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Volume 14
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10.3390/technologies14070406
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

AI-Enabled Edge-Based Intraoral Wearable System for Early Detection and Management of Dental Caries

by
Titus Ifeanyi Chinebu
1,2,
Kennedy Chinedu Okafor
2,3,4,5,6,*,
Henrietta Onyinye Uzoeto
7,
Ogochukwu Militus Ifenze
3,
Juliet Onyinye Nwigwe
7,
Diovu Remigius Chidiebere
3,
Ijeoma Peace Okafor
8,
Ijeoma Madonna Onwusuru
2,
Wisdom Okafor
2 and
Onukwube Victor Apeh
7
1
Department of Prosthetics and Orthotics, Federal University of Allied Health Sciences, Enugu PMB 01473, Nigeria
2
IEEE SkillUp Hub, Center for Future Technologies, University of Chichester, Bognor Regis PO21 1HR, UK
3
Department of Biomedical Engineering, Federal University of Allied Health Sciences, Enugu, PMB 01473, Nigeria
4
Department of Engineering, Manchester Metropolitan University, Manchester M1 5GD, UK
5
Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa
6
Department of Management and Entrepreneurship, Imperial College Business School, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
7
Department of Biochemistry, Federal University of Allied Health Sciences, Enugu PMB 01473, Nigeria
8
Department of Public Health, Cardiff Metropolitan University, Llandaff Campus, Western Avenue, Cardiff CF5 2YB, UK
*
Author to whom correspondence should be addressed.
Technologies 2026, 14(7), 406; https://doi.org/10.3390/technologies14070406
Submission received: 8 March 2026 / Revised: 11 June 2026 / Accepted: 16 June 2026 / Published: 2 July 2026
Versions Notes

Abstract

Dental caries remains one of the most prevalent yet preventable non-communicable diseases worldwide, disproportionately affecting populations with limited access to dental care and persistent socioeconomic inequalities. Early-stage lesions frequently remain undetected because of their asymptomatic nature, inadequate screening infrastructure, and the absence of continuous monitoring technologies, resulting in preventable complications and increased healthcare costs. To address these challenges, this study proposes an Internet of Things (IoT)-enabled intraoral wearable sensing device (I-OWSD) for continuous, quantitative, real-time monitoring of biomarkers associated with caries progression. The proposed framework integrates intraoral wearable sensing, cloud-based telemedicine services, and artificial intelligence (AI)-assisted analytics to support preventive oral healthcare and remote clinical decision-making. Two primary contributions are presented. First, a fractional-order delay-type model (FODM) based on the Caputo–Fabrizio derivative is proposed to capture the memory-dependent and nonlocal dynamics of caries progression. Mathematical analysis establishes the model’s non-negativity, boundedness, existence, uniqueness, and stability properties. Second, a biocompatible intraoral sensor interface is designed to enable continuous data acquisition and secure wireless communication with digital health platforms. Simulation results based on the proposed FODM suggest that, under an estimated adoption rate of 67.49%, the I-OWSD framework could reduce caries prevalence by approximately 15% while improving opportunities for early intervention and preventive care. The findings demonstrate the potential of combining fractional-order modelling, wearable sensing, and AI-driven teledentistry to advance continuous oral health monitoring and preventive dental care.
Keywords: artificial intelligence; smart intelligent system; sensory devices; proportional Caputo–Fabrizio; internet of things artificial intelligence; smart intelligent system; sensory devices; proportional Caputo–Fabrizio; internet of things

Share and Cite

MDPI and ACS Style

Chinebu, T.I.; Okafor, K.C.; Uzoeto, H.O.; Ifenze, O.M.; Nwigwe, J.O.; Chidiebere, D.R.; Okafor, I.P.; Onwusuru, I.M.; Okafor, W.; Apeh, O.V. AI-Enabled Edge-Based Intraoral Wearable System for Early Detection and Management of Dental Caries. Technologies 2026, 14, 406. https://doi.org/10.3390/technologies14070406

AMA Style

Chinebu TI, Okafor KC, Uzoeto HO, Ifenze OM, Nwigwe JO, Chidiebere DR, Okafor IP, Onwusuru IM, Okafor W, Apeh OV. AI-Enabled Edge-Based Intraoral Wearable System for Early Detection and Management of Dental Caries. Technologies. 2026; 14(7):406. https://doi.org/10.3390/technologies14070406

Chicago/Turabian Style

Chinebu, Titus Ifeanyi, Kennedy Chinedu Okafor, Henrietta Onyinye Uzoeto, Ogochukwu Militus Ifenze, Juliet Onyinye Nwigwe, Diovu Remigius Chidiebere, Ijeoma Peace Okafor, Ijeoma Madonna Onwusuru, Wisdom Okafor, and Onukwube Victor Apeh. 2026. "AI-Enabled Edge-Based Intraoral Wearable System for Early Detection and Management of Dental Caries" Technologies 14, no. 7: 406. https://doi.org/10.3390/technologies14070406

APA Style

Chinebu, T. I., Okafor, K. C., Uzoeto, H. O., Ifenze, O. M., Nwigwe, J. O., Chidiebere, D. R., Okafor, I. P., Onwusuru, I. M., Okafor, W., & Apeh, O. V. (2026). AI-Enabled Edge-Based Intraoral Wearable System for Early Detection and Management of Dental Caries. Technologies, 14(7), 406. https://doi.org/10.3390/technologies14070406

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