2018
DOI: 10.11591/ijeecs.v10.i2.pp456-468
|View full text |Cite
|
Sign up to set email alerts
|

Internet of Things based Wireless Plant Sensor for Smart Farming

Abstract: <p>About 10% of the world’s workforce is directly dependent on agriculture for income and about 99% of food consumed by humans comes from farming. Agriculture is highly climate dependent and with global warming and rapidly changing weather it has become necessary to closely monitor the environment of growing crops for maximizing output as well as increasing food security while minimizing resource usage. In this study, we developed a low cost system which will monitor the temperature, humidity, light inte… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
9
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
6
4

Relationship

0
10

Authors

Journals

citations
Cited by 26 publications
(11 citation statements)
references
References 26 publications
(23 reference statements)
0
9
0
Order By: Relevance
“…Commercial engineering development of low-cost eddy covariance networks, to attain state-wide spatial coverage across the US or for specific regions, for example, coupled with innovative features, including unmanned aerial vehicles (Berman et al, 2012; Metzger et al, 2012), shared data networks (Dai et al, 2018) and automated reporting is achievable offering a modernized alternative to estimation protocols. Advancements in blockchain accounting platforms (Düdder & Ross, 2017), artificial intelligence (Reis et al, 2018) and the internet of things (Subashini et al, 2018) can be readily integrated within eddy covariance networks but for the reasons we discuss here cannot be successful without direct measurement of CO 2 . Eddy covariance as an instrumental method has characteristic limitations and uncertainties (Nicolini et al, 2018) and faces engineering challenges for large-scale deployment as well as upscaling eddy covariance methods (Barba et al, 2018; Kumar et al, 2016; Ran et al, 2016; Warner et al, 2019; Wutzler et al, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…Commercial engineering development of low-cost eddy covariance networks, to attain state-wide spatial coverage across the US or for specific regions, for example, coupled with innovative features, including unmanned aerial vehicles (Berman et al, 2012; Metzger et al, 2012), shared data networks (Dai et al, 2018) and automated reporting is achievable offering a modernized alternative to estimation protocols. Advancements in blockchain accounting platforms (Düdder & Ross, 2017), artificial intelligence (Reis et al, 2018) and the internet of things (Subashini et al, 2018) can be readily integrated within eddy covariance networks but for the reasons we discuss here cannot be successful without direct measurement of CO 2 . Eddy covariance as an instrumental method has characteristic limitations and uncertainties (Nicolini et al, 2018) and faces engineering challenges for large-scale deployment as well as upscaling eddy covariance methods (Barba et al, 2018; Kumar et al, 2016; Ran et al, 2016; Warner et al, 2019; Wutzler et al, 2018).…”
Section: Discussionmentioning
confidence: 99%
“…IoT devices most of the time are usually limited in terms of resource and power supply. For example, the power supply system that manages the task of distributing required power to the components and regulating the voltage from the battery of a proposed agricultural IoT device is capable of running at only 5V with a 5000 mAh Li-ion battery [18].…”
Section: Security System For Sg Networkmentioning
confidence: 99%
“…Nowadays, agriculture is becoming more productive because of advancements and the latest technologies as sensors, devices, and information technology that help generate a large amount of data [1]. However, irrigation scheduling can be more efficient by using new technologies based on accurate crop and irrigation models, weather forecasting, sensors, IoT, AI, and cloud computing [2]. Irrigation scheduling is considered one of the most prevalent problems of the agriculture system.…”
Section: Introductionmentioning
confidence: 99%