Introduction
An extensive and forward-looking examination of how AI, IoT, and remote sensing technologies are reshaping environmental sustainability, industrial innovation, and data-driven decision-making. Applied Artificial Intelligence in Data Science, Cloud Computing and IoT Frameworks (Volume 5) demonstrates how intelligent systems powered by satellite imagery, UAVs, sensor networks, and geospatial analytics can monitor ecosystems, predict climate dynamics, optimize industrial operations, and support global sustainability efforts.
The volume explores AI-based pollution detection, biodiversity assessment, climate and CO₂ forecasting, and geospatial approaches to deforestation monitoring. It further examines the rise of Industry 6.0, evaluates forecasting model performance, and highlights advanced technologies such as Generative Adversarial Networks (GANs) for image enhancement, intelligent meteorological analysis, and AI applications in higher education. Ethical considerations, data governance, and digital security challenges are addressed to ensure responsible deployment of intelligent systems.
Key Features
- - Showcases real-world case studies demonstrating AI, IoT, and remote sensing integration for sustainable development.
- - Evaluates forecasting models, decision-support systems, and geospatial frameworks for environmental analytics.
- - Highlights applications of advanced algorithms such as GANs for image enhancement and climate data interpretation.
- - Addresses ethical, governance, and data security challenges in intelligent environmental systems.
Target Readership:
Researchers, practitioners, and graduate students in remote sensing, environmental science, AI, and sustainable development.