Document Type : Primary Research paper
Authors
1
Assistant Professor, Department of Biology, College of Natural and Computational Science, Dambi Dollo University, Dambi Dollo, Oromia Region, Ethiopia.
2
Associate Professor & HoD, Department of ECE, Vivekanandha College of Engineering for Women, Elayampalayam, Tiruchengode, Namakkal, Tamil Nadu, India.
3
Assistant Professor, Department of Mechanical Engineering, Vignan's Foundation for Science Technology and Research, Vadlamudi, Guntur, Andhra Pradesh, India.
4
Assistant Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram , Guntur, Andhra Pradesh, India.
5
Associate Professor, Department of Computer Science and Engineering, Velammal Institute of Technology, Velammal Knowledge Park, Chennai, India.
6
Assistant Professor, Department of EEE, St. Peter's Institute of Higher Education and Research, Avadi, Chennai, India.
Abstract
Smart agriculture was introduced in all developing countries of the world, but all farmers are not cultivated more crops and yield due to their land parameters problems such as quality of soil, water contaminants, and nutrition. Cultivating more amounts of plants is possible in some farmer's land where the neighboring land doesn’t produce that much growth will lead to a major problem in agriculture. Researchers were doing more experiments on this but they are not concluding that this land will produce all kinds of crops and plants effectively. There are multiple methods used by the small-scale farmers, nevertheless, the improvement was not at the expected level especially in paddy, vegetable cultivation. To overcome this problem in developed countries drones are used to find the soil quality and nutrition level of the farmers and with the pictures taken from the drones. Based on the results given by the drones, the affected areas are identified and their nutrition level is also found in agricultural land. Smart devices like mobile phones, tabs are used with applications or software to reveal the amount of nutrition provided to that land and fertilizers used also. This research work proposed a method called Geo-Fencing which is used to identify the soil quality and nutrition of the land with the help of drone images. Analytics can be done with the help of application software and notifications will send to the farmers for using them in regular intervals. This research also improves the land quality by adding fertilizers to produce the expected crops and vegetables in each season.
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