Artificial Intelligence Tools and Applications in Embedded and Mobile Systems

Selected Papers from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), 24-25 November 2022, Arusha, Tanzania
1. Auflage 2024
ISBN: 978-3-031-56575-5
Verlag: Springer

Buch, Englisch, 250 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Progress in IS

The emergence of Artificial Intelligence (AI) has had a tremendous impact on embedded and mobile systems. This book presents a diverse collection of papers that showcase cutting-edge research and practical applications of AI in this field. The peer-reviewed research articles stem from the First International Conference on Embedded and Mobile Systems (ICTA-EMOS), which was held on November 24th – 25th, 2022, in Arusha, Tanzania, East Africa. They demonstrate the breadth and depth of AI’s impact across various domains, exploring topics such as healthcare advances, transportation optimization, sustainable solutions, and business and process optimization.

Zielgruppe

Research

Autoren/Hrsg.

Marx Gómez, Jorge

Elikana Sam, Anael

Godfrey Nyambo , Devotha

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik

Inhaltsverzeichnis

Improving Robustness of Optimized Parameters Gradient Tree Boosting for Crime Forecast Model.- Evidence Based Practices On Co-Operative Societies Information Record Management.- Influence of Microservice Design Patterns for Data Science Workflows.- A systematic literature review toward standardization of business rules discovery in the context of Process Mining.- Contextual Multi-view Graph Community Detection using Graph Neural Networks.- Feature Selection Approach To Improve Malaria Diagnosis Model's Performance For High And Low Endemic Areas Of Tanzania.- 2-Stage Hybrid Ensemble Based Heterogeneous Committee Machine for Improving Soil Fertility Status Prediction Performance.- Convolutional Neural Network deep learning model for early detection of streak virus and lethal necrosis in maize: A case of Northern-highlands, Tanzania.- Object Detection Model for Poultry Diseases Diagnostics.- Machine Learning Model for Predicting Construction Project Success in Tanzania.- Improved MedicalImaging Transfer learning through the conflation of domain features.- Determining Emotion Intensities From Audio Data Using A Convolutional Neural Network.- Machine Learning Based Forward Collision Avoidance System: A Case study for the Kayoola EVS.- Visualizing Outlier Explanations for Mixed-type Data.- A Dolutegravir-Associated Hyperglycemia Computational Prediction Tool for People Living with HIV in Uganda.- Extraction of Numerical Facts from German Texts to enrich Internal Audit Data.- From Process Mining to Enterprise Mining.- CNN With Attention Guided Concatenation For Improved Image Restoration.- A Contribution to the Development of Sustainable Target Value Streams with Machine Learning Considering Material Flow Cost.- Mask R-CNN model for banana diseases segmentation.- The artificial neural network-based smart number plate for vehicles with real-time traffic signs recognition and notification.- Intermodal matching algorithm including public transportation and ride-hailing.- A Machine Learning-Based IoT Environmental Monitoring Platform for Data Centres

Über Autor(innen)

Prof. Jorge Marx Gómez is a full Professor and Chair of Business Information Systems at Carl von Ossietzky University, Oldenburg, Germany. His research interests include very large business applications, business information systems, federated ERP systems, business intelligence, data warehousing, interoperability and environmental management information systems.

Prof. Anael Sam is an Associate Professor of Information Technology and Chair of the Smart Electronics Systems Development (SeSDev) research group at the Nelson Mandela African Institution of Science and Technology, Tanzania. His research interests include cyber security, electronics engineering, mobile and wireless communication systems, and software quality assurance engineering.


Dr. Devotha Godfrey Nyambo is a Lecturer and Head of Artificial Intelligence and Complexity Sciences at the Nelson Mandela African Institution of Science and Technology, Tanzania. Her research interests include appliedmachine learning, multi-agent systems, modeling and simulations, and agricultural informatics.