The Smart Agriculture System Using IOT and ML

- Numerous countries have abundant resources, including land, rivers, groundwater, the environment, with agriculture serving as the primary source of income for many people in country. Nonetheless, resource shortage has grown in recent decades, particularly for groundwater and river water, so remote...

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Bibliographic Details
Published inJournal of Electrical Systems Vol. 20; no. 2; pp. 1539 - 1548
Main Authors Ghadge, Siddhi Vijay, Devale, Prakash, Deshmukh, Shrikala, Shah, Saloni, Gadhave, Ganesh, Pawar, Sarika, Limkar, Swapnali
Format Journal Article
LanguageEnglish
Published Paris Engineering and Scientific Research Groups 18.04.2024
Subjects
Agricultural production
Agriculture
Alarm systems
Automation
Crop yield
Fertilizers
Fire detection
Groundwater
Internet of Things
Irrigation systems
Machine learning
Rainfall
Remote control
Sensors
Spraying
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Summary:- Numerous countries have abundant resources, including land, rivers, groundwater, the environment, with agriculture serving as the primary source of income for many people in country. Nonetheless, resource shortage has grown in recent decades, particularly for groundwater and river water, so remote control smart irrigation system is developed to avoid access use and loss of water in the agriculture. A lack of information about the best use of available resources leads to increased resource consumption and worse crop yields. Choosing crops that are unsuited for the soil or climate reduces both quality and quantity of crop. As a result, system that recommends appropriate crops and fertilizers based on soil NPK values, soil colour, Season, PH, Rainfall, temperature etc has been developed. Fires are one of the most destructive global disasters, thus early detection is necessary to avoid the damages in agriculture. To reduce losses, an automated system capable of early fire detection through alarm systems and prompt extinguishing procedures through the roof structure pipeline in the farm is developed. Another use of that same pipeline is for spraying the pesticides and fertilizers. A potential resolution to address all these challenges involves the development and implementation of an intelligent agricultural system integrating Internet of Things (IOT) and Machine Learning technologies.
ISSN:1112-5209
DOI:10.52783/jes.1457