Guest Editors
Dr. Muhammad Attique Khan, HITEC University, Pakistan.
Dr. Gaurav Dhiman, Government Bikram College of Commerce, India.
Dr. Sathishkumar V E, Hanyang University, Korea.
Summary
Today’s Agriculture faces lot of challenges in production and cost efficiency. Over the decades, as there is tremendous growth in world population with increased urbanization and change of habitation lead to high demand and revolution in food production. Though there exist challenges like change of climate, limited land against population and urbanization, non-availability of skilled labour there arise a need to achieve an increased demand in food production. This facilitates rapid acceleration in the progress of production to achieve the transition from manual farming process to fully automated farms and production farms with low cost. To attain this autonomous agriculture process in mere future, the major constituent is developing the autonomous system with accuracy and robust in nature for obtaining productive agriculture environment. Recent technological advancements with the emergence of new sensing modalities with computing power and algorithms has stimulated the growth of the perception systems for agriculture in the viewpoint of industry and research. Robotics and automation plays an expected key role in attaining these needs and challenges in the improvement of farm productivity in the technological era.
With the recent developments in Artificial Intelligence, many automated systems and machines exploded in various sectors. With the advent of automation in terms of autonomous intelligent robots, dynamic decision making, automated modelling and sensing has enabled the automated agricultural processes with lessened environmental influence and enhanced efficiency. These advancements march towards with the goal of fully automated machineries with low cost which is suitable for applying in agriculture and to be carried out rapidly in all the ways that incorporate sensors, automate robots, cloud storage, machine automation and genetics in smart agriculture. This smart agriculture can be implemented in various verticals such as crop monitoring, disease identification, harvesting, automated irrigation, weather monitoring and forecasting, crop yield prediction, resource availability monitoring, application of agrochemicals for harvesting, automatic packing and management till the identification of the needy consumers to the farmers.
Today’s research need to focus on automated ground with the implementation of robotics to perform all the operations with the gathered data in an effective way than the manual practices. The existing agriculture systems need to be applied with the precision farming using robotic technologies and automation with genetics to improve the resource efficiency and eco-friendly agriculture production that meet the needs of the growing population. Hence various research work should be performed to develop sustainable farming and analyse the impact of the environment, visualization and modelling for crop yield, automated seeding and agrochemical applying, cycling of water, eco-friendly fertilization, management of livestock, effective planning in crop harvesting, sensor fixation and remote monitoring of crop production, designing agriculture robotics, effective storage of sensed data in cloud and still more.
The objective of this special issue is to focus on the research articles on innovations in robotics and automation in agriculture. The aim of this issue also emphasis on presenting the issues and challenges, practical implementation problems pertaining to robotics and automation, and innovations and improvements to be developed in the agriculture field.
List of potential topics of interest include but not constrained to the following:
• Agricultural Robots – sensor devices and implementation
• Agricultural Robots – Planning and cost effective remote monitoring
• Intelligent Systems modelling for Robotics and Automation in Agriculture
• Pattern Recognition in implementation of Robotic Agriculture
• Robotic Automation in Smart Agriculture
• Intelligent Systems for Agricultural Robotics and Automation
• Smart agriculture – applications in aerial systems
• Big Data storage and maintenance in Robotics Agriculture
• Automated robotics for Quality Monitoring and pest control in Agriculture
• Robotics and automation in Agriculture– maintaining environment friendly atmosphere through aerial robotics
• Agricultural Automation – Integration with IoT and sensors in machines
• Crop yield Monitoring and phenotyping
• Automation in agriculture for disease detection and pest control
• Agricultural sensors and robots – harvesting, seeding and removal of weeds
• Dynamic decision making in crop monitoring through Aerial and ground robotic systems
• Quality monitoring in fruits/Crops for increased productivity
• Cost-effective sensing for all day monitoring in agriculture automation
Keywords
Agricultural Robots ; Sensor ; Automation ; Big data ; monitoring
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