Intelligent Smart Agriculture Methane Crop Yields Detection and Prediction for Machine Learning Techniques

S. P. Ramesh^1, and Dr. Muthusamy Periyasamy²

¹Research Scholar, Shri Venkateshwara University, Gajraula, Uttar Pradesh, India

²Professor, Shri Venkateshwara University, Gajraula, Uttar Pradesh, India

Cite this paper:
S. P. Ramesh and Dr. Muthusamy Periyasamy. Intelligent Smart Agriculture Methane Crop Yields Detection and Prediction for Machine Learning Techniques. Applied Ecology and Environmental Sciences. 2022; 10(8):509-518. doi: 10.12691/aees-10-8-3

Abstract

The MEVM (methane energy value model) was created for several energy crops. Machine learning has been created with big data developments and better enrolling than make new open doors for data genuine science in the multi-disciplinary agri-business progresses territory. By applying machine learning to sensor data, farm the chief's frameworks are forming into ceaseless artificial intelligence engaged tasks that give rich recommendations and encounters to farmer decision help and action. IoT contraptions give data about the nature of developing fields and a short time later make a move dependent upon the farmer input. The arrangement endeavors to mastermind diverse possible unstructured associations of crude data, assembled from different kinds of IoT devices, united and advanced self-ruling style using the upside of model changes and model-driven designing to change data in a coordinated structure.

Keywords:
machine learning big data Internet of Things (IoT)

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