Affordable Artificial Intelligence -- Augmenting Farmer Knowledge with AI

• URL: http://arxiv.org/abs/2303.06049v1
• Date: Sat, 4 Mar 2023 02:29:52 GMT
• Title: Affordable Artificial Intelligence -- Augmenting Farmer Knowledge with AI
• Authors: Peeyush Kumar, Andrew Nelson, Zerina Kapetanovic, and Ranveer Chandra
• Abstract summary: This article presents the AI technology for predicting micro-climate conditions on the farm. This publication is the fifth in the E-agriculture in Action series, launched in 2016 and jointly produced by FAO and ITU. It aims to raise awareness about existing AI applications in agriculture and to inspire stakeholders to develop and replicate the new ones.
• Score: 1.9992810351494297
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Farms produce hundreds of thousands of data points on the ground daily. Farming technique which combines farming practices with the insights uncovered in these data points using AI technology is called precision farming. Precision farming technology augments and extends farmers' deep knowledge about their land, making production more sustainable and profitable. As part of the larger effort at Microsoft for empowering agricultural labor force to be more productive and sustainable, this paper presents the AI technology for predicting micro-climate conditions on the farm. This article is a chapter in publication by Food and Agriculture Organization of the United Nations and International Telecommunication Union Bangkok, 2021. This publication on artificial intelligence (AI) for agriculture is the fifth in the E-agriculture in Action series, launched in 2016 and jointly produced by FAO and ITU. It aims to raise awareness about existing AI applications in agriculture and to inspire stakeholders to develop and replicate the new ones. Improvement of capacity and tools for capturing and processing data and substantial advances in the field of machine learning open new horizons for data-driven solutions that can support decision-making, facilitate supervision and monitoring, improve the timeliness and effectiveness of safety measures (e.g. use of pesticides), and support automation of many resource-consuming tasks in agriculture. This publication presents the reader with a collection of informative applications highlighting various ways AI is used in agriculture and offering valuable insights on the implementation process, success factors, and lessons learnt.

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