Internet-of-Mirrors for Non-Invasive Digital Smile Analysis in Smart Dental Care

Supervisor: Dr Lina Mohjazi and Haneen Fatima (PGR)

School: Engineering

Industry Partner: Dr Rahaf Omran, Independent Dentist

Description: 

The integration of smart technology, such as Internet of Things (IoT) and machine-to-machine (M2M) communications, and cloud computing, in healthcare, including dental care, enables AIdriven products and services to offer personalised patient experiences. Automated image analysis allows non-invasive pain-free diagnosis and early detection of dental conditions, improving treatment effectiveness and patient engagement.
 
This project will therefore aim to use the Internet of Mirrors (IoM) prototype, built in house at the Communication, Sensing, and Imaging Hub, to develop an immersive dashboard on a smart mirror that visualises various dental parameters, providing an accurate digital smile analysis for dental consultations and treatments. Figures 1 and 2 illustrate the prototype of the smart mirror and the IoM system, respectively. By visualising various dental parameters, such as gum health, plaque build up, and teeth alignment, our IoM System can provide a personalised approach to dental care, where the smart mirror is not just a reflection of a person’s smile, but a gateway to a personalised dental experience. A smart mirror with high-resolution depth camera and located at individuals’ home can continuously take high-quality images of their teeth and gums, allowing them to receive instant feedback on an interactive screen on their oral health and oral aesthetics through machine learning (ML)-powered digital smile analysis. The outputs of the project will be informed by the input of a dentist to ensure that the research direction is aligned with current dental practices and standards, ensuring that the technology leads to effective benefits to the field.
 
 
The objectives of the project are as follows:
 
  • Objective 1 – Data Collection Stage: Collect smile image from the high-resolution depth camera integrated with the smart mirror to build a dataset, depicting a wide range of oral health and aesthetics conditions, as informed by the dentist, to train the ML algorithms (2 weeks).
  • Objective 2 – AI Stage and Live Image Recognition: Develop ML algorithms to accurately detect, in real-time, the oral health and/or aesthetics condition using cutting edge classification algorithms. The algorithms will recognise oral features and smile proportions (3 to 4 weeks).
  • Objective 3 – Development and Integration with 5G Testbed: Develop a dashboard on an interactive screen that visualises the detected oral conditions. The IoM system will be integrated with the 5G Testbed, specifically the IoT Scotland Network, to investigate the connectivity capabilities of the system, such as reliability, latency, and data processing energy cost (3 to 4 weeks).