Smart Agricultural Micro-Insurance Solution through Machine Learning and Remote Sensing

Abstract
In this study we use the combination of satellite imagery coupled with Image Processing and parallel computing techniques to predict agricultural yield of various crops such as Rice and Potato, monitor the health of those crops in real-time, perform risk profiling and pricing and carry out Time-Series analysis using various agricultural indices and Machine Learning techniques. We also show correlations between ground yield data with remotely sensed satellite data. The study was carried out in four agriculture-based regions in Bangladesh. With our results, we introduce the concepts of micro insurance to smallholder farmers and help them become debt-free through a profitable business model. Automation and minimum human capital requirement drive down costs of operating insurance thus making our product highly scalable and service efficient.
Description
Keywords
Citation
Department Name
Electrical and Computer Engineering
Publisher
North South University
Printed Thesis
DOI
ISSN
ISBN