This book highlights the growing impact of artificial intelligence in addressing real-world challenges. The chapters explore topics such as wearable mechatronic sensing for ergonomic risk assessment in healthcare, mechatronic robotic phenotyping and machine learning in plant breeding, mechatronic sensor networks for air quality prediction, hybrid metaheuristic optimization for cloud-connected mechatronic and cyber-physical task scheduling, mechatronic sensor-driven anomaly detection for carbon credit fraud, sentiment analysis for mechatronic human–machine interaction, and mechatronic, automation-ready drug discovery. Although these contributions span diverse disciplines, they share a common focus on applying intelligent computing to the sensing, decision-making, and optimization problems that increasingly define modern mechatronic and engineering systems.
This book highlights the growing impact of artificial intelligence in addressing real-world challenges. The chapters explore topics such as wearable mechatronic sensing for ergonomic risk assessment in healthcare, mechatronic robotic phenotyping and machine learning in plant breeding, mechatronic sensor networks for air quality prediction, hybrid metaheuristic optimization for cloud-connected mechatronic and cyber-physical task scheduling, mechatronic sensor-driven anomaly detection for carbon credit fraud, sentiment analysis for mechatronic human–machine interaction, and mechatronic, automation-ready drug discovery. Although these contributions span diverse disciplines, they share a common focus on applying intelligent computing to the sensing, decision-making, and optimization problems that increasingly define modern mechatronic and engineering systems.
Akshat Agrawal
Ergonomic Risk Assessment Robotic Phenotyping Mechatronic Sensor Networks Urban Air Quality Prediction Cloud-Connected Mechatronic systems Genetic Algorithm–Particle Swarm Optimization (GA-PSO) Human-Machine Interaction QSAR Modelling Wearable Mechatronic Sensing