Title

Democratization of AI to small scale farmers, albeit food harvesting citizen data scientists, that are at the bottom of the economic pyramid

Publication Date

1-1-2020

Document Type

Conference Proceeding

Department

Computer Engineering

Publication Title

Intelligent Human Systems Integration 2020: Proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020): Integrating People and Intelligent Systems, February 19-21, 2020, Modena, Italy

Editor

Tareq Ahram, Waldemar Karwowski, Alberto Vergnano, Francesco Leali, Redha Taiar

DOI

10.1007/978-3-030-39512-4_55

First Page

348

Last Page

358

Abstract

Climate change is impacting milk production worldwide. For instance, increased heat stress in cows is causing average-sized dairy farms losing thousands of milk gallons each year; drastic climate change, especially in developing countries, pushing small farmers, farmers with less than 10 to 25 cattle, below the poverty line and is triggering suicides due to economic stress and social stigma. It’s profoundly clear that current dairy agriculture practices are falling short to counter the impacts of climate change. What we need are innovative and intelligent dairy farming techniques that employ best of traditional practices with data infused insights to counter negative effects of climate change. To achieve innovative and intelligent dairy farming techniques, we need to disseminate state of art data science to masses. In other word, provide the state of art data science algorithms to every food harvesting citizen data scientist, farmer. The democratization of artificial intelligence to farmers, importantly, is not only empowers farmers to understand the patterns and signatures of climate change but also provides the ability to forecast the impending climate change adverse events and recommends data driven insights to counter the negative effects of climate change. With the availability of new data tools, farmers can not only improve their standard of life but also conquer, importantly, perennial “climate change related suicide” issue. It’s our staunch believe that the gold standard for the success of the democratization of artificial intelligence is no farmer life loss due to negative effects of climate change. In this paper, we propose an innovative machine learning Sensor edge approach that considers the impact of climate change and develops artificial intelligent (AI) models that is validated globally but enables localized solution to thwart impacts of climate change. The paper presents prototyping dairy IoT sensor solution design as well as its application and certain experimental results.

Keywords

Climate Change, Climate change related suicides, Climate models, Decision tree, Edge analytics, Embedded device, Farmer suicides, Hanumayamma dairy IoT sensor, Internet of Things (IoT), Machine Learning, Regression analysis

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