Description

As workplace stress can manifest in both physical and mental illness, the aim of this project is to create a smart work Life balance system that uses AI and wearable data to support healthier and more equitable work practices. This system will consider not only working hours but also external life demands such as commuting time, domestic chores, and childcare responsibilities.

There will be three main components:

1. Stress Prediction Model
   An AI model will analyse survey responses from the specific user, out of work routines(household chores, commute, childcare) and data from wearables (fitbit)to predict stress.

2. Scheduling Optimisation
   A decision optimisation algorithm will generate personalised work schedules, recommending flexible arrangements such as remote work days(if selected by the user), adjusted working hours, or focus blocks. The goal is to minimise predicted stress while maintaining required productivity levels and keeping up with commitments.

3. Mobile App This will integrate wearable data, AI predictions, and scheduling recommendations. Users will receive personalised insights into their stress levels and suggested adjustments.

Will use fitbit as a wearable as it is possible to pull data such as heart rate (resting & continuous), sleep (duration, efficiency, stages), active / sedentary minutes.