2019
DOI: 10.18034/apjee.v6i2.542
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How Artificial Intelligence Improves Agricultural Productivity and Sustainability: A Global Thematic Analysis

Abstract: In the face of the agricultural sector's challenges, food security with an increasing human population and high demand for food is a significant problem. Traditional methods used by farmers have not been sufficient to meet the food requirements of the growing population. As a result, the agricultural sector has begun to deploy artificial intelligence to meet the demand for food and sustainability. This study was conducted to examine how AI improves farmers' productivity and sustainability. Data were analyzed u… Show more

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Cited by 27 publications
(10 citation statements)
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“…Researcher (Paruchuri, 2019) used the ML approaches for the detection of diabetes. Various researchers used the ML for detecting the diabetes (Habibi et al, 2015;Razavian et al, 2015;Meng et al, 2013;Ozcift et al, 2011;Vadlamudi, 2019). Some of the most popular ML algorithms that are used for detecting the diabetes are given below.…”
Section: Resultsmentioning
confidence: 99%
“…Researcher (Paruchuri, 2019) used the ML approaches for the detection of diabetes. Various researchers used the ML for detecting the diabetes (Habibi et al, 2015;Razavian et al, 2015;Meng et al, 2013;Ozcift et al, 2011;Vadlamudi, 2019). Some of the most popular ML algorithms that are used for detecting the diabetes are given below.…”
Section: Resultsmentioning
confidence: 99%
“…Modern-day customers in financial services prefer user-specific services and products that fit and predict their ever-changing desires, needs, and behaviors (Vadlamudi, 2019). Over twenty percent of small and medium-sized financial institutions have lost clients because they don't offer clients personalized products and services that prioritize clients' experiences.…”
Section: Targeting and Predictionmentioning
confidence: 99%
“…These sorts of sensors are viewed as a decent decision in light of its cost viability, its assortment of utilizations and convenience and customizability. Basic uses are tank checking, splash distance estimation (e.g., blast tallness and width control to perform uniform spray inclusion, object discovery, and crash evasion), and observing yield covering (Dvorak et al, 2016;Alvarez et al, 2016;Vadlamudi, 2019). At the point when joined with a camera, these sensors are utilized for weed identification, where the statures of plants are distinguished utilizing the ultrasonic sensors and the camera decides the weed and harvest inclusion.…”
Section: Literature Reviewmentioning
confidence: 99%