IOT-BASED SUSTAINABLE DEVICE FOR MONITORING AND OPTIMIZING HYDROPONIC PLANT GROWTH

Abstract

An IoT-based sustainable device for monitoring and optimizing hydroponic plant growth is described herein. The device incorporates various sensors, including pH, electrical conductivity, temperature, humidity, and light sensors, to track and regulate key environmental factors. A microcontroller processes this data and triggers actuators to deliver nutrients, adjust lighting, and control air circulation. With cloud connectivity for remote monitoring, machine learning for data analysis, and resource optimization algorithms, the system minimizes water and energy consumption. The device also integrates renewable energy sources and provides real-time feedback through an intuitive user interface with data visualization tools.

Specification

Description:Field of the Invention
The present invention relates to the field of agricultural technology, specifically to a sustainable, Internet of Things (IoT)-based device for monitoring and optimizing hydroponic plant growth. The invention is designed to track key environmental parameters such as nutrient concentration, pH levels, temperature, humidity, and light intensity. Through cloud connectivity and machine learning, the device allows remote monitoring and control of hydroponic systems, aiming to optimize resource usage, enhance plant growth, and promote environmentally sustainable agricultural practices.
Background of the Invention
This section is intended to provide information relating to the field and background of the invention and thus any approach/functionality described below should not be assumed to be qualified as prior art merely by its inclusion in this section.
Hydroponics, a method of growing plants without soil, has gained significant attention in recent years due to its potential to optimize agricultural production, especially in urban areas, regions with poor soil quality, or environments with limited access to water. Traditional hydroponic systems rely on a nutrient-rich water solution that delivers essential nutrients directly to the plants' roots, bypassing the need for soil. While hydroponics offers significant advantages, such as faster plant growth and reduced water usage compared to traditional farming, it is not without its challenges.
In conventional hydroponic systems, continuous monitoring and precise control of environmental factors such as pH levels, nutrient concentration, temperature, humidity, and light intensity are critical to the success of the crops. Maintaining these factors manually requires constant attention and expertise, making the system prone to human error. For instance, improper nutrient dosing or unregulated environmental conditions can lead to stunted growth, poor crop yield, or even plant death. Many conventional hydroponic systems lack real-time feedback mechanisms, making it difficult for growers to identify problems until the damage is irreversible.
Various technological solutions have been proposed to address these challenges. Basic automation tools, such as timers for irrigation or lights, have been implemented in many hydroponic setups to reduce the burden on growers. However, these systems are often limited in scope and fail to provide the comprehensive data necessary for optimal crop management. For example, they may not account for fluctuations in pH levels, nutrient concentrations, or temperature, all of which can impact plant health. Moreover, while some systems offer monitoring capabilities, they lack the ability to analyze data and make real-time adjustments, limiting their overall effectiveness.
Recent advances in IoT technology have opened new possibilities for enhancing hydroponic systems. IoT-enabled devices offer real-time monitoring and control capabilities by integrating sensors, microcontrollers, and cloud-based data storage. These systems provide remote access to key environmental parameters, allowing users to monitor their crops from anywhere and at any time. However, many existing IoT-based solutions suffer from several limitations.
First, the existing IoT systems for hydroponics often have poor scalability and lack modularity, making it difficult for users to customize or expand their systems according to the specific needs of different crops or growing conditions. Most of these systems are designed for small-scale, home-based hydroponic setups and are not robust enough to support large-scale commercial operations.
Second, many IoT-based hydroponic systems lack advanced data analytics capabilities. While these systems collect vast amounts of data from sensors, they do not utilize this data effectively. Machine learning and data analysis tools are often not integrated, which means the systems cannot identify trends, predict outcomes, or make automated decisions based on historical data. This absence of advanced analytics hampers the system's ability to optimize growing conditions and respond proactively to potential problems.
