence and machinery learning so as to generate relevant recommendations regarding the proper management of plants in an optimal way. This new way of monitoring agriculture-related information targets farmers and agronomists since crucial information will always be available in the agricultural field in real time and hence timely interventions are done to improve productivity and efficient use of resources. This system responds directo to important issues in agriculture, for instance, sustainable management of resources and optimal monitoring systems of crops health. It assist farmers and agronomists to address issues before they affect productivity as reasonable amounts of timely data on crops health are provided. The fact that the system is plug-and-play also means that it can be operated by people with limited technological background and therefore promotes large scale use in different agricultural environments. In addition, users are further enabled through the simple nature of such complex data interpretation into precise recommendations which makes it simpler to ensure the plant health is maintained and the yields are optimized in an environmentally friendly manner, thanks to the AI-based recommendations accessed via the cloud dashboard.
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 is a plug-and-play edge device system that combines the unique features of different communication technologies with cloud-based analytics tools for the optimal real-time monitoring of diverse plant's health. This system comprises three core nodes, each with a specific function that assists in collecting and transmitting data on health attributes of plants, soil and the surrounding. Thereafter, the data is amalgamated and interpreted in a cloud environment through artificial intelligence and machinery learning so as to generate relevant recommendations regarding the proper management of plants in an optimal way. This new way of monitoring agriculture-related information targets farmers and agronomists since crucial information will always be available in the agricultural field in real time and hence timely interventions are done to improve productivity and efficient use of resources. This system responds directo to important issues in agriculture, for instance, sustainable management of resources and optimal monitoring systems of crops health. It assist farmers and agronomists to address issues before they affect productivity as reasonable amounts of timely data on crops health are provided. The fact that the system is plug-and-play also means that it can be operated by people with limited technological background and therefore promotes large scale use in different agricultural environments. In addition, users are further enabled through the simple nature of such complex data interpretation into precise recommendations which makes it simpler to ensure the plant health is maintained and the yields are optimized in an environmentally friendly manner, thanks to the AI-based recommendations accessed via the cloud dashboard.
Technical Aspects:
The system is implemented in a modular architecture which contains three basic nodes. The first one is related to data collection of plant health indicators, the second one is a communication node acting within a local network, and the last one is a cloud node for general data processing and communication over long distance. In such a setup, a short range as well as long range communication modes are present, thus making it a robust network to facilitate data transfer on even huge agricultural sites. There are three positions-each of which performs a unique function- one measures physical quantities employing high distributed sensors two assures transmission of data through the net and three coordinates storage and analysis conducted in the clouds. Artificial intelligence and machine learning algorithms are integrated into the cloud platform to process incoming data and provide recommendations that cater for authorized users through a web user interface that has been specially designed for them.
BEST METHOD OF WORKING
With the integration of a Raspberry Pi Board, nRF Module, ADS1117 Module, Soil Sensor, NPK Sensor, Temperature Sensor and Power Supply, the PlantHealth Node allows for the monitoring of vital soil and environment parameters with the level of accuracy and focus of time necessary for effective plant health monitoring and anticipatory crop management.
The Communication Node, with an integrated STM32 Board, nRF Module, LoRa RF Module, LED Indicator and Power Supply is able to provide a data relay in an intranet configuration offering seamless communication of plant health data across large farm areas.
Equipped with an ESP32 Board, LoRa RF Module, GSM Modem and Power Supply, the Cloud Node assists in cloud storage and retrieval of data allowing for live plant health monitoring, AI analytics and smart solutions for plant health management.
The nRF Module in both the PlantHealth and Communication Nodes were responsible for short range data transmission helping in faster and more efficient data transfers making possible near real time updates to the agricultural intranet for monitoring the status of the plants.
Utilizing a GSM Modem, any authorized personnel in the Plant may obtain plant health or AI-driven recommendations remotely through the web dashboard developed as part of the cloud node which expands agricultural management control to the web.
ADVANTAGES OF THE INVENTION
1. Raspberry Pi of the PlantHealth Node is equipped with an NPK Sensor and a Soil Sensor which, in conjunction, allow for the accurate and timely evaluation of a plant's nutrients and the environment which in turn improves the plant care's quality.
2. nRF Module and LoRa RF Module adapters for both PlantHealth and Communication Nodes make it possible to perform data transfer within long, middle and short distances which makes it possible to monitor the farms concentrating on both narrow and large agricultural areas.
3. Dynamic data acquisition and subsequent transmission to a tailor made cloud platform that interprets the agricultural metrics using artificial intelligence and machine learning algorithms is done by the ESP32 Board. This method avails reports and inquiries that help promote the correct use of plants which ensures better yields.
4. The authorized users are also able to access the prescribed plant health relevant insights and recommendations through a customized dashboard embedded in the cloud node connected to GSM modem. In this mode of operation, the users are able to supervise the farm activities from remote locations which assist in farm management.
5. The modular arrangement of the PlantHealth, Communication, and Cloud Nodes renders them to be modular and easy to expand and customize. For instance, more STM32 Boards in the Communication Node, or even more sensors in the PlantHealth Node, makes modification to different crops, field areas and farm needs possible.
, Claims:1. A plug-and-play edge device for precise plant health monitoring with ai recommendations using hybrid nrf and lora intranet communication comprises Raspberry Pi Board (101), nRF Module (102), ADS1117 Module (104), Soil Sensor (103), NPK Sensor (105), Temperature Sensor (107) and Power Supply (106), the PlantHealth Node (100) allows for the monitoring of vital soil and environment parameters with the level of accuracy and focus of time necessary for effective plant health monitoring and anticipatory crop management.
2. The device as claimed in claim 1, wherein the Communication Node, with an integrated STM32 Board, nRF Module, LoRa RF Module, LED Indicator and Power Supply is able to provide a data relay in an intranet configuration offering seamless communication of plant health data across large farm areas.
3. The device as claimed in claim 1, wherein equipped with an ESP32 Board, LoRa RF Module, GSM Modem and Power Supply, the Cloud Node assists in cloud storage and retrieval of data allowing for live plant health monitoring, AI analytics and smart solutions for plant health management.
4. The device as claimed in claim 1, wherein the nRF Module in both the PlantHealth and Communication Nodes were responsible for short range data transmission helping in faster and more efficient data transfers making possible near real time updates to the agricultural intranet for monitoring the status of the plants.
5. The device as claimed in claim 1, wherein utilizing a GSM Modem, any authorized personnel in the Plant may obtain plant health or AI-driven recommendations remotely through the web dashboard developed as part of the cloud node which expands agricultural management control to the web.

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