PubAg

Main content area

The road towards plant phenotyping via WSNs: An overview

Author:
Al-Turjman, Fadi
Source:
Computers and electronics in agriculture 2019 v.161 pp. 4-13
ISSN:
0168-1699
Subject:
crops, fertilizers, hock, humidity, livestock productivity, phenotype, poultry industry, precision agriculture, temperature
Abstract:
The recent advances of wireless sensor networks have enabled the integration and application of this technology in vital environmental applications. Among these environmental applications, Plant Phenotyping (PP) arises as one of the state-of-the-art technologies that can introduce a significant increase to the crops, poultry and livestock productivity by effectively managing the available resources and providing the appropriate quantities in terms of water, food, temperature, humidity, fertilizers, etc. It can lead to increased productivity by more than a 100% in some agriculture applications such as the poultry industry. However, the application of the PP to various sectors of agriculture is still facing some serious limitations. The recent widespread of wireless networks and their applications has created a substantial demand for bandwidth and power resources, which is also the case for the PP scenario. To be able to collect precise data about a certain sector, it is usually required to deploy a massive number of low cost and low power wireless sensors. Therefore, such sensors are not expected to have high transmission power. Moreover, having a massive number of sensors communicating over wireless channels triggers the channel access organization and interference problems. Particularly a network is created in an ad hock manner.The aim of this survey paper is to provide a comprehensive understanding of the efficient techniques that can be utilized in increasing the capacity of Wireless ad hock Sensor Networks (WSNs) in PP. Although it can be applied for various precision agriculture applications, the reviewed techniques are mainly focused, analyzed and optimized for PP applications. We believe this promises significant new breakthroughs in plant science.
Agid:
6160238