🧰 Technologies Used

Synora was built using a carefully chosen stack that balances reliability, scalability, cost, and ease of deployment across home and clinical environments.

Programming Languages

  • Python – AI model development, data processing, and backend logic
  • C and C++ – Embedded firmware for low-power wearable devices
  • JavaScript and TypeScript – Caregiver dashboard and mobile interface logic

Frameworks and Libraries

  • TensorFlow Lite – Lightweight machine learning models optimized for edge devices
  • PyTorch – Prototyping and training AI models
  • React and React Native – Web and mobile caregiver applications
  • Node.js with Express – Backend API services
  • MQTT – Lightweight real-time device communication

Hardware and Embedded Platforms

  • ESP32-class microcontrollers – Sensor integration, wireless communication, and power-efficient processing
  • IMU and vital sensors – Motion, fall detection, and physiological signal capture

Cloud and Backend Services

  • AWS – Scalable backend infrastructure and device management
    • AWS IoT Core for device connectivity
    • AWS Lambda for event-driven processing
    • AWS S3 for encrypted data storage

Databases

  • PostgreSQL – Structured user, device, and event data
  • Redis – Real-time alert queues and low-latency state management

APIs and Integrations

  • REST APIs – Secure communication between devices, cloud services, and caregiver apps
  • Push notification APIs – Instant caregiver alerts on critical events
  • Encryption libraries – End-to-end data protection and user-controlled access

DevOps and Tooling

  • Docker – Consistent deployment across environments
  • Git and GitHub – Version control and collaborative development
  • CI and CD pipelines – Automated testing and deployment workflows

Security and Privacy

  • TLS and AES encryption – Secure data transmission and storage
  • Role-based access control – Ensuring data visibility only to authorized caregivers

This technology stack allowed Synora to remain affordable, scalable, and privacy-first while delivering real-time, AI-driven assistive care.

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