"DREAM-EATING TAPIR” A DREAM DETECTION AROMATHERAPY INTELLIGENT DIFFUSER

With the cross development of neuroscience and artificial intelligence, the bio
signal-based environmental adaptive technology has become a research
frontier in the field of smart home. In this paper, we propose a smart
aromatherapy machine system that can combine brainwave (EEG) monitoring
and AI-driven, aiming to achieve dynamic optimisation of the home
environment through real-time EEG signal analysis. The study first builds a
multimodal data acquisition module to extract the characteristic frequency
bands such as α-wave and β-wave to identify the user's relaxation,
concentration or fatigue state. Secondly, a lightweight deep learning model is
designed to classify EEG signals in real-time and ensure low-latency
interaction through edge computing architecture. The system dynamically
regulates the aromatherapy machine based on the classification results. Users
can self-select a theme in the system according to their preferences or
emotions, and then the aromatherapy device releases the corresponding aroma
according to the selected theme to help the user fall asleep more easily.
During sleep, the system continuously tracks the user's sleep dynamics
through an integrated sleep monitoring application, which transmits the data to
the device. At the same time, the system collects and analyses detailed data on
sleep quality, dream activity and scent adjustment to generate a
comprehensive report that is sent to the user's smartphone.
This innovative design not only enhances the user experience, but also
provides a scientific basis for assessing individual sleep conditions. Current
research shows that aromatherapy has a positive effect on improving sleep
quality and relieving anxiety symptoms.
However, there is still a lack of research on the dynamic adjustment of
fragrance based on real-time sleep data. This study aims to fill this gap by
developing a system that enables personalised fragrance release based on user
preferences and real-time sleep monitoring data, providing users with an
unprecedented sleep experience.