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<p>During the COVID-19 pandemic, there was a conspicuous void in the integration of contemporary technological solutions in the public health sector. Tracy and Tracer are mobile applications designed to address this gap by enabling users to contribute extensive datasets through real-time surveillance, thus facilitating both effective contact tracing and integration of health data. Tracy leverages Bluetooth and GPS to automatically record movement data and proximity interactions, generating comprehensive datasets for advanced analytics. Tracer, on the other hand, collects self-assessed health data, which can be further refined for public health analysis. Developed using Flutter and Android Studio with data securely stored in Firebase, both applications implement privacy-focused data processing protocols, ensuring anonymization and adherence to ethical standards. By combining data collection with privacy-centric processes, Tracy and Tracer serve as complementary AI-powered tools that can significantly enhance public health decision-making during health crises. The system architecture, data capture mechanisms, and data transfer protocols emphasize privacy protection and secure data handling, with promising applications for future epidemic mitigation efforts.</p>

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Tracy and Tracer: AI-Powered Mobile Applications for Privacy-Preserving Contact Tracing and Health Monitoring

  • 期刊论文

  • 发表日期：

    2026年2月11日

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  • Bolanle Adefowoke Ojokoh,
  • Benjamin Segun Aribisala,
  • Arome Junior Gabriel,
  • Olusola Tope Babalola,
  • Oluwafemi Abimbola Sarumi,
  • Tobore Victor Igbe,
  • Olatunji Omisore,
  • Abimbola Helen Afolayan,
  • Abiola Ezekiel Taiwo,
  • Uchechukwu M. Chukwuocha,
  • Tolulope Anthonia Ugwu,
  • Daniel Adeniyi

摘要

During the COVID-19 pandemic, there was a conspicuous void in the integration of contemporary technological solutions in the public health sector. Tracy and Tracer are mobile applications designed to address this gap by enabling users to contribute extensive datasets through real-time surveillance, thus facilitating both effective contact tracing and integration of health data. Tracy leverages Bluetooth and GPS to automatically record movement data and proximity interactions, generating comprehensive datasets for advanced analytics. Tracer, on the other hand, collects self-assessed health data, which can be further refined for public health analysis. Developed using Flutter and Android Studio with data securely stored in Firebase, both applications implement privacy-focused data processing protocols, ensuring anonymization and adherence to ethical standards. By combining data collection with privacy-centric processes, Tracy and Tracer serve as complementary AI-powered tools that can significantly enhance public health decision-making during health crises. The system architecture, data capture mechanisms, and data transfer protocols emphasize privacy protection and secure data handling, with promising applications for future epidemic mitigation efforts.