IoT and Analytics for Agriculture / edited by Prasant Kumar Pattnaik, Raghvendra Kumar, Souvik Pal, S. N. Panda

Contributor(s):

Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Studies in Big Data ; 63 | Springer eBooks Intelligent Technologies and RoboticsPublisher: Singapore : Springer, 2020Edition: 1st ed. 2020Description: 1 Online-Ressource (XVII, 240 p. 84 illus., 60 illus. in color)ISBN:

9789811391774

Subject(s):

Additional physical formats: 9789811391767 | Erscheint auch als: 978-981-13-9176-7 Druck-AusgabeDDC classification:

629.892 23

LOC classification:

TJ210.2-211.495 T59.5

DOI: DOI: 10.1007/978-981-13-9177-4Online resources:

Summary: Expert system for soil management:pHcontrol, Moisture content -- Integrating Big Data Practices in Agriculture -- Solar Powered Automated IoT based Drip irrigation system -- Internet of Things Foundations and its Application -- e-Device for the Protection of Agricultural Land from Elephant Attacks in Odisha: A Review -- Impact Of Irrigation On Agricultural Productivity In Bolpur Sub Division, West Bengal -- Big Data, Climate Smart Agriculture and India-Africa Relations: A Social Science Perspective -- IoT Enabled Agricultural System Applications, Challenges and Security Issues -- A Design of IoT Based Agricultural System for Optimal ManagementSummary: This book presents recent findings on virtually every aspect of wireless IoT and analytics for agriculture. It discusses IoT-based monitoring systems for analyzing the crop environment, and methods for improving the efficiency of decision-making based on the analysis of harvest statistics. In turn, it addresses the latest innovations, trends, and concerns, as well as practical challenges encountered and solutions adopted in the fields of IoT and analytics for agriculture. In closing, it explores a range of applications, including: intelligent field monitoring, intelligent data processing and sensor technologies, predictive analysis systems, crop monitoring, and weather data-enabled analysis in IoT agro-systemsPPN: PPN: 168172684XPackage identifier: Produktsigel: ZDB-2-INR | ZDB-2-SEB | ZDB-2-SXIT

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