Review—Machine Learning Techniques in Wireless Sensor Network Based Precision Agriculture
TL;DR: This paper is a comprehensive review of the application of different machine learning algorithms in sensor data analytics within the agricultural ecosystem and discusses a case study on an IoT based data-driven smart farm prototype as an integrated food, energy, and water (FEW) system.
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About: This article is published in Journal of The Electrochemical Society. The article was published on 01 Jan 2020. and is currently open access. The article focuses on the topics: Wireless sensor network & Precision agriculture.
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Citations
Machine Learning Applications for Precision Agriculture: A Comprehensive Review
TL;DR: In this paper, the authors present a systematic review of ML applications in the field of agriculture, focusing on prediction of soil parameters such as organic carbon and moisture content, crop yield prediction, disease and weed detection in crops and species detection.
A Comprehensive Review of Crop Yield Prediction Using Machine Learning Approaches With Special Emphasis on Palm Oil Yield Prediction
TL;DR: In this paper, a review on the use of machine learning algorithms to predict crop yield with special emphasis on palm oil yield prediction is presented, along with a brief discussion on the overview of widely used features and prediction algorithms.
Precision Irrigation Management Using Machine Learning and Digital Farming Solutions
Emmanuel Abiodun Abioye,Oliver Hensel,Travis Esau,Olakunle Elijah,Mohamad Shukri Zainal Abidin,Ajibade Sylvester Ayobami,Omosun Yerima,Abozar Nasirahmadi +7 more
TL;DR: How digital farming solutions, such as mobile and web frameworks, can enable the management of smart irrigation processes, with the aim of reducing the stress faced by farmers and researchers due to the opportunity for remote monitoring and control is discussed.
Towards Paddy Rice Smart Farming: A Review on Big Data, Machine Learning, and Rice Production Tasks
TL;DR: A survey of the latest research on intelligent data processing technology applied in agriculture, particularly in rice production, can be found in this paper, where the authors describe the data captured and elaborate role of machine learning algorithms in paddy rice smart agriculture.
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