Third, existing solutions often fail to address sustainability concerns. While hydroponic systems are generally more resource-efficient than traditional farming, there is room for improvement in optimizing water and energy usage. Most IoT-based hydroponic systems do not incorporate renewable energy sources or implement algorithms to minimize resource consumption, thus limiting their sustainability.
Fourth, the user interfaces of many current hydroponic systems are often not intuitive, making it difficult for non-experts to navigate or fully utilize the system's features. A lack of visualization tools, such as charts and graphs that display real-time data and trends, further complicates the user experience. Without proper visualization, growers may struggle to interpret the data collected by the system, limiting their ability to make informed decisions.
Moreover, while hydroponic systems offer significant environmental benefits, such as reduced water usage and space efficiency, there is still a need for improved environmental monitoring. Parameters such as energy consumption, water usage, and nutrient waste are not adequately tracked by current systems, preventing growers from assessing the overall environmental impact of their operations. This limits the ability of hydroponic systems to contribute effectively to sustainability goals.
Given these limitations, there is a clear need for an advanced IoT-based hydroponic system that can address the shortcomings of existing solutions. Such a system should offer real-time monitoring of key environmental factors, provide robust data analysis and machine learning capabilities, and incorporate sustainability features to optimize resource usage. Furthermore, it should be scalable and modular, allowing it to be adapted to different scales of operation, from small urban farms to large commercial hydroponic facilities.
This invention aims to overcome the limitations of the prior art by providing an IoT-based sustainable device for monitoring and optimizing hydroponic plant growth patterns. By integrating sensors, microcontrollers, cloud storage, machine learning, and sustainability features, this invention enables real-time data collection, analysis, and automated adjustments to ensure optimal growing conditions. Additionally, the system focuses on resource optimization, environmental impact monitoring, and user-friendly interface design, addressing key concerns in existing hydroponic technologies.
This invention is not only designed to enhance plant growth efficiency but also contributes to more sustainable agricultural practices, making it highly relevant in the context of increasing global food demands and environmental concerns. By combining IoT technology with advanced data analysis tools and sustainability measures, this invention provides a comprehensive solution that addresses the challenges faced by current hydroponic systems while offering new opportunities for agricultural innovation.
Object of the Invention
This section is intended to introduce certain objects of the disclosed composition in a simplified form, and is not intended to identify the key advantages or features of the present disclosure.
The main object of the present invention is to provide an IoT-based sustainable device for monitoring and optimizing hydroponic plant growth patterns, which overcomes the limitations of existing systems and enhances agricultural productivity and efficiency.
Another object of the invention is to enable continuous monitoring of critical environmental parameters such as pH, nutrient levels, temperature, humidity, and light intensity through an array of sensors to ensure optimal plant growth
The further object of the present invention is to provide automated control of key systems, such as nutrient delivery, lighting, and ventilation, using actuators to adjust conditions based on real-time data, reducing human error and labor.
It is still further object of the present invention to leverage machine learning algorithms and historical data analysis to predict growth patterns, identify trends, and optimize growing conditions, thereby improving crop yield and quality.
It is still yet further object of the present invention to offer connectivity through Wi-Fi or LoRaWAN, allowing users to remotely monitor, adjust, and control the hydroponic system via a user-friendly mobile or web interface.
It is still yet further object of the present invention to incorporate renewable energy sources like solar panels, and to implement algorithms that optimize resource usage, such as water and nutrients, minimizing environmental impact.
It is still yet further object of the present invention is to design a system that is modular and scalable, allowing for flexibility in deployment, whether for small urban farms or large commercial hydroponic operations.
It is still yet further object of the present invention is to develop an intuitive dashboard that includes visualization tools like graphs and charts for real-time data representation and analysis, making the system accessible to users with varying levels of expertise.
These and other objects, features and advantages of the present invention will become more apparent from the following description when taken in connection with the accompanying drawing which shows, for the purpose of illustration only, one embodiment in accordance with the present invention.
