UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 8
August-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2108502


Registration ID:
314391

Page Number

e156-e160

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Title

Embedded Sensors Combined with Artificial Intelligence for Improved Agricultural Yield

Authors

Abstract

Automation in agriculture is a big cause of concern and a hot subject all around the world. The world's population is rapidly growing, increasing the demand for food and jobs. Traditional farming practices were insufficient to meet these objectives. New automated procedures were created as a result. These innovative techniques met food demands while also offering employment opportunities for billions of people. Artificial intelligence (AI) has easily slipped into a range of monitoring and control applications, including agriculture. Attempts to build low-power sensing devices with fully functional AI, on the other hand, are still dispersed. In this work, we provide an AI-enhanced embedded system for studying and predicting plant leaf growth dynamics in real time. The embedded solution is based on a low-power embedded sensor device with a GPU capable of running neural network-based AI on the device. A Recurrent Neural Network (RNN) and a Long-Short Term Memory Network (LSTMN) are the foundations of our AI system. The recommended approach assures the system's autonomy for 180 days using a standard Li-ion battery. We use cutting-edge mobile graphics processors for smart analysis and administration of autonomous devices. This work paves the way for a variety of sophisticated monitoring applications, especially in agriculture.

Key Words

Embedded sensing, Smart sensing, Artificial intelligence, Precision agriculture, Sensing and control

Cite This Article

"Embedded Sensors Combined with Artificial Intelligence for Improved Agricultural Yield", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 8, page no.e156-e160, August-2021, Available :http://www.jetir.org/papers/JETIR2108502.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Embedded Sensors Combined with Artificial Intelligence for Improved Agricultural Yield", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 8, page no. ppe156-e160, August-2021, Available at : http://www.jetir.org/papers/JETIR2108502.pdf

Publication Details

Published Paper ID: JETIR2108502
Registration ID: 314391
Published In: Volume 8 | Issue 8 | Year August-2021
DOI (Digital Object Identifier):
Page No: e156-e160
Country: Pandalam, kerala, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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