AI Recommender System With ML for Agricultural Research

Peters, Debra P. C.; Savoy, H.; Ramirez, Geovany A.; Huang, Haitao

doi:10.1109/mitp.2020.2986125

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…However, the development and implementation of AI also raises ethical concerns (UNESCO 2021). The impact of AI on society and the environment needs to be evaluated and managed to ensure that the benefits of AI are realized while minimizing the risks [43]. In conclusion, AI has the potential to transform several sectors of the economy including governance, economy, agriculture and judiciary.…”

Section: Fig 2 Ai-powered Toolboxmentioning

confidence: 99%

The AI vantage: an exposition of global dynamics

Kishor,

Patle,

Bhojane

2023

J. mechatron., artif. intell., eng.

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Over the past few years, there has been a growing interest in this field of Artificial Intelligence (AI). This review paper aims to examine the extent to which AI has been adopted across various domains in different regions of the world. Specifically, this study seeks to explore the effectiveness of AI in areas such as banking, governance, judiciary, and agriculture. While AI’s impact on these areas has been studied before, this research focuses on aspects that have not been given much needed attention so far. The study will begin by offering an overview of AI’s development from a regional perspective, analyzing 63 articles from leading journals and institutions to identify the most commonly used terminologies, theories, and technologies. The increasing computational power has played a crucial role in the advancement of AI. However, the role of AI in governance, judiciary, and legislature system has not been explored in depth in previous research. Furthermore, most studies tend to focus on single domain, whereas this paper aims to examine several domains and their relationship to AI. The study presents several AI-driven techniques, including Deep Neural Net (DNN), Artificial Neural Net (ANN), Candlestick Plots, Natural Language Processing (NLP), Explainable Deep Neural Net (xDNN), Attentional Maps, Digital Inventory, Deep Learning among others, that can be applied to enhance society’s performance in different domains. The research also delves deeper into the judiciary domain, proposing specific AI techniques that could be useful in this field. Additionally, tables summarizing different AI tactics relevant to each domain are presented.

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Section: Fig 2 Ai-powered Toolboxmentioning

confidence: 99%

The AI vantage: an exposition of global dynamics

Kishor,

Patle,

Bhojane

2023

J. mechatron., artif. intell., eng.

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“…, 2020). Some of them studied the implementation process in large enterprises such as multinational companies (Malik et al , 2020), while others focused on key areas such as medical care (Benaich and Hogarth, 2020), agriculture (Peters et al. , 2020), education (Knox, 2020) and human resources (Malik et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Some researchers have focused on studying the influence of intelligent products on employees and performance (Kaare and Otto, 2015;Krolczyk et al, 2020), competition (Acemoglu and Restrepo, 2020;Fleming, 2019) and collaboration (F€ ugener et al, 2019;Seeber et al, 2020). Some of them studied the implementation process in large enterprises such as multinational companies (Malik et al, 2020), while others focused on key areas such as medical care (Benaich and Hogarth, 2020), agriculture (Peters et al, 2020), education (Knox, 2020) and human resources (Malik et al, 2020). However, these studies overlooked SMEs in China, especially those with limited capabilities to carry out intelligent transformation in lessdeveloped regions.…”

Section: Introductionmentioning

confidence: 99%

How to survive in the age of artificial intelligence? Exploring the intelligent transformations of SMEs in central China

Wang

Fan³

et al. 2021

IJOEM

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PurposeThe purpose of the research is to explore how small and medium enterprises (SMEs) in central China achieve intelligent transformation through the use of artificial intelligence (AI). Because of unequal resource allocation, constraints on the intelligent transformation of SMEs in central China are different from those in economically and technologically well-developed coastal provinces. Hence, the authors focus on SMEs in central China to identify drivers of and barriers to intelligent transformation.Design/methodology/approachThe interview data were collected from 66 SMEs across 20 industries in central China. To verify the validity of the data collection method, the authors used two methods to control for retrospective bias: multi-level informants and enterprises' AI project application materials (Wei and Clegg, 2020). The final data were validated without conflicts. Next, the authors cautiously followed a two-step approach recommended by Venkatesh et al. (2010) and used NVivo 11.0 to analyze the collected text data.FindingsSMEs in central China are enthusiastic about intelligent transformation while facing both internal and external pressures. SMEs need to pay attention to both internal (enterprise development needs, implementation cost, human resources and top management involvement) and external factors (external market pressure, convenience of AI technology and policy support) and their different impacts on intelligent transformation. However, constrained by limited resources, SMEs in central China have been forced to take a step-by-step intelligent transformation strategy based on their actual needs with the technological flexibility method in the short term.Originality/valueConsidering the large number of SMEs and their importance in promoting China's economic development and job creation (SME Bureau of MIIT, 2020), more research on SMEs with limited resources is needed. In the study, the authors confirmed that enterprises should handle “social responsibility” carefully because over-emphasizing it will hinder intelligent transformation. However, firms should pay attention to the role of executives in promoting intelligent transformation and make full use of policy support to access more resources.

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