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 not intended to identify key or essential inventive concepts of the invention, nor is it intended for determining the scope of the invention.
The present invention relates to an IoT-based sustainable device designed to monitor and optimize hydroponic plant growth. This system integrates various sensors, including pH, electrical conductivity (EC), temperature, humidity, and light sensors, to gather real-time environmental data crucial for plant health. A microcontroller, such as an Arduino or Raspberry Pi, processes the sensor data and communicates with actuators responsible for delivering nutrients, regulating light intensity, and managing air circulation.
The device features cloud connectivity via Wi-Fi or LoRaWAN, enabling remote monitoring and control through a web or mobile app. The data collected is stored on a cloud platform, where historical trends can be analyzed using machine learning algorithms to optimize growing conditions. This predictive capability improves plant growth efficiency and resource management by adjusting system settings automatically when predefined thresholds are met.
In addition to temperature regulation, the machine incorporates a dynamic aeration system that enhances oxygen flow to the compost pile, further accelerating the breakdown of organic materials. The aeration system adjusts airflow based on real-time feedback from the sensors, contributing to a balanced environment that minimizes odors and reduces the risk of pathogen growth.
Sustainability is a core feature, with renewable energy sources, such as solar panels, powering the device. Additionally, algorithms are designed to minimize the use of water and nutrients, thereby reducing the environmental footprint.
The user interface offers a real-time dashboard for viewing sensor data and system analytics, including visual tools like graphs to illustrate growth patterns over time. This system is modular and scalable, making it suitable for various hydroponic setups, from small urban farms to large-scale commercial operations.
By integrating IoT technology with sustainable agricultural practices, this invention provides an efficient and eco-friendly solution for optimizing hydroponic plant growth.
To the accomplishment of the foregoing and related ends, certain illustrative aspects of the disclosure are described herein in connection with the following description. These aspects are indicative, however, of but a few of the various ways in which the principles of the disclosure can be employed and the subject disclosure is intended to include all such aspects and their equivalents.
Detailed Description
For the purpose of promoting an understanding of the principles of the invention, reference will be described in specific language. It will be understood by those skilled in the art that the foregoing general description and the following detailed description are explanatory of the invention and are not intended to be restrictive thereof.
Reference throughout this specification to "an aspect", "another aspect" or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention.
As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless expressly stated otherwise. It will be further understood that the terms "includes", "comprises", and/or "comprising" when used in this specification, 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. Furthermore, the term "and/or" includes any and all combinations and arrangements of one or more of the associated listed items.
As used herein, the following terms and variations thereof have the meanings given below, unless a different meaning is clearly intended by the context in which such term is used. Definitions, where the definition of terms departs from the commonly used meaning of the term, applicant intends to utilize the definitions provided below, unless specifically indicated.
For purposes of the present disclosure, it should be noted that to provide a more concise description, some of the quantitative expressions given herein are not qualified with the term "about." It is understood that whether the term "about" is used explicitly or not, every quantity given herein is meant to refer to the actual given value, and it is also meant to refer to the approximation to such given value that would reasonably be inferred based on the ordinary skill in the art, including approximations due to the experimental and/or measurement conditions for such given value.
The present invention relates to optimize plant growth in hydroponic systems by utilizing IoT technology integrated with various sensors, actuators, a microcontroller, and cloud connectivity. The system automatically monitors and adjusts environmental factors that are critical to plant health, such as nutrient levels, pH, light intensity, temperature, and humidity. Below is a detailed explanation of how each component is arranged, connected, and functions as part of the system.
System Components and Configuration
1. Sensors: Several types of sensors are deployed within the hydroponic system to monitor the growing environment:
- pH Sensor: Measures the acidity or alkalinity of the nutrient solution to ensure optimal conditions for nutrient absorption by plants.
- EC (Electrical Conductivity) Sensor: Monitors the concentration of dissolved nutrients in the solution, which is critical for plant growth.
