A Machine Learning-Based Mobile Chatbot for Crop Farmers

Usip, Patience U.; Udo, Edward N.; Asuquo, Daniel E.; James, Otobong R.

doi:10.1007/978-3-031-22950-3_15

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…Usip et al (2022) [72] Utilizes agricultural technology and knowledge propagation, naming the government as an ideal client for obtaining input on governance through agricultural services, to enhance agricultural knowledge availability and production with a mobile chatbot created exclusively for crop producers.…”

Section: Ai Collaboration For Agricultural Advancements and Informed ...mentioning

confidence: 99%

Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review

Al Naqbi,

Bahroun,

Ahmed

2024

Sustainability

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In this review, utilizing the PRISMA methodology, a comprehensive analysis of the use of Generative Artificial Intelligence (GAI) across diverse professional sectors is presented, drawing from 159 selected research publications. This study provides an insightful overview of the impact of GAI on enhancing institutional performance and work productivity, with a specific focus on sectors including academia, research, technology, communications, agriculture, government, and business. It highlights the critical role of GAI in navigating AI challenges, ethical considerations, and the importance of analytical thinking in these domains. The research conducts a detailed content analysis, uncovering significant trends and gaps in current GAI applications and projecting future prospects. A key aspect of this study is the bibliometric analysis, which identifies dominant tools like Chatbots and Conversational Agents, notably ChatGPT, as central to GAI’s evolution. The findings indicate a robust and accelerating trend in GAI research, expected to continue through 2024 and beyond. Additionally, this study points to potential future research directions, emphasizing the need for improved GAI design and strategic long-term planning, particularly in assessing its impact on user experience across various professional fields.

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Section: Ai Collaboration For Agricultural Advancements and Informed ...mentioning

confidence: 99%

Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review

Al Naqbi,

Bahroun,

Ahmed

2024

Sustainability

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“…Intelligent system, chatbot Technical characteristics (algorithm, type of system) [13] Website, chatbot and Google API Technical characteristics (algorithm, type of system) [6] Chatbot, system Technical characteristics (algorithm, type of system) [7] Chatbot, e-commerce Technical characteristics (algorithm, type of system) [14] Chatbot, machine learning Technical characteristics (algorithm, type of system) [15] Mobile and web application Technical characteristics (algorithm, type of system) [16] Mobile and web application Technical characteristics (algorithm, type of system) [17] Chatbot and IBM service Technical characteristics (algorithm, type of system) [18] Chatbot Technical characteristics (algorithm, type of system) [19] Chatbot Technical characteristics (algorithm, type of system) [20] Chatbot Technical characteristics (algorithm, type of system) [21] Chatbot Technical characteristics (algorithm, type of system) [22] Chatbot Technical characteristics (algorithm, type of system) [23] Chatbot Technical characteristics (algorithm, type of system) [24] Chatbot Technical characteristics (algorithm, type of system) [25] Chatbot Technical characteristics (algorithm, type of system) [26] Chatbot Technical characteristics (algorithm, type of system) [27] Chatbot Technical characteristics (algorithm, type of system) [28] Chatbot Technical characteristics (algorithm, type of system) [29] Chatbot Technical characteristics (algorithm, type of system) [30] Chatbot Technical characteristics (algorithm, type of system) [31] Chatbot Technical characteristics (algorithm, type of system) [32] Chatbot Technical characteristics (algorithm, type of system) [33] Chatbot, customer service Chatbot-customer relationship [32] Chatbot Technical characteristics (algorithm, type of system) [34] Chatbot, dialogues Technical characteristics (algorithm, type of system) [35] Chatbot, customer service Chatbot-customer relationship [8] Chatbot, artificial intelligence language Technical characteristics (algorithm, type of system) [36] www.ijacs...…”

Section: According To Evaluated Aspects According To Conditioning Fac...mentioning

confidence: 99%

Implementation of a Web System with Chatbot Service for Sales Management - A Review

Barrantes-Saucedo,

García-Leandro,

Iparraguirre-Villanueva

et al. 2023

IJACSA

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The objective of the research was to analyze various researches about web systems with chatbot service in the sales management process between the years 2018-2022, employing four databases, such as: S cience Direct, Taylor & Francis, IEEE Xplore and S pringer. The PRIS MA methodology was applied, selecting 60 manuscripts where the year of highest publication was 2021 (35%), leading the US A as the country with the highest scientific production equivalent to 23.33%; in addition, the type of research that predominated were scientific articles with the percentage value of 70% and being entirely in the English language. Finally, it was found that there are two relevant components regarding the implementation of a web system with chatbot service for S ales Management, the first are the evaluated aspects, explained as those that focus on the analysis of the intelligent system, chatbot, website, Google API, ecommerce, machine learning, IBM service, mobile application, web, relationship with customer service, sales management, digital transformation, information system, algorithm and innovation and as the second component, according to the conditional factors refers to the context in which the use of chatbot in sales management occurs, being such technical features as algorithm, type of system, chatbot-customer relationship, sales and innovation and sales-system relationship.

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