Artificial Intelligent Systems and Machine Learning

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Crop Yield Prediction Using IoT


Affiliations
1 Department of ISE, Rashtreeya Vidyalaya College of Engineering, Bengaluru-560059, India
     

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Internet of Things (IoT) devices are used to communication between different things is effective. The application of IoT in agriculture industry plays a key role to make functionalities easy. Using the concept of IoT and Wireless Sensor Network (WSN), smart farming system has been developed in many areas of the world. Atmosphere, crop hereditary qualities, crop management (intensity as well as management skill level) and the substance and physical properties of soils have significant effects on crop yield soil conditions, especially change stunningly from farm to residence and field to field and conditions can contrast even inside an individual field.


Keywords

IoT, WSN, Precision Agriculture, Yield Prediction.
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Abstract Views: 329

PDF Views: 4




  • Crop Yield Prediction Using IoT

Abstract Views: 329  |  PDF Views: 4

Authors

Nitin Shettar
Department of ISE, Rashtreeya Vidyalaya College of Engineering, Bengaluru-560059, India
B. M. Sagar
Department of ISE, Rashtreeya Vidyalaya College of Engineering, Bengaluru-560059, India
N. K. Cauvery
Department of ISE, Rashtreeya Vidyalaya College of Engineering, Bengaluru-560059, India

Abstract


Internet of Things (IoT) devices are used to communication between different things is effective. The application of IoT in agriculture industry plays a key role to make functionalities easy. Using the concept of IoT and Wireless Sensor Network (WSN), smart farming system has been developed in many areas of the world. Atmosphere, crop hereditary qualities, crop management (intensity as well as management skill level) and the substance and physical properties of soils have significant effects on crop yield soil conditions, especially change stunningly from farm to residence and field to field and conditions can contrast even inside an individual field.


Keywords


IoT, WSN, Precision Agriculture, Yield Prediction.

References