Overview

The book focuses on the different aspects of sensing technology, i.e. high reliability, adaptability, recalibration, information processing, data fusion, validation and integration of novel and high performance sensors specifically aims to monitor agricultural and environmental parameters.   This book is dedicated to Sensing systems for Agricultural and Environmental Monitoring  offers to variety of users, namely, Master and PhD degree students, researchers, practitioners, especially Agriculture and Environmental engineers. The book will provide an opportunity of a dedicated and a deep approach in order to improve their knowledge in this specific field.

Full Product Details

Author:   Subhas Chandra Mukhopadhyay ,  Subhas Chandra Mukhopadhyay
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of the original 1st ed. 2012
Volume:   146
Dimensions:   Width: 15.50cm , Height: 2.10cm , Length: 23.50cm
Weight:   0.813kg
ISBN:  

9783662507940

ISBN 10:   3662507943
Pages:   386
Publication Date:   23 August 2016
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

From the content: An Autonomous Wireless Sensor/Actuator Network for Precision Irrigation in Greenhouses.- Optical Sensors to assist agricultural crop and pasture management.- Design, Implementation, and Testing of an M2M-based Remote Agroecological Monitoring System for Oriental Fruit Fly, Bactrocera dorsalis (Hendel).- Analysis of Moisture Content, Total Oil and Fatty Acid Composition by NIR Reflectance Spectroscopy: A Review.- Greenhouse Environment: Air and Water Monitoring.- The Effect of Temperature Factor on the Detection of Nitrate Contamination in Water Based on Planar Electromagnetic Sensor and Independent Component Analysis.- Latent Variable Models in the Understanding of Animal Monitoring Data.

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