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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM33610
Volume:
8 |
5 |
May 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In response to the imperatives of modern agriculture, our project presents a comprehensive precision agriculture solution centered around a multifunctional robocar. This autonomous vehicle integrates IoT sensors for data-driven crop management, employing machine learning for monitoring and predicting yields while optimizing resource utilization. Automation features include automated obstacle avoidance, periodic image capture, and automatic water spraying for real-time data collection and management, empowering farmers with actionable insights for informed decision-making. Additionally, a web-based platform utilizing Streamlit framework facilitates rapid and accurate crop disease detection using a meticulously trained VGG19 model from uploaded images. By embracing advanced technology, our solution aims to enhance agricultural productivity and pave the way for a sustainable future.
KEYWORDS
Publication Date
12/31/45421
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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