Germination Predication to Access the Quality of Grains for Different Crops Using IoT and Machine Learning

Germination Predication to Access the Quality of Grains for Different Crops Using IoT and Machine Learning

Dr. Bharathi M, Manish Kumar , Monisha B N, Preethi M and Rahila Fardeen

Department of Computer Science and Design

S J C Institute of Technology Chikballapur, India

Abstract— The paper expounds on a advanced framework that consistently blends Counterfeit Insights (AI) and Web of Things (IoT) innovations to figure seed germination in rural settings. It underscores the noteworthiness of leveraging real-time information sourced from soil sensors nearby cutting-edge machine learning calculations to supply important bits of knowledge into the designs of edit germination. This imaginative framework is made with the essential objective of preparing ranchers with opportune and significant data, subsequently encouraging educated decision-making forms relating to water system procedures and asset assignment. Central to the system's engineering is its versatility, encouraged by a cloud-based stage that empowers consistent development and adjustment to shifting rural necessities. This guarantees not as it were the productive investigation of sensor- derived information but moreover permits for the customization of the system's highlights to suit the different needs of diverse rural settings. Subsequently, the system's flexibility loans itself to optimizing yields and cultivating feasible nourishment generation hones, subsequently contributing to the overarching objective of guaranteeing nourishment security and natural stewardship.

Keywords— Smart System, Seed Germination Prediction, AI and IoT Integration, Agriculture, Machine Learning Models, Real-time Data, Crop Management, Scalable Cloud Platform, Customizable Design, Sustainable Food Production.