DEVELOPING A CROSS-PLATFORM SOLUTION FOR A SMART TEXTILE COMPANY

Discover how DBB Software partnered with a Canadian smart textile company to create a cross-platform mobile app that gathers and processes user parameters and biometric data from innovative textile garments.

Industry

Healthcare & Biotech

Service

Mobile App Development

Team

4 FE Developers

Project State

January 2021 - August 2022

Country

Canada

About the Client

MyAnt, a pioneer in the smart textile industry, specializes in designing garments embedded with biometric sensors. Their mission is to empower users to monitor health metrics like heart rate, ECG, and activity levels seamlessly through everyday clothing, enhancing wellness and healthcare outcomes.

THE CLIENT'S  INITIAL REQUEST

The client approached DBB Software to develop a cross-platform mobile application to complement their smart textile garments, with a focus on collecting and analyzing user parameters and biometric data:

Cross-Platform Compatibility

Build an app for iOS and Android to maximize user reach.

Biometric Data Integration

Enable seamless connectivity with garment sensors to collect metrics like heart rate, ECG, and steps.

User Parameter Management

Allow users to view, manage, and share personalized health data.

Real-Time Processing

Ensure the app processes and displays biometric insights instantly for user accessibility.

SOLUTIONS WE DELIVERED

As a result, the DBBS team delivered a comprehensive cross-platform and feature-rich solution:

Cross-Platform Development

Utilized Flutter to create a single-codebase app compatible with iOS and Android, reducing development time and ensuring consistent performance across platforms.

Biometric Sensor Integration

Engineered a robust Bluetooth Low Energy (BLE) module to connect the app with smart textile sensors, enabling real-time collection of biometric data such as heart rate, ECG, and movement patterns.

User Data Dashboard

Designed an intuitive interface with a WYSIWYG-style dashboard, allowing users to visualize biometric data through charts and graphs, manage historical records, and set sharing preferences with healthcare providers.

Real-Time Data Processing

Implemented a lightweight backend using Node.js and MongoDB to process incoming biometric data, delivering insights to users within seconds, optimized for low latency even with high data volumes.

RESULTS ACHIEVED

Integration with Smart Garments

Added seamless BLE connectivity between the app and garments.

Complex Data Analysis

Implemented algorithms for complex health indicators analysis.

Data Structuring

Developed an algorithm to process and structure data into insights.

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