Journal ArticleDOI
An IoT based smart irrigation management system using Machine learning and open source technologies
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TLDR
An open-source technology based smart system to predict the irrigation requirements of a field using the sensing of ground parameter like soil moisture, soil temperature, and environmental conditions along with the weather forecast data from the Internet is presented.About:
This article is published in Computers and Electronics in Agriculture.The article was published on 2018-12-01. It has received 334 citations till now. The article focuses on the topics: Smart system & Precision agriculture.read more
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A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming
TL;DR: The article explains the major components of IoT based smart farming, including network architecture and layers, network topologies used, and protocols, and some open research issues and challenges in IoT agriculture field have been presented.
Journal ArticleDOI
A systematic literature review on machine learning applications for sustainable agriculture supply chain performance
TL;DR: An ML applications framework for sustainable ASC is proposed and identifies the role of ML algorithms in providing real-time analytic insights for pro-active data-driven decision-making in the ASCs and provides the researchers, practitioners, and policymakers with guidelines on the successful management of ASCs for improved agricultural productivity and sustainability.
Journal ArticleDOI
IoT-Based Smart Irrigation Systems: An Overview on the Recent Trends on Sensors and IoT Systems for Irrigation in Precision Agriculture
TL;DR: A survey aimed at summarizing the current state of the art regarding smart irrigation systems, which determines the parameters that are monitored in irrigation systems regarding water quantity and quality, soil characteristics and weather conditions.
Journal ArticleDOI
Survey on IoT security: Challenges and solution using machine learning, artificial intelligence and blockchain technology
TL;DR: This survey systematically study the three primary technology Machine learning(ML), Artificial intelligence (AI), and Blockchain for addressing the security issue in IoT.
Journal ArticleDOI
Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies
TL;DR: In this article, a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture is presented, including unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV), cloud/fog computing, and middleware platforms.
References
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Book
Crop evapotranspiration : guidelines for computing crop water requirements
TL;DR: In this paper, an updated procedure for calculating reference and crop evapotranspiration from meteorological data and crop coefficients is presented, based on the FAO Penman-Monteith method.
Journal ArticleDOI
Internet of Things (IoT): A vision, architectural elements, and future directions
TL;DR: In this article, the authors present a cloud centric vision for worldwide implementation of Internet of Things (IoT) and present a Cloud implementation using Aneka, which is based on interaction of private and public Clouds, and conclude their IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.
Journal ArticleDOI
An efficient k-means clustering algorithm: analysis and implementation
Tapas Kanungo,David M. Mount,Nathan S. Netanyahu,Christine D. Piatko,Ruth Silverman,Angela Y. Wu +5 more
TL;DR: This work presents a simple and efficient implementation of Lloyd's k-means clustering algorithm, which it calls the filtering algorithm, and establishes the practical efficiency of the algorithm's running time.
Journal ArticleDOI
Support vector machines
TL;DR: This issue's collection of essays should help familiarize readers with this interesting new racehorse in the Machine Learning stable, and give a practical guide and a new technique for implementing the algorithm efficiently.
Proceedings Article
Support Vector Regression Machines
TL;DR: This work compares support vector regression (SVR) with a committee regression technique (bagging) based on regression trees and ridge regression done in feature space and expects that SVR will have advantages in high dimensionality space because SVR optimization does not depend on the dimensionality of the input space.