AI & Machine Learning

AI & Machine Learning in Engineering and Technology

Scope of Research

Artificial Intelligence (AI) and Machine Learning (ML) are transforming engineering and technology by enabling intelligent automation, predictive analytics, and data-driven decision-making.

Inovato welcomes high-quality research that explores advanced AI models, engineering applications, and real-world implementations to drive next-generation innovations.

This section provides a platform for researchers focusing on AI-driven engineering solutions, robotics, deep learning, and autonomous decision-making systems that improve industrial processes, system efficiency, and smart adaptive environments.

Key Research Areas

We encourage submissions in the following areas:

1. AI-Driven Automation & Control Systems

• Intelligent control systems for industrial automation
• AI-powered process optimization in engineering
• Smart decision-support systems for real-time applications

2. Deep Learning & Neural Networks

• Convolutional and recurrent neural networks in engineering
• Generative AI applications in engineering problem-solving
• AI-driven predictive maintenance and fault detection

3. Robotics & Intelligent Machines

• AI-enhanced robotic automation and machine learning in robotics
• Human-robot interaction and autonomous robotic systems
• AI-powered vision and perception systems

4. AI in Industrial & Manufacturing Processes

• AI-driven predictive analytics in smart manufacturing
• Machine learning for real-time quality control and defect detection
• AI-enhanced production scheduling and workflow optimization

5. Natural Language Processing (NLP) in Engineering

• AI-based technical documentation and automated report generation
• Voice and text recognition systems in industrial applications
• AI-powered knowledge extraction and domain-specific NLP models

6. AI for Cyber-Physical Systems & Smart Infrastructure

• AI integration with IoT for intelligent infrastructure management
• AI-based cybersecurity solutions for smart engineering systems
• AI-driven network optimization in smart grids and industrial IoT

7. Ethical AI & Responsible Machine Learning

• Bias mitigation and fairness in AI algorithms
• Explainable AI (XAI) in engineering applications
• AI governance and regulatory considerations in industrial settings

Types of Research Papers Welcomed

Researchers are invited to submit original contributions in the following categories:

• Original Research Articles – Novel AI/ML methodologies, algorithm development, and engineering applications.
• Review Papers – Comprehensive surveys of AI applications in specific engineering domains.
• Case Studies – AI-driven solutions for real-world engineering challenges.
• Comparative Studies – Performance evaluations of AI models in engineering applications.
• Technical Reports – Reports on AI deployments in industrial and technological settings.