Development of an AI-enabled smart ambulance system for real-time emergency response and traffic navigation

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dc.contributor.authorSani Saminu
dc.contributor.authorOlaosebikan Samuel Tunmise
dc.contributor.authorSuleiman Abimbola Yahaya
dc.contributor.authorIdris Oladele Muniru
dc.contributor.authorSalaudeen K. Olawale
dc.contributor.authorMuhammad kabir Abdulkadir
dc.contributor.authorSanusi Abdulrazaq
dc.contributor.authorHauwa Mohammed Hambali
dc.date.accessioned2026-09-04T10:31:25Z
dc.date.available2026-09-04T10:31:25Z
dc.date.issued2026
dc.description.abstractDelay in ambulance arrival during an emergency remains a major cause of avoidable damage, especially in congested areas and under-resourced regions. This project presents the design and development of an artificial intelligence ambulance detection and alert system using public space CCTV cameras. The system uses a Raspberry Pi as the central processing unit, running a deep learning model built on TensorFlow and trained with MobileNetV2 to identify an ambulance. Upon successful detection, an integrated buzzer is triggered for immediate local alert, while a GSM module sends SMS notifications to the nearby hospital or emergency response unit. The system was mechanically designed using TinkerCAD, with a 3D model that optimally arranges the camera, Raspberry Pi, and peripheral components. Circuit design and simulation were conducted using Cirkit Designer to ensure electrical stability and compatibility. This AI-enabled system demonstrated 96% detection accuracy and high precision, providing a reliable, cost-effective, and scalable alternative to GPS or a manual tracking approach. It offers a vital improvement to emergency medical response workflow, particularly in developing environments where smart healthcare infrastructure is still emerging.
dc.description.sponsorshipSelf
dc.identifier.citationSaminu, S. Tunmise, O.S. Yahaya, S. A. Muniru, I. O. Salaudeen A.H. Salaudeen, K.O. Kabir, M.A. Sanusi, A. Hauwa, M.H. (2026): Development of an AI-enabled smart ambulance system for real-time emergency response and traffic navigation. KIU Journal of Science, Engineering and Technology, 5(1), 14-23. published by Kampala International University (KIU)
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/123456789/18523
dc.language.isoen
dc.publisherKIU Journal of Science, Engineering and Technology
dc.subjectAmbulance Detection
dc.subjectPublic Space Camera
dc.subjectRaspberry Pi
dc.subjectDeep Learning
dc.subjectTinkerCAD
dc.titleDevelopment of an AI-enabled smart ambulance system for real-time emergency response and traffic navigation
dc.typeArticle

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