Related papers: Adoption of ICT innovations in the agriculture sector in Africa: A Systematic Literature Review

Adoption of ICT innovations in the agriculture sector in Africa: A Systematic Literature Review

URL: http://arxiv.org/abs/2006.13831v1
Date: Wed, 24 Jun 2020 16:03:27 GMT
Title: Adoption of ICT innovations in the agriculture sector in Africa: A Systematic Literature Review
Authors: Claudia Ayim, Ayalew Kassahun, Bedir Tekinerdogan, Chris Addison
Abstract summary: This study aims to explore ICT innovations in the agriculture sector of Africa. The main ICT technologies adopted are text and voice-based services targeting mobile phones. The adoption of the services is constrained by poor technological infrastructure, inappropriate ICT policies and low capacity levels of users.
Score: 3.0969191504482243
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: According to the latest World Economic Forum report, about 70% of the African population depends on agriculture for their livelihood. This makes agriculture a critical sector within the African continent. Nonetheless, agricultural productivity is low and food insecurity is still a challenge. This has in recent years led to several initiatives in using ICT (Information Communication Technology) to improve agriculture productivity. This study aims to explore ICT innovations in the agriculture sector of Africa. To achieve this, we conducted a SLR (Systematic Literature Review) of the literature published since 2010. Our search yielded 779 papers, of which 23 papers were selected for a detailed analysis following a detailed exclusion and quality assessment criteria. The analysis of the selected papers shows that the main ICT technologies adopted are text and voice-based services targeting mobile phones. The analysis also shows that radios are still widely used in disseminating agriculture information to rural farmers, while computers are mainly used by researchers. Though the mobile-based services aimed at improving access to accurate and timely agriculture information, the literature reviews indicate that the adoption of the services is constrained by poor technological infrastructure, inappropriate ICT policies and low capacity levels of users, especially farmers, to using the technologies. The findings further indicate that literature on an appropriate theoretical framework for guiding ICT innovations is lacking.

Related papers

LoRa Communication for Agriculture 4.0: Opportunities, Challenges, and Future Directions [40.08908132533476]
The emerging field of smart agriculture leverages the Internet of Things (IoT) to revolutionize farming practices. This paper investigates the transformative potential of Long Range (LoRa) technology as a key enabler of long-range wireless communication for agricultural IoT systems.
arXiv Detail & Related papers (2024-09-17T13:55:44Z)
Application of Machine Learning in Agriculture: Recent Trends and Future Research Avenues [6.0460261046732455]
Food production is a vital global concern and the potential for an agritech revolution through artificial intelligence (AI) remains largely unexplored. This paper presents a comprehensive review focused on the application of machine learning (ML) in agriculture, aiming to explore its transformative potential in farming practices and efficiency enhancement.
arXiv Detail & Related papers (2024-05-23T17:53:31Z)
On the Opportunities of Green Computing: A Survey [80.21955522431168]
Artificial Intelligence (AI) has achieved significant advancements in technology and research with the development over several decades. The needs for high computing power brings higher carbon emission and undermines research fairness. To tackle the challenges of computing resources and environmental impact of AI, Green Computing has become a hot research topic.
arXiv Detail & Related papers (2023-11-01T11:16:41Z)
Web of Things and Trends in Agriculture: A Systematic Literature Review [0.4640835690336651]
The main aim of this study is about understanding and providing a growing and existing research content, issues, and directions for the future regarding WOT-based agriculture. A taxonomy of WOT-base agriculture application domains has also been presented in this study.
arXiv Detail & Related papers (2023-06-15T12:20:30Z)
Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward [60.43248801101935]
This article gives a bird's eye view of the essential scientific tools and approaches informing and supporting the transition from raw EO data to usable EO-based information. We cover the impact of (i) Computer vision; (ii) Machine learning; (iii) Advanced processing and computing; (iv) Knowledge-based AI; (v) Explainable AI and causal inference; (vi) Physics-aware models; (vii) User-centric approaches; and (viii) the much-needed discussion of ethical and societal issues related to the massive use of ML technologies in EO.
arXiv Detail & Related papers (2023-05-15T07:47:24Z)
Empowering Agrifood System with Artificial Intelligence: A Survey of the Progress, Challenges and Opportunities [86.89427012495457]
We review how AI techniques can transform agrifood systems and contribute to the modern agrifood industry. We present a progress review of AI methods in agrifood systems, specifically in agriculture, animal husbandry, and fishery. We highlight potential challenges and promising research opportunities for transforming modern agrifood systems with AI.
arXiv Detail & Related papers (2023-05-03T05:16:54Z)
Citation Trajectory Prediction via Publication Influence Representation Using Temporal Knowledge Graph [52.07771598974385]
Existing approaches mainly rely on mining temporal and graph data from academic articles. Our framework is composed of three modules: difference-preserved graph embedding, fine-grained influence representation, and learning-based trajectory calculation. Experiments are conducted on both the APS academic dataset and our contributed AIPatent dataset.
arXiv Detail & Related papers (2022-10-02T07:43:26Z)
Role of Information and ICTs as Determinants of Farmer's Adaptive Capacity to Climate Risk: An Empirical Study From Haryana, India [0.0]
We use path analysis technique using the lavaan package in RStudio to empirically test the role of information. We find that information is a direct and significant contributor to enhancing farmers' adaptive capacity. We take an ensemble view of ICTs operationalized using ICT ecosystem and find significant interlinkages between information, technology and the ICT ecosystem.
arXiv Detail & Related papers (2021-08-22T16:00:06Z)
Machine Learning Challenges and Opportunities in the African Agricultural Sector -- A General Perspective [0.0]
The agricultural sector is vital for African economies. improving yields, mitigating losses, and effective management of natural resources are crucial in a climate change era. The purpose of this paper is to contextualize and discuss barriers to ML-based solutions for African agriculture.
arXiv Detail & Related papers (2021-07-11T17:48:23Z)
Determinants of ICT Adoption Among Small Scale Agribusiness Enterprises In Somalia [0.8793721044482612]
ICT has made significant contributions to agribusiness because it allows enterprises to manage their operations. The literature has indicated ICT adoption among small-scale agribusiness enterprises in Somalia is not fully understood. This study investigates the adoption of ICT among small-scale agribusiness enterprises in Somalia.
arXiv Detail & Related papers (2021-02-24T11:25:15Z)
Learning from Data to Optimize Control in Precision Farming [77.34726150561087]
Special issue presents the latest development in statistical inference, machine learning and optimum control for precision farming. Satellite positioning and navigation followed by Internet-of-Things generate vast information that can be used to optimize farming processes in real-time.
arXiv Detail & Related papers (2020-07-07T12:44:17Z)

This list is automatically generated from the titles and abstracts of the papers in this site.