Cover image for Emerging Technologies for Developing Countries 5th EAI International Conference, AFRICATEK 2022, Bloemfontein, South Africa, December 5-7, 2022, Proceedings
Title:
Emerging Technologies for Developing Countries 5th EAI International Conference, AFRICATEK 2022, Bloemfontein, South Africa, December 5-7, 2022, Proceedings
Author:
Masinde, Muthoni. editor. (orcid)
ISBN:
9783031358838
Edition:
1st ed. 2023.
Physical Description:
XII, 225 p. 130 illus., 106 illus. in color. online resource.
Series:
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 503
Contents:
Education in the 4IR Era -- Reinforcement Learning in Education: A Multi-Armed Bandit Approach -- Assessing Institutional Readiness for the Fourth Industrial Revolution: Using Learning Analytics to Improve Student Experiences -- M-learning during COVID-19: A Systematic Literature Review -- Opportunities for driving Efficiencies and Effectiveness -- Archiving 4.0: Dataset Generation and Facial recognition of DRC political Figures Using Machine Learning -- On the Machine Learning Models To Predict Town-scale Energy Consumption In Burkina Faso -- Application of Latent Dirichlet Allocation topic model in identifying 4IR Research Trends -- A conceptual model for the digital inclusion of SMMEs in the Informal Sector in South Africa - The use of Blockchain Technology to access loans -- Key 4IR Baseline Architectures -- Multiple Robotic Formation Control Based on Differential Flatness -- AComparison of Publish-Subscribe and Client-Server Models for Streaming IoT Telemetry data -- Fourth industrial revolution research outputs in Africa: A bibliometric review -- Modelling DDoS Attacks in IoT Networks using Machine Learning -- Application of 4IR in Environment and Agriculture Monitoring -- Towards a microservice-based middleware for a multi-hazard early warning system -- Indigenous Knowledge mobile-based application that quantifies farmers' season predictions with the help of scientific knowledge -- Weed Identification in Plant Seedlings Using Convolutional Neural Networks.
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