Patala, N.Kadyamatimba, A.Manganyi, Smile2024-10-042024-10-042024-09-06Manganyi, S. 2024. Framework for smart sustainable farming using the artificial intelligence of things in South Africa: A case of small-scale plant farming. . .https://univendspace.univen.ac.za/handle/11602/2720M. Com (Business Information Systems)Department of Business Information SystemsThe 4.0 green revolution in agriculture, also known as "smart farming," combines agricultural methodologies with technology such as sensors, actuators, information, and communication technology (ICT), the Internet of Things (IoT), robotics, and drones, to achieve desired production efficiencies at controlled costs. It is considered an important factor in disseminating farming to small-scale plant farmers across the globe. Even though some large-scale farmers in South Africa have previously embraced Artificial Intelligence of Things to support their agricultural processes. Small-scale plant farmers are still unable to operate due to some circumstances, such as inappropriate skills, knowledge, and services. There is no proper framework to assist small-scale plant farmers in the Vhembe district of Limpopo to develop a quality and smart farming environment. This study focused on discovering factors that influence the implementation of Artificial Intelligence of Things (AIoT) systems towards small-scale plant farmers and its challenges. The researcher collected data from 10 participants through interviews and guided by a structured interview guide. The collected data was transcribed using Microsoft word and analysed through thematic framework analysis using ATLAS ti. The findings of this study intended to bring new insights and guidelines to small-scale plant farmers on the best method to utilise AIoT tools and skills they would require throughout. The study recommended that the government must assist the small-scale farmers with funding, maintenance and awareness towards the automation of their farms. The study found that AIoT is an essential tool for sustaining farming. The findings revealed that the effective adoption of AIoT shall improve productivity and sustainability for small-scale farmers to serve the globe without relying solely on commercial farms. Eventually, this study proposed a framework for smart sustainable farming specified at integrating farming practices, technologies and its stakeholders based on the UTAUT model.1 online resource (xi, 107 leaves) : color illustrationsenUniversity of VendaArtificial intelligence of ThingsUCTDSmart farmingArtificial Intelligence (AI)Internet of ThingsSmall-scale plant farmersDissertationManganyi S. Framework for smart sustainable farming using the artificial intelligence of things in South Africa: A case of small-scale plant farming. []. , 2024 [cited yyyy month dd]. Available from:Manganyi, S. (2024). <i>Framework for smart sustainable farming using the artificial intelligence of things in South Africa: A case of small-scale plant farming</i>. (). . Retrieved fromManganyi, Smile. <i>"Framework for smart sustainable farming using the artificial intelligence of things in South Africa: A case of small-scale plant farming."</i> ., , 2024.TY - Dissertation AU - Manganyi, Smile AB - The 4.0 green revolution in agriculture, also known as "smart farming," combines agricultural methodologies with technology such as sensors, actuators, information, and communication technology (ICT), the Internet of Things (IoT), robotics, and drones, to achieve desired production efficiencies at controlled costs. It is considered an important factor in disseminating farming to small-scale plant farmers across the globe. Even though some large-scale farmers in South Africa have previously embraced Artificial Intelligence of Things to support their agricultural processes. Small-scale plant farmers are still unable to operate due to some circumstances, such as inappropriate skills, knowledge, and services. There is no proper framework to assist small-scale plant farmers in the Vhembe district of Limpopo to develop a quality and smart farming environment. This study focused on discovering factors that influence the implementation of Artificial Intelligence of Things (AIoT) systems towards small-scale plant farmers and its challenges. The researcher collected data from 10 participants through interviews and guided by a structured interview guide. The collected data was transcribed using Microsoft word and analysed through thematic framework analysis using ATLAS ti. The findings of this study intended to bring new insights and guidelines to small-scale plant farmers on the best method to utilise AIoT tools and skills they would require throughout. The study recommended that the government must assist the small-scale farmers with funding, maintenance and awareness towards the automation of their farms. The study found that AIoT is an essential tool for sustaining farming. The findings revealed that the effective adoption of AIoT shall improve productivity and sustainability for small-scale farmers to serve the globe without relying solely on commercial farms. Eventually, this study proposed a framework for smart sustainable farming specified at integrating farming practices, technologies and its stakeholders based on the UTAUT model. DA - 2024-09-06 DB - ResearchSpace DP - Univen KW - Artificial intelligence of Things KW - Smart farming KW - Artificial Intelligence (AI) KW - Internet of Things KW - Small-scale plant farmers LK - https://univendspace.univen.ac.za PY - 2024 T1 - Framework for smart sustainable farming using the artificial intelligence of things in South Africa: A case of small-scale plant farming TI - Framework for smart sustainable farming using the artificial intelligence of things in South Africa: A case of small-scale plant farming UR - ER -