Software Engineering in IoT, Big Data, Cloud and Mobile Computing

Software Engineering Meets the Intelligent Edge

As everyday devices, cloud platforms, and mobile services become increasingly interconnected, software engineering faces new demands for reliability, scalability, and intelligence. This edited volume from Springer’s Studies in Computational Intelligence series gathers 17 peer-selected papers from the International Semi-Virtual Workshop on Software Engineering in IoT, Big Data, Cloud and Mobile Computing (SE-ICBM 2020). The contributions reflect a focused effort to understand how software engineering practices can be adapted and applied across these rapidly converging fields.

Inside the Collection

The papers explore a range of real-world applications and emerging techniques, including:

• Variability modeling in software product lines
• Big data analytics for supply chain performance
• Smart U-health care systems and cloud-based health services
• Video translation using optical character recognition
• Predicting fire ignition factors with artificial neural networks
• Driver drowsiness detection through heart rate variability
• Psychological steady state variations from auditory stimulation
• Flipped learning and unplugged activities in data structures
• Agent architecture for context-aware services
• Blockchain-based transaction management for IoT
• Plant growth monitoring and smart cattle shed systems using LoRa
• Business model innovation for sustainable mobile services
• Deep convolutional neural networks for product image analysis
• Cloud monitoring with open-source solutions
• AI and EduTech trends in lifelong education
• Optimal public cloud service provider selection for microservices

Approaches That Move Beyond Theory

Several chapters stand out for their hands-on orientation. For instance, the development of plant growth measurement systems and smart cattle shed monitoring demonstrates how low-power wide-area networks like LoRa can support practical agricultural IoT. Similarly, the implementation of a video translation system using OCR shows how existing technologies can be combined to solve real language accessibility problems. The blockchain-as-a-service software proposal for IoT security illustrates how distributed ledger concepts can be integrated into existing IoT networks without reinventing the wheel.

A Volume for Researchers and Practitioners

This book is intended for researchers, graduate students, and software engineers who want to stay current with applied research in computational intelligence and its intersection with IoT, big data, cloud, and mobile computing. The papers are written by contributors from academia and industry, offering a mix of systematic reviews, experimental studies, and system designs. While some chapters assume familiarity with basic concepts in machine learning, IoT, or software architecture, the overall presentation remains accessible to advanced readers seeking concrete examples and recent results.

What Makes This Springer Edition Valuable

As part of the Studies in Computational Intelligence series, this volume benefits from Springer’s rigorous editorial standards and wide indexing. The series is indexed by SCOPUS, DBLP, WTI Frankfurt eG, zbMATH, and SCImago, and all books are submitted for consideration in Web of Science. For researchers who need citable, peer-reviewed material on the latest applications of software engineering in emerging technology domains, this collection offers a convenient and authoritative reference.

Explore the Research Directions

Whether you are investigating supply chain optimization, smart healthcare, agricultural IoT, or cloud-native architectures, the chapters in this book highlight both established patterns and new ideas that are shaping the future of software engineering. The editors hope the volume will inspire further work and serve as a foundation for continued innovation in the field.