Result
- 500,000+ children supported annually through consistent biometric matching
- Reduced missed and duplicate vaccinations by enabling reliable biometric matching in offline clinics
- 586 clinics operating offline AI identification made possible by energy-efficient Arm compute
Market | Use Case
- On-device biometric ID
- Cloud-based training of growth prediction models
- Healthcare AI
- Mobile AI
- Datacenter AI
Powered by Arm
Infant Identification at the Frontline
Vaccinations protect children from preventable diseases, but only when each child can be reliably identified and their health records tracked. In low-resource settings, fragmented paper records, migration between clinics, and unreliable power or connectivity lead to missed or duplicate vaccinations during early childhood.
Enabling Edge-to-Cloud AI for Reliable Infant Identification
Simprints developed SimprintsID, a biometric digital identity system running on Arm-powered smartphones and tablets already used in clinics. At the point of care, health workers use a smartphone or tablet to capture key biometric modalities of the face, ear, and foot that will form the basis of their medical ID. On-device AI performs instant quality checks and identifies the highest quality image, even offline. When connectivity returns, encrypted biometric templates securely sync to the cloud for future record matching. As the child grows up, AI algorithms running in the cloud project growth patterns, providing a consistent medical ID over time.
Arm’s energy-efficient CPUs enable AI inference in remote clinics, while Arm-based cloud infrastructure supports scalable model training and secure data processing, with biometric data encrypted in transit and at rest.
Delivering Accurate Infant Identification at National Scale
What began as a pilot in 30 clinics has grown to 586, reaching more than 500,000 children across two regions of Ghana.
Families experience fewer missed visits and health ministries gain clearer visibility into coverage gaps. As a result, duplicate vaccinations are reduced, improving efficiency at a national scale.
Key Takeaways
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Restored continuity of care by linking infant identities across visits so the right child receives the right vaccine at the right time.
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Reduced duplicate and missed vaccinations through accurate biometric matching across clinics and regions.
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Enabled secure offline AI identification on energy-efficient Arm-based devices in low-power settings.
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Scaled from edge to cloud with on-device inference and Arm-based cloud training for national record matching.
