Cognitive sensing systems combined with IoTs and smart technologies are used in countless applications such as industrial robotics, computer-aided diagnosis, brain-computer interface (BCI), human-computer interaction (HCI), telemedicine, driverless cars and smart energy systems.

• Chapter 1: Introduction to cognitive sensing technologies and applications
• Chapter 2: Hardware architectures for some sparse signal recovery approaches
• Chapter 3: Performance evaluation of cognitive sensor frameworks for IoT applications in healthcare and environment monitoring
• Chapter 4: Cognitive sensors for rehabilitation and therapeutic treatment
• Chapter 5: An ensemble machine learning-based intelligent system for human activity recognition using sensory data
• Chapter 6: Challenges in the acquisition of non-invasive brain signals - electroencephalographic signals (EEG)
• Chapter 7: Cognitive task and workload classification using EEG signal
• Chapter 8: Automatic detection of Parkinson's disease using non-linear signal decomposition and machine learning techniques
• Chapter 9: A review on gait kinematics acquisition sensors and its advancements in IoT and machine learning
• Chapter 10: Cognitive IoT sensors for smart industrial and biomedical applications
• Chapter 11: Intelligent automation using IoT and machine learning
• Chapter 12: Recent trends in applications of cognitive sensors for smart manufacturing and control
• Chapter 13: A systematic study on cognitive sensors in robotics, UAVs, and drones
• Chapter 14: Sensor data fusion and processing in smart agriculture: crop quality assessment, crop damage, smart planning
• Chapter 15: Incremental learning of plant diseases and new plant types: moving towards a smart agriculture system
• Chapter 16: Disaster susceptibility analysis in remote sensing
• Chapter 17: Topological assessment of road transportation network
• Chapter 18: Future perspective and research direction in cognitive sensing technologies