Environmental Monitoring and Assessment - Special Issue: Unmanned Aerial Vehicle for Optimize Irrigation and Crop Monitoring
With the increasing population, the demand for nourished food has increased constantly, which creates pressure on food producers and suppliers to avail good quality food in a sufficient amount to entire universe. Climatic condition, water supply (irrigation) and nutrients (fertilizer and pesticides) availability are three major factors that affect productivity of crop. With the increasing changes in of global warming and climatic condition invariable at same time, water and nutrients are becoming physically scarce due to growing multiple demands for water and fast exhausting of fossil fuels. To cope up with the scarcity of natural resources and improvement of crop production, it is necessary for the agricultural sector to adopt latest innovative aerial technologies to produce and satisfy the need of food nourishment while monitoring requirement of natural resources. Technological integration in smart agriculture not only helps in crop monitoring, and crop production tracking but also analysing several crop yielding operations like soil groundwork preparation, crop selection, seed collection, sowing of seed, crop growth and irrigation, soil fertilization, crop watering, harvesting etc.
Emergent technologies such as Internet of Things (IoT) can provide substantial potential in Smart agriculture and precision farming applications, allowing the acquisition of real-time ecological data. Unmanned Aerial Vehicles (UAVs) is one of IoT device that can be used to exploit variety of agriculture-based applications relevant to crops monitoring, optimized irrigation and crop management by capturing temporal and high-spatial resolution images. Unmanned aerial vehicle (UAV) integrates the concepts of information and communication technologies (ICT), robotics, artificial intelligence (AI), and big data analytics to help farmers in various agricultural task like growth monitoring of the vegetation, monitor crop or vegetation healthiness and crop irrigation management as well as ensure healthy and nutritious crop yielding production. Agriculture based UAVs are extremely proficient, and their usage has extended across all fields of agriculture, including fertilizer and pesticide squirting, seed sowing, irrigation and crop growth monitoring and mapping. Consequently, the market for agriculture-based UAVs is likely to continue rising with the associated technologies.
This special issue titled “Unmanned aerial vehicle for optimize irrigation and Crop Monitoring” provides emergent research discovering the hypothetical and real-world facets of critical technological explanations within the agriculture industry. This special issue focuses on introducing quality research that use unmanned aerial vehicles (UAV) for efficient irrigation planning, monitoring crop production based on climatic condition and requirement of soil nutrients. We welcome qualitative research articles from researchers, academicians and industrial expert that address advancement in agricultural sector by introducing latest technology like robotic systems, machine learning, cloud computation and big data analytics, and observe the effects of UAV for crop monitoring and enhancing productivity.
The topics of interest for the special issue include, but not limited to the following:
• UAV based Agriculture automation to optimize crop irrigation and crop monitoring.
• UAV enabled analysis of crop yielding process in a real time environment.
• Smart Farming with Autonomous UAV to analyse and optimize Crop harvesting Process.
• UAV data accumulation-based crop irrigation optimization model for horticulture in real time using machine learning.
• Crop plant monitoring in Polyhouse through UAV technology.
• Artificial Neural Network based Fungal infection detection and analysis of crop plant using UAV enabled image acquisition and segmentation algorithm.
• UAV integrated mobile application for image recognition and classification in plant pathology using deep learning based artificial neural networks.
• UAV enabled Soil irrigation and optimization model based on the analysis of soil moisture using artificial intelligence algorithm.
• Agronomic data collection and processing based IoT integrated UAV devices using convolution neural network.
• Recent applications of Unmanned aerial vehicle (UAV) in Smart Agriculture.
• Crop monitoring for pesticide and fertilization management Through cloud-based analysis and visualization using UAV.
• Soil recognition and classification based on fertility through feature extraction from UAV integrated cloud environment.
• Application of smart agricultural techniques to mitigate scarcity of water.
• Design model of smart agriculture based on UAV technology for water irrigation and soil fertilization.
• Real time analysis of UAV accumulated agronomic data for smart agriculture using latest computer intelligent algorithm.
• Analysis crop production using computer intelligence to detect the application of pesticides and herbicides.
Tentative Timeline
Submission Deadline of Papers: 31.12.2021
Authors Notification Date: 24.12.2021
Revised Papers Due Date: 28.02.2022
Final notification Date: 25.04.2022
Guest Editors:
Dr. S. Balamurugan
Senior Member IEEE
ACM Distinguished Speaker
Founder & Chairman, Albert Einstein Engineering and Research Labs (AEER Labs), Coimbatore, TamilNadu, India.
Vice Chairman of Renewable Energy Society of India (RESI)
balamurugan@ieee.org
dr.balamurugan@ircsresearch.com
sbnbala@gmail.com
Dr. BalaAnand Muthu
Associate Professor,
Department of Computer Science & Engineering,
Adhiyamaan College of Engineering, India.
balavdy@gmail.com
Dr. Sheng-Lung Peng
National Taipei university of business, Taiwan.
slpeng@ntub.edu.tw
Dr. Mohd Helmy Abd Wahab
Universiti Tun Hussein Onn Malaysia, Malaysia
helmy@uthm.edu.my