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Internet of things and analytics for agriculture.Volume 3

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Internet of things and analytics for agriculture.edited by Prasant Kumar Pattnaik, Raghvendra Kumar, Souvik Pal.
其他作者:	Pattnaik, Prasant Kumar.
出版者:	Singapore :Springer Singapore :2022.
面頁冊數:	xiv, 380 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Artificial intelligenceAgricultural applications.
電子資源:	https://doi.org/10.1007/978-981-16-6210-2
ISBN:	9789811662102$q(electronic bk.)

Internet of things and analytics for agriculture.Volume 3
Internet of things and analytics for agriculture.Volume 3[electronic resource] /edited by Prasant Kumar Pattnaik, Raghvendra Kumar, Souvik Pal. - Singapore :Springer Singapore :2022. - xiv, 380 p. :ill., digital ;24 cm. - Studies in big data,v. 992197-6511 ;. - Studies in big data ;v.1..

IoT: Foundations and Applications -- Functional Framework for IoT-based agricultural system -- Field monitoring and automation system -- Agriculture Sensor Network: Infrastructure, protocols and standards -- Implementation of sensors and RFID for disease and pest control -- Sensor-based Precision agriculture, Sensor data acquisition.

The book discusses one of the major challenges in agriculture which is delivery of cultivate produce to the end consumers with best possible price and quality. Currently all over the world, it is found that around 50% of the farm produce never reaches the end consumer due to wastage and suboptimal prices. The authors present solutions to reduce the transport cost, predictability of prices on the past data analytics and the current market conditions, and number of middle hops and agents between the farmer and the end consumer using IoT-based solutions. Again, the demand by consumption of agricultural products could be predicted quantitatively; however, the variation of harvest and production by the change of farm's cultivated area, weather change, disease and insect damage, etc., could be difficult to be predicted, so that the supply and demand of agricultural products has not been controlled properly. To overcome, this edited book designed the IoT-based monitoring system to analyze crop environment and the method to improve the efficiency of decision making by analyzing harvest statistics. The book is also useful for academicians working in the areas of climate changes.

ISBN: 9789811662102$q(electronic bk.)

Standard No.: 10.1007/978-981-16-6210-2doiSubjects--Topical Terms:

803531
Artificial intelligence
--Agricultural applications.

LC Class. No.: S494.5.D3 / I58 2022

Dewey Class. No.: 630.208563

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