METHOD FOR AGRICULTURAL PRODUCTIVITY ENHANCEMENT THROUGH IOT

Abstract

ABSTRACT A method (100) for agricultural productivity enhancement through IoT. Further, the method comprising deploying wireless sensors for real-time data collection on environmental parameters. Further, the method (100) comprising the steps of transmitting the data to a cloud-based platform for analysis and storage. Further, the method (100) comprising the steps of analyzing the data using machine learning algorithms for actionable insights. Further, the method (100) comprising the steps of providing a user interface for monitoring and alerts. Further, the method (100) comprising the steps of automating irrigation systems and generating reports for informed decision-making. <>

Specification

Description:
FIELD OF THE DISCLOSURE
[0001] This invention generally relates to the field of agricultural technology and, in particular, to a method for enhancing agricultural productivity through the use of Internet of Things (IoT) devices that facilitate real-time monitoring and data-driven decision-making, thereby promoting sustainable farming practices and optimizing resource utilization.
BACKGROUND
[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] The agricultural industry faces numerous challenges, including the need for increase , Claims:1. A method (100) for agricultural productivity enhancement through IoT, the method comprising the steps of:
deploying wireless sensors for real-time data collection on environmental parameters;
transmitting the data to a cloud-based platform for analysis and storage;
analyzing the data using machine learning algorithms for actionable insights;
providing a user interface for monitoring and alerts; and
automating irrigation systems and generating reports for informed decision-making.

2. The method (100) as claimed in claim 1, the wireless sensors are configured to measure additional parameters including nutrient levels and weather conditions, further enhancing the accuracy of the data analysis and the effectiveness of the actionable insights generated for crop management.

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