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Fabrication of Remotely Controllable Robotic Weed-Ejector Vehicle
K. Girishma Yadav1, B. Druga Prasad2

1K Girishma Yadav, Department of Mechanical Engineering, JNTUA College of Engineering, Anantapur (Andhra Pradesh), India.

2Prof. B. Durga Prasad, Department of Mechanical Engineering, JNTUA College of Engineering, Anantapur (Andhra Pradesh), India. 

Manuscript received on 30 July 2024 | Revised Manuscript received on 27 August 2024 | Manuscript Accepted on 15 October 2024 | Manuscript published on 30 October 2024 | PP: 17-22 | Volume-14 Issue-1, October 2024 | Retrieval Number: 100.1/ijeat.A453714011024 | DOI: 10.35940/ijeat.A4537.14011024

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Weed is an unwanted plant in an agriculture field that keeps the crop plants deprived of sunlight, fertilisers and water. If not removed, weed reduces the crop output to a larger extent i.e., endangering the farmer’s interests. There are three main reasons for leaving weed to grow in fields and substantial loss of crop output 1) non-availability of agricultural labour, 2) fear of snake bites and 3) higher amounts of time required for weed injection. As of there are no successful ROVs (Remotely operating vehicles) to get to the weed and capable of pulling off the weed without the farmer physically entering into the agricultural fields. The Proposed model reduces farmers getting exposed to snake bites during weed ejection and reduces the time and labour requirement for weed ejection. The project involves the study of different mechanisms required for weed pull-off from the agricultural fields and remote-control systems, modelling of components, fabrication of components, assembly and testing of the Remotely Controllable Robotic Weed-Ejector Vehicle.

Keywords: Weed Mechanism, Testing of Remotely Controllable Vehicle, Remote Control System, Fabrication Components.
Scope of the Article: Artificial Intelligence & Methods