Automated agricultural field analysis and monitoring system using IOT
Автор: Kajol R., Akshay Kashyap K., Keerthan Kumar T. G.
Журнал: International Journal of Information Engineering and Electronic Business @ijieeb
Статья в выпуске: 2 vol.10, 2018 года.
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Smarter world is the resultant of the smarter technology. Agriculture was implemented in the nine of sedentary human civilization and it is the backbone of our Indian Economy. But the same traditional techniques like manual field monitoring, water feeding, pest detection, soil testing, etc., we are using for monitoring the field and frequently applying pesticides with or without having the knowledge of quantity to be used to control pests that affect the crops. So it is very important to enhance the agricultural production by making use of technology to overcome the damages being done. Our aim is to provide smart monitoring system using the current technologies like IoT, cloud computing and image processing. To address the above problems the authors of this paper are coming up with a model named “AAFAMS”( Automated Agricultural Field Analysis and Monitoring System Using IOT) which is used not only for monitoring the field but also to suggest the farmers about the moisture content in soil, detecting pest and the type of crop suited for the soil. In AAFAMS, a line follower robot is developed by using a hardware kit called Raspberry pi, which monitors the soil moisture level at every 100m distance using a soil moisture sensor and the information obtained from the sensor will be sent to cloud for storage. A camera will be connected to the AAFAMS which will detect the pests. After complete survey of field AAFAMS retrieves all stored data from cloud and SQLite database to provide a detailed report of Moisture content and Pests information and suggests farmer with the required pesticide. AAFAMS runs either on batteries or solar panel by utilizing the solar energy available and thereby helping farmers to monitor their fields effectively.
IoT, Cloud computing, image processing, line follower, Raspberry pi, sensor
Короткий адрес: https://sciup.org/15016125
IDR: 15016125 | DOI: 10.5815/ijieeb.2018.02.03
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