- Temperature and Humidity Sensors: Measure the ambient temperature and humidity levels in the growing environment.
- Light Sensor: Tracks the intensity and duration of light exposure to ensure plants receive the appropriate amount of light for photosynthesis.
These sensors are strategically placed in the nutrient reservoirs, growth chambers, or near the plants to gather real-time data, which is continuously fed into the system.
2. Microcontroller: The microcontroller, such as an Arduino or Raspberry Pi, serves as the processing unit of the system. It collects data from the sensors and controls the actuators based on preset conditions or real-time feedback. The microcontroller also handles communication with the cloud platform for remote monitoring and data analysis.
- Connections: The sensors are wired to the microcontroller via input pins. The actuators, like pumps and lights, are connected via output pins. Communication modules, such as a Wi-Fi or LoRaWAN chip, are attached for cloud connectivity.
- Functionality: The microcontroller processes data and performs real-time adjustments by triggering actuators. For instance, if the EC sensor detects a drop in nutrient concentration, the microcontroller activates a pump to deliver additional nutrients.
3. Actuators: The actuators perform essential functions in the hydroponic system, including:
- Nutrient Pumps: Deliver the required amount of nutrients to the plants based on feedback from the EC sensor.
- Air Circulation Fans: Maintain optimal airflow and temperature within the growth chamber by circulating air when necessary.
- Lighting System: LED grow lights are automatically adjusted based on feedback from the light sensor, ensuring that plants receive the optimal amount of light for their growth stage.
The actuators are connected to the microcontroller, which controls them based on sensor inputs.
4. Connectivity and Cloud Integration: The system is designed to be connected to the cloud via Wi-Fi or LoRaWAN communication protocols. The data collected from the sensors is sent to a cloud platform like AWS, Google Cloud, or Microsoft Azure for remote storage and processing.
- Data Storage and Analysis: The cloud platform stores historical sensor data in a database, allowing users to track trends and patterns over time. Machine learning algorithms analyze the data to optimize growing conditions, providing real-time feedback and recommendations to improve plant growth efficiency.
- Remote Monitoring: Users can access real-time data and system status through a mobile or web application. Alerts can be triggered if any environmental parameters fall outside the predefined thresholds, allowing for manual adjustments or automatic system corrections.
5. Data Analysis and Automation: The system incorporates machine learning algorithms to predict and optimize plant growth. The collected data is used to adjust various environmental parameters, such as:
- Nutrient Concentration: If the nutrient levels drop below the required threshold, the system will automatically deliver more nutrients.
- Light Intensity: Based on the light sensor data, the system adjusts the LED lights to provide optimal intensity and duration for each growth stage of the plant.
- Water and Resource Optimization: The algorithms are designed to minimize water and nutrient waste, ensuring sustainable use of resources. The system tracks water consumption and nutrient usage over time to reduce environmental impact.
6. User Interface: The user interface is an essential part of the system, allowing for easy interaction with the system components. It includes:
- Dashboard: The real-time dashboard displays current environmental conditions, including pH, temperature, light intensity, and nutrient levels. It allows users to monitor the system's performance and make manual adjustments as necessary.
- Alerts and Notifications: The system sends notifications when any parameter falls outside the optimal range, allowing users to take immediate corrective action.
- Visualization Tools: Graphs and charts represent historical data, showing growth patterns, resource consumption, and system performance over time.
7. Sustainability Features: The system is designed with sustainability in mind, incorporating features such as:
- Renewable Energy Sources: The system can be powered by solar panels, reducing reliance on non-renewable energy sources.
- Water and Nutrient Optimization: The algorithms optimize water and nutrient usage, ensuring minimal waste and environmental impact.
