1. An Overview of IoT and ML-Based Emotion Recognition Systems
- Author
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Leena I. Sakri, Deepa Bendigeri, Rachana Hegde, Anushree Hegde, Shreya Anvekar, and Amogh Huddar
- Subjects
General Medicine - Abstract
Emotion recognition has emerged as a crucial research area in recent years due to its potential applications in various fields such as healthcare, marketing, and entertainment. In this study, we propose a novel approach to emotion recognition using the Internet of Things (IoT) and Machine Learning (ML) techniques. Our system consists of IoT devices equipped with sensors that capture physiological signals such as heart rate, skin conductance, and facial expressions. These signals are pre-processed and fed into an ML model for emotion classification. We evaluate our system on a publicly available dataset and achieve an accuracy of over 90%. Our results demonstrate the feasibility and effectiveness of using IoT and ML for emotion recognition, which can have significant implications for various industries. The proposed system can be extended to real-world applications such as personalized healthcare, customer feedback analysis, and content recommendation.
- Published
- 2023
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