Emerging Technologies for Developing Countries
Springer International Publishing (Verlag)
978-3-031-35882-1 (ISBN)
The 14 full papers included in this book were carefully reviewed and selected from 24 submissions.
This book constitutes the refereed conference proceedings of the 5th International Conference on Emerging Technologies for Developing Countries, AFRICATEK 2022, held in Bloemfontein, South Africa, in December 5-7, 2022.
The 14 full papers included in this book were carefully reviewed and selected from 24 submissions. They were organized in topical sections as follows: answer set programming; Education in the 4IR Era, Opportunities for driving Efficiencies and Effectiveness, Key 4IR Baseline Architectures, Application of 4IR in Environment and Agriculture Monitoring.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 ConvolutionalNeural Networks.
| Erscheinungsdatum | 07.07.2023 |
|---|---|
| Reihe/Serie | Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering |
| Zusatzinfo | XII, 225 p. 130 illus., 106 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 373 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Netzwerke |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Informatik ► Weitere Themen ► Hardware | |
| Schlagworte | Artificial Intelligence • Autonomous learning • Bibliometric Review • Blockchain technology • Computer Science • convolutional neural networks • Fourth industrial revolution (4IR) • Indigenous knowledge • intrusion/anomaly detection and malware mitigation • Latent Dirichlet Allocation (LDA) • microservice-based middleware • Middleware • M-learning during COVID-19 • Mobile Robotics Formation Control • multi-hazard early warning system • Small, Medium and Micro Enterprises (SMMEs) • topic model • Weed Identification |
| ISBN-10 | 3-031-35882-1 / 3031358821 |
| ISBN-13 | 978-3-031-35882-1 / 9783031358821 |
| Zustand | Neuware |
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