According to an embodiment of the present invention, the examples of the device are given below:
Example 1: Small-Scale Urban Hydroponic Farm
A user sets up a small hydroponic farm in an urban environment. The system is configured with pH, EC, temperature, and light sensors, all connected to a Raspberry Pi microcontroller. The data is transmitted to a cloud platform where it is analyzed, and the user can monitor the farm remotely through a mobile app. The system automatically adjusts light intensity and nutrient concentration based on real-time sensor feedback. Over time, the machine learning algorithms optimize the growing conditions, resulting in higher yields with less resource use.
Example 2: Commercial Hydroponic Greenhouse
In a large-scale commercial setup, the system includes multiple IoT devices connected to a central server. Each device monitors different sections of the greenhouse, adjusting temperature, humidity, and light exposure according to the specific needs of each plant type. The system minimizes water consumption and optimizes energy use by powering the system with solar panels. The data collected over months is used to fine-tune the growing conditions for maximum yield and resource efficiency. , Claims:We Claim:
1. An IoT-based sustainable device for monitoring and optimizing hydroponic plant growth consisting of:
a plurality of sensor configured to monitor environmental factors within the hydroponic system, and further consisting of:
a pH sensor for measuring the acidity of the nutrient solution;
an electrical conductivity (EC) sensor for determining nutrient concentration;
a temperature and humidity sensor for tracking atmospheric conditions;
a light sensor for monitoring light intensity
a microcontroller configured to process data received from the plurality of sensors, wherein the microcontroller is selected from a group consisting of Arduino or Raspberry Pi;
an actuator configured to
deliver nutrients via pumps,
control light systems for plant growth,
regulate air circulation via fans;
a connectivity means selected from Wi-Fi or LoRaWAN, to facilitate communication between the device and a cloud platform for remote monitoring and control;
a data storage and management system configured to
store sensor data on a cloud platform selected from AWS, Google Cloud, or Azure;
maintain a database for historical data analysis;
a data analysis module configured to
implement machine learning algorithms to analyze plant growth patterns;
optimize environmental conditions by setting thresholds for each parameter;
trigger alerts or automatic system adjustments based on the threshold parameters;
an user interface consisting of:
a dashboard for real-time monitoring of data and analytics;
a controls allowing users to manually adjust environmental parameters
a visualization tool including graphs and charts displaying growth patterns and environmental trends over time;
2. The IoT-based sustainable device for monitoring and optimizing hydroponic plant growth as claimed in claim 1, wherein the a sustainability system that includes
resource optimization algorithms configured to minimize water and nutrient usage;
a power system utilizing renewable energy sources, including solar panels, to power the device;
a monitoring system configured to track energy consumption and water usage, thereby minimizing environmental impact.
3. The IoT-based sustainable device for monitoring and optimizing hydroponic plant growth as claimed in claim 1, wherein the machine learning algorithms are configured to
analyze correlations between environmental conditions and plant growth efficiency;
predict optimal conditions for different stages of plant growth;
adjust nutrient delivery, lighting, and air circulation automatically based on data-driven insights;
4. The IoT-based sustainable device for monitoring and optimizing hydroponic plant growth as claimed in claim 1, wherein the dashboard is configured to:
send notifications to the user regarding any deviations from the optimal environmental parameters;
allow for manual or automatic adjustments in nutrient delivery, lighting, or air circulation based on real-time data.
5. The IoT-based sustainable device for monitoring and optimizing hydroponic plant growth as claimed in claim 1, wherein the renewable energy source comprises a solar panel system that provides at least 80% of the total energy consumption required for operating the device.
6. The IoT-based sustainable device for monitoring and optimizing hydroponic plant growth as claimed in claim 1, wherein the connectivity means is configured to operate under low-energy protocols, facilitating energy-efficient and long-range communication for remote monitoring.
7. The IoT-based sustainable device for monitoring and optimizing hydroponic plant growth as claimed in claim 1, wherein the cloud platform includes security features such as encryption, authentication, and data redundancy to ensure secure storage and transmission of sensor data.

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