Shafi, U, Mumtaz, R, Hassan, SA et al. (3 more authors) (2019) Crop Health Monitoring Using IoT-Enabled Precision Agriculture. In: Chowdhry, BS, Shaikh, FK and Mahoto, NA, (eds.) IoT Architectures, Models, and Platforms for Smart City Applications. Advances in computer and electrical engineering . IGI Global , Pennsylvania, USA , pp. 134-154. ISBN 9781799812531
Abstract
Agriculture holds paramount significance in Pakistan due to its high impact on gross domestic product (GDP). However, there is huge gap between actual production and estimated production in agriculture due to manual farming system, which is time-consuming, inefficient, and labor-intensive. As of today, ultra-modern technology such as Internet of Things (IoT) can assist in acquiring timely and accurate crop information essential for the success of precision agriculture technology. Towards such ends, the authors propose an IoT-based crop health monitoring system comprised of different sensors used in agricultural fields. Additionally, low altitude remote sensing platforms, such as drones, are used to capture the spectral imagery of the entire crop field of the study region. The development of such a system can be instrumental for crop status monitoring and localizing the areas under stress to maximize the agricultural output by leveraging the IoT technology.
Metadata
Item Type: | Book Section |
---|---|
Authors/Creators: |
|
Editors: |
|
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 Dec 2019 12:02 |
Last Modified: | 23 Dec 2019 12:02 |
Published Version: | https://www.igi-global.com/gateway/book/231908#pnl... |
Status: | Published |
Publisher: | IGI Global |
Series Name: | Advances in computer and electrical engineering |
Identification Number: | 10.4018/978-1-7998-1253-1.ch007 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:154861 |