Scientific Programming for Precision Agriculture
1Islamia University of Bahawalpur, Bahawalpur, Pakistan
2Zhongnan University of Economics and Law, Wuhan, China
3Inha Technical College, Incheon, Republic of Korea
Scientific Programming for Precision Agriculture
Description
In recent years, software applications for smart environments, such as precision agriculture, have become a major trend in computing. Modern agricultural control needs the integration of sensor data and imaging inputs with other data, providing farmers with the ability to identify fields that require treatment and to determine the optimum amount of water, fertiliser, and pesticides to apply. Such smart systems in agriculture may help farmers to avoid wasting resources and prevent run-off, ensuring that the soil has the right number of additives for optimum health, while reducing costs and controlling the farm's environmental impact.
In the past, precision agriculture has been limited to larger operations able to support the IT infrastructure and other technology resources required to fully implement and profit from precision agriculture. Today, however, mobile applications, smart sensors, drones, and cloud computing can help to make precision agriculture viable for farming cooperatives and even small family farms. However, there is a need to analyse, model, and implement precision agriculture-assisted software applications that are not only effective and energy efficient but also easy to use.
The aim of this Special Issue is to bring together academic and industrial practitioners to exchange and discuss the latest innovations in the programming aspects of software applications that focus on the modelling and programming of efficient software applications for precision agriculture. Modern agriculture requires smart applications that are not only capable of decision making but are also energy efficient. For such features in applications, there is the need to explore and identify new models and new ways of programming to incorporate these demanding features into classical programming techniques.
Potential topics include but are not limited to the following:
- Programming for decision making in precision agriculture
- Programming smart applications for precision agriculture
- Programming to handle uncertainty in precision agriculture applications
- Programming for feedback and synthesis of precision agriculture
- Programming energy efficient applications for precision agriculture