IoT Wearables Dataset for Women's Safety: Stress Detection and Analysis

The enhanced dataset is a sophisticated collection of simulated data points, meticulously designed to emulate real-world data as collected from wearable Internet of Things (IoT) devices. This dataset is tailored for applications in safety monitoring, particularly for women, and is ideal for developing machine learning models for distress or danger detection.

These visualizations offer valuable insights into the data, highlighting key aspects like the commonality of certain device types and the general health metrics like pulse rate and body temperature among the dataset's subjects.

Data Quality:

The dataset maintains a balance between realistic variations and data quality, ensuring its utility for analytical purposes.

This enhanced dataset provides a rich, realistic foundation for studies focusing on wearable technology, IoT applications, and machine learning, particularly in the context of women's safety and proactive risk detection.