Leaching Estimation for Paddy Crop using IoT and Machine Learning

Autor: Ch. Madhavi Sudha
Rok vydání: 2021
Předmět:
Zdroj: International Journal for Research in Applied Science and Engineering Technology. 9:4419-4423
ISSN: 2321-9653
DOI: 10.22214/ijraset.2021.36090
Popis: Soil salinity is a major issue in farming faced by many farmers across the globe. So it is very much important to identify the salinity level of the soil. Internet of Things (IoT) assisted solution is proposed to determine Electric Conductivity, temperature, and Moisture level at the root zone of the crop field. Internet of Things (IoT) and Machine Learning (ML), based leaching water requirements estimation for saline soils is made using the onsite monitoring of the salinity level and crop field temperature and crop growth stage. Food and Agricultural Organization (FAO) proposed method of leaching requirement is implemented for efficient leaching water estimation. These parameters are used to train and test the Machine learning model to predict the leaching requirement. The performance of machine learning is measured in terms of accuracy.
Databáze: OpenAIRE