Multi-Tasking Agri-Bot for Integrated Field and Lawn Operations: An Experimental Study

The present systems for irrigation and lawn upkeep have inefficient water consumption, poor coverage, no automation, which contributes to resource loss and productivity decline. This specific work meets these eco-friendly agricultural innovations shortcomings through the integration of eco-seeding, eco-irrigation, eco-pesticide spraying, and eco-mowing into one system. Agri-Bot has sophisticated features that enable it to function independently by planting crops, irrigating, pesticide spraying, and mowing lawns. By default, the robot with an ultrasonic sensor is capable of steering and avoiding blockages without being led through set routes. Furthermore, its ability to capture solar energy renders it free from climatic conditions to provide reliable eco-friendly farming. Further, the unit is controlled through a custom developed native application that is multilingual, includes voice recognition, and is designed to extend user experience. This kind of multifunctional unit eases the farmers work burden and reduces human resource dependency for farming tasks. The Agri-Bot is constructed to be automated and operational in farming which increases the degree of control and farming sustainability. Its integration of various sensors and actuators provides the capability to accomplish many tasks accurately and consistently over a large tract of land.

Authors

Institutions

Publication Details

Journal
Premier journal of science.
Published
2025-12-27
DOI
https://doi.org/10.70389/pjs.100145
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-Tasking Agri-Bot for Integrated Field and Lawn Operations: An Experimental Study

Sharath Jayachandran, V S Prabhu, Prabhudev Jagadeesh, V. Harinath et al.
Premier journal of science.
Smart Agriculture and AI
article

Multi-Tasking Agri-Bot for Integrated Field and Lawn Operations: An Experimental Study

Sharath Jayachandran, V S Prabhu, Prabhudev Jagadeesh, V. Harinath, S. Leo Jerry
article en

Abstract

The present systems for irrigation and lawn upkeep have inefficient water consumption, poor coverage, no automation, which contributes to resource loss and productivity decline. This specific work meets these eco-friendly agricultural innovations shortcomings through the integration of eco-seeding, eco-irrigation, eco-pesticide spraying, and eco-mowing into one system. Agri-Bot has sophisticated features that enable it to function independently by planting crops, irrigating, pesticide spraying, and mowing lawns. By default, the robot with an ultrasonic sensor is capable of steering and avoiding blockages without being led through set routes. Furthermore, its ability to capture solar energy renders it free from climatic conditions to provide reliable eco-friendly farming. Further, the unit is controlled through a custom developed native application that is multilingual, includes voice recognition, and is designed to extend user experience. This kind of multifunctional unit eases the farmers work burden and reduces human resource dependency for farming tasks. The Agri-Bot is constructed to be automated and operational in farming which increases the degree of control and farming sustainability. Its integration of various sensors and actuators provides the capability to accomplish many tasks accurately and consistently over a large tract of land.

Premier journal of science.
Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN), National Institute of Technology Meghalaya (IN)
Zero hunger
Openalex Percentile: Top 23%
Smart Agriculture and AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.