Smart Sensing Technology for Agriculture and Environmental Monitoring

Softcover Nachdruck of the original 1. Auflage 2012
ISBN: 978-3-662-50794-0
Verlag: Springer

Buch, Englisch, Band 146, 386 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 598 g

Reihe: Lecture Notes in Electrical Engineering

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.

Zielgruppe

Research

Autoren/Hrsg.

Chandra Mukhopadhyay, Subhas

Fachgebiete

• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umweltüberwachung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Sensorik
• Naturwissenschaften Agrarwissenschaften Agrarwissenschaften Agrartechnik, Landmaschinen
• Geowissenschaften Umweltwissenschaften Umweltüberwachung, Umweltanalytik, Umweltinformatik

Inhaltsverzeichnis

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.