Main description:

The book covers the integration of Internet of Things (IoT) and Artificial Intelligence (AI) to tackle applications in smart healthcare. The authors discuss efficient means to collect, monitor, control, optimize, model, and predict healthcare data using AI and IoT. The book presents the many advantages and improvements in the smart healthcare field, in which ubiquitous computing and traditional computational methods alone are often inadequate. AI techniques are presented that play a crucial role in dealing with large amounts of heterogeneous, multi-scale and multi-modal data coming from IoT infrastructures. The book is intended to cover how the fusion of IoT and AI allows the design of models, methodologies, algorithms, evaluation benchmarks, and tools can address challenging problems related to health informatics, healthcare, and wellbeing.

Contents:

1. Lower-Gait Tracking Application Using Smartphones and Tablets2. One-class classification approach in accelerometer based remote monitoring of physical activities for healthcare applications

3. Detecting and monitoring behavioural patterns in individuals with cognitive disorders in the home environment with partial annotations

4. Towards On-device Weight Monitoring from Selfie Face Images Using Smartphones

5. Convergence between IoT and AI for Smart Health and Predictive Medicine

6. An Artificial Intelligence and Internet of Things Platform for Healthcare and Industrial Applications

7. Methods in Digital Mental Health: Smartphone-based Assessment and Intervention for Stress, Anxiety and Depression

8. AI for the detection of the Diabetic Retinopathy

9. Enhancing EEG-based Emotion Recognition with Fast Online Instance Transfer

10. Using Association Rules to mine Actionable Knowledge from Internet of Medical Thinks data