An IoT-Based Robotic Irrigation System for Optimal Water Management

This paper presents the design, implementation, and testing of an autonomous smart irrigation robot. The main aim is to optimize water use in agriculture through innovative integration of the Internet of Things (IoT) technology and renewable energy sources. The robot's architecture is composed of sensors, autonomous navigation, and remote data management systems, all powered by a solar-charged battery. In field tests, the robot displayed a high level of sensor accuracy, satisfactory navigation, and reliable data transfer to the cloud. Challenges such as environmental resilience, energy optimization, data transmission, and system durability were identified and addressed, paving the way for further refinement. Future iterations of the project will focus on incorporating predictive analytics for dynamic irrigation scheduling, enhancing user experience through interface personalization, achieving autonomous operational decision-making, and ensuring scalability for diverse agricultural contexts.

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Publication Details

Published
2025-02-07
DOI
https://doi.org/10.1109/etis64005.2025.10961321
Citations
1
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
0.82
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article

An IoT-Based Robotic Irrigation System for Optimal Water Management

Anshu Prakash Murdan, Bradley Matthew Wong Hon Lang
1 citations
Water Quality Monitoring Technologies
0.82
article

An IoT-Based Robotic Irrigation System for Optimal Water Management

Anshu Prakash Murdan, Bradley Matthew Wong Hon Lang
article en
1 citations

Abstract

This paper presents the design, implementation, and testing of an autonomous smart irrigation robot. The main aim is to optimize water use in agriculture through innovative integration of the Internet of Things (IoT) technology and renewable energy sources. The robot's architecture is composed of sensors, autonomous navigation, and remote data management systems, all powered by a solar-charged battery. In field tests, the robot displayed a high level of sensor accuracy, satisfactory navigation, and reliable data transfer to the cloud. Challenges such as environmental resilience, energy optimization, data transmission, and system durability were identified and addressed, paving the way for further refinement. Future iterations of the project will focus on incorporating predictive analytics for dynamic irrigation scheduling, enhancing user experience through interface personalization, achieving autonomous operational decision-making, and ensuring scalability for diverse agricultural contexts.

University of Mauritius (MU)
Clean water and sanitation
Openalex Percentile: Top 27%
Water Quality Monitoring Technologies
0.82
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An IoT-Based Robotic Irrigation System for Optimal Water Management — Anshu Prakash Murdan, Bradley Matthew Wong Hon Lang · (2025) | TGRS Research Map | TGRS