An IoT-Based Smart System for Crop Management by Dynamic Irrigation System Using Artificial Intelligence

The current scenario in agriculture nowadays relies on efficient management of irrigation because of the world's expanding consumption of food and shortages of water and agricultural land. This paper presents an intelligent production administration system based on the Internet of Things (IoT) that combines artificial intelligence (AI) with self-activated, accruable irrigation to conserve water dynamically. To find out when feeding is necessary for the crop, the system initiates the algorithm which is proposed to gather dynamic, real-time information from soil moisture sensors, weather predictions, and plant growth indicators with the help of machine learning algorithm. The research results indicate that by dynamically modifying the amount of irrigation in response to soil and plant needs and environmental circumstances, the proposed method can improve crop output as well as quality, while producing significant water savings throughout the period in cultivation.

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Publication Details

Published
2025-04-04
DOI
https://doi.org/10.1109/icaeca63854.2025.11012375
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.75
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article

An IoT-Based Smart System for Crop Management by Dynamic Irrigation System Using Artificial Intelligence

M. Manikantan, R. Dhivakar, P. Parameswari
1 citations
Smart Agriculture and AI
1.75
article

An IoT-Based Smart System for Crop Management by Dynamic Irrigation System Using Artificial Intelligence

M. Manikantan, R. Dhivakar, P. Parameswari
article en
1 citations

Abstract

The current scenario in agriculture nowadays relies on efficient management of irrigation because of the world's expanding consumption of food and shortages of water and agricultural land. This paper presents an intelligent production administration system based on the Internet of Things (IoT) that combines artificial intelligence (AI) with self-activated, accruable irrigation to conserve water dynamically. To find out when feeding is necessary for the crop, the system initiates the algorithm which is proposed to gather dynamic, real-time information from soil moisture sensors, weather predictions, and plant growth indicators with the help of machine learning algorithm. The research results indicate that by dynamically modifying the amount of irrigation in response to soil and plant needs and environmental circumstances, the proposed method can improve crop output as well as quality, while producing significant water savings throughout the period in cultivation.

Zero hunger
Openalex Percentile: Top 15%
Smart Agriculture and AI
1.75
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