IOT-BASED SOIL MOISTURE DETERMINATION SYSTEM

Abstract

An IoT-based system for determining soil moisture content is disclosed in the current invention. The system monitors and controls soil moisture levels in real-time using Internet of Things (IoT) technology. In order to gather information on the moisture content of the soil, a network of sensors has been buried in the ground. Wireless transmission of this data to a central platform for processing and analysis is used. By giving farmers precise and timely information on soil moisture levels, the device can assist them to maximize crop output via - irrigation strategies.

Specification

Field of the Invention: loT-based systems and techniques for regulating soil moisture are the focus of the current innovation, which is related to the subject of agricultural technology.
Background of the Invention: Conserving water and increasing agricultural productivity need efficient irrigation management. Water is used inefficiently because traditional soil moisture monitoring techniques are often labor-intensive and do not offer real-time data. An answer is provided by IoT technology, which makes it possible to remotely monitor and - control soil moisture levels. The idea gives farmers precise and useful information to adjust irrigation schedules based on real soil moisture levels by merging sensors, wireless connectivity, and cloud computing.
Summary of the Invention: The system made available by the current invention measures soil moisture content by means of an Internet of Things network of sensors that are implanted in the soil. Wirelessly transmitted data from the sensors is processed and analysed at a central Internet of Things platform. To understand soil moisture levels, machine learning algorithms are used to analyze the data. With the system's user interface, fanners may monitor soil moisture levels and get advice for improving imgeation techniques from their PCs or mobile devices.


1. Sensor Network: An agricultural area that is covered with a network of sensors measuring soil moisture. At different depths and places, sensors monitor the moisture content of the soil. 2. Data Collection and Transmission: Wireless communication modules (e.g., LoRa, NB-IoT)-equipped data gathering devices. Real-time data from devices is sent for analysis to a central IoT platform. 3. IoT Platform: An Internet of Things platform running on the cloud that gathers, stores, and handles data from the sensor network, provides useful insights by analyzing soil moisture data using machine learning methods.
4. User Interface: -An intuitive user interface that may be accessed on PCs or mobile deVices. offers historical data analysis, irrigation suggestions, and real-time monitoring of soil moisture levels.
Sensor Network: An agricultural field-wide network of soil moisture sensors is part of the Internet of Things-based system for determining soil moisture. For reliable measurements of soil moisture content, these sensors are buried at varying depths. They detect soil moisture content using technological tools like capacitance and resistance. 2. Data Collection and Transmission: Continuous data collection is accomplished via soil moisture sensors, which wirelessly send the data to a central IoT platform. Wireless communication methods, such Wi-Fi, NB-IoT, and LoRa (Long Range), are used in the data transmission process to provide dependable and instantaneous data transfer.
3. IoT Platform: Data provided by the sensor network is received by the central IoT platform. The information is processed by machine learning algorithms and kept safely on the cloud. In order to identify trends, patterns, and anomalies in the soil moisture data, these algorithms evaluate it. This process yields important information about the
state of the soil. 4. Machine Learning Algorithms: When analyzing the soil moisture data, machine learning methods are used. With the use of historical data, weather predictions, and other pertinent information, these algorithms are able to estimate soil moisture levels.
In order to assist farmers make educated choices and maximize crop productivity and water consumption, they also provide suggestions for irrigation timing. 5. User Interface: Computers and mobile devices may access the system's user interface. This interface allows farmers to monitor the soil moisture levels in real time, which are shown on clear graphs and charts. Farmers are also able to compare current circumstances with historical observations thanks to the presentation of historical data analysis and trends. Optimal water management techniques are ensured by the interface, which offers irrigation suggestions based on the soil moisture levels at the moment. -


We Claim
26-Nov-2024/140490/202441092053/Form 2(Title Page)
1. A cloud-based Internet of Things platform that receives, stores, and processes data from the sensor network using machine learning algorithms to analyze soil moisture levels; • A user interface accessible via computers or mobile devices that provides real-time monitoring of soil moisture levels, historical data analysis, and irrigation recommendations. • A network of soil moisture sensors embedded in the agricultural field to measure soil
moisture content.
• Data collection devices equipped with wireless communication modules for transmitting real-time data to a central loT platform.

2. The system of claim 1, where the soil moisture sensors detect capacitance or resistance to determine soil moisture levels. 3. In claim 1, the wireless communication modules employ protocols such as LoRa, NB-IoT, or Wi-Fi to provide reliable and real-time data transfer. 4. The system of claim 1, in which the IoT platform uses machine learning algorithms to assess soil moisture data and offer information about soil conditions. 5. In claim 1, the user interface provides real-time soil moisture levels, historical data analysis, and irrigation suggestions in the form of comprehensible graphs and charts. 6. The system of claim 1, wherein the machine learning algorithms anticipate soil moisture levels using historical data', weather predictions, and other pertinent information. 7. The system of claim 1, wherein the user interface allows farmers to compare current soil moisture levels to previous measurements and alter irrigation operations appropriately.

Documents