The issue:

In the context of field data collection for assets in areas with limited or no mobile coverage, a key challenge was ensuring that data collected by arborists could reliably sync with a central database. Initially, the process required constant internet connectivity, which was problematic in remote areas. Additionally, as the team grew from one to over ten arborists, sync times slowed, causing data transfer delays that hindered operations.

How we solved it:

To address this, we developed an optimised sync module that checks the device’s connection status. If offline, it stores data locally and sends alerts if un-synced for several days. When back online, it compares local and central data, syncing only necessary updates, reducing sync time from five minutes to 10-20 seconds. This improved both efficiency and data security, even in cases of device loss or damage.

The tech used:

Our solution supports seamless Quality Assurance processing for large datasets, focusing on speed, data integrity, and adaptability.

• Local storage: Each device uses a lightweight SQLite database to securely store data offline, keeping the app responsive even with large datasets.
• Smart sync logic: The module queues updates locally when offline, with alerts for un-synced data. Once reconnected, it syncs only necessary updates, reducing sync time and bandwidth by over 90%.
• Delta-sync and version control: Transfers only new or modified records using GUIDs and timestamps to maintain up-to-date data as users increase.
• Server-side merging: The server remains the data authority, handling record merges efficiently with transaction and sync IDs, avoiding data conflicts.
• Secure architecture: Encrypted communications and audit trails protect data integrity and enable easy change tracing without compromising the database.

This module enables faster, more reliable Quality Assurance, allowing field officers to work efficiently even in low-connectivity environments.