Deadline Date: 10 August 2026
The integration of soft computing, machine learning, and mathematical modeling is transforming real time automation across a wide range of engineering domains. With the rapid growth of the Internet of Things, edge computing, and cloud based systems, there is an increasing need for intelligent and adaptive solutions that can process large volumes of data and make decisions autonomously. These technologies empower systems to operate dynamically, respond to environmental changes, and optimize performance without manual intervention. Edge computing enables data processing close to the source, which reduces latency and supports real time responsiveness in applications such as healthcare monitoring, smart transportation, and home automation. Cloud computing complements edge devices by providing centralized learning, deeper analysis, and large scale storage. The combination of cloud and edge systems allows for the development of robust architectures that support distributed intelligence and real time simulation.
Soft computing techniques such as neural networks, fuzzy logic, and evolutionary algorithms are well suited to handle imprecise and nonlinear data. When integrated with mathematical modeling, these methods enable the construction of adaptive and predictive systems for engineering process optimization, intelligent control, and simulation. Additionally, automated learning pipelines help models evolve with real time data, improving accuracy, reliability, and efficiency.
This call for papers seeks contributions that explore the synergy of soft computing and mathematical modeling in real time automation. Areas of interest include intelligent edge AI, secure data driven decision making, predictive maintenance, and scalable engineering solutions. The objective is to foster research that advances smart and autonomous systems through computational intelligence and mathematical frameworks.
The integration of soft computing, machine learning, and mathematical modeling is transforming real time automation across a wide range of engineering domains. With the rapid growth of the Internet of Things, edge computing, and cloud based systems, there is an increasing need for intelligent and adaptive ... show more
Editorial board
