To run the app in the background without draining the battery, we optimized the app for battery usage efficiency. We used techniques like mobile location and mobile sensors to gather information. For example, the app updates the mobile location information and when a person is in continuous motion, the app collects the data and updates the information. Using this technique for updating information in the background reduces battery energy-draining issues.

The users can stay connected through the mobile app and post any issues in their surroundings. When a user updates an incident through the app, it is reflected as a notification in the local app user interface. This required instant and efficient notifications to multiple users. We framed the app to handle notifications from multiple users. Any issues in the locality or missing reports can be sent to multiple users in a fraction of a second to help solve the issue.

Many operations require alternative flows to make the process simple. QR operations are integrated into the app to enhance accessibility. Multiple operations are performed with QR for logging in, face recognition, and tag scanning. Implementing the QR system in the entire app needed to be handled. Generating a unique QR code for numerous users and providing information was very important. The QR process made the workflow easier.

To help pet identification be enhanced, the integration of Near Field Communication (NFC) tags on the pet’s collar was introduced. These tags can securely store essential pet information, facilitating rapid identification. Upon scanning, the NFC tag should trigger a real-time notification to the pet owner. To implement this system, collaborative agreements with NFC tag suppliers were needed to be established.