Alert system for forgotten baby syndrome with Bluetooth Low Energy (BLE) tags

Azman, Nurul Liyana and Shahbudin, Fadilah Ezlina (2025) Alert system for forgotten baby syndrome with Bluetooth Low Energy (BLE) tags. Progress in Computer and Mathematics Journal (PCMJ), 3. ISSN 3030-6728

Official URL: https://fskmjebat.uitm.edu.my/pcmj/

Abstract

Forgotten Baby Syndrome (FBS) is a tragic situation in which parents unintentionally leave their infants or young children alone in parked cars, leading to severe outcomes like heatstroke or even fatality. Cases related to this syndrome are commonly reported across the globe including Malaysia. With the aim of improving child safety, this project proposed a mobile application with an alert system to prevent FBS that works through Bluetooth Low Energy (BLE) tag. The BLE tag is attached to the child. Each BLE tag is capable of sustaining a connection up to 30 until 50 meters indoors and 100 until 240 meters in open areas. When the connection is lost, the application sounds an alarm, sends a notification to the parent’s phone, and sends an SMS to the emergency contact. The project development follows the Mobile Application Development Life Cycle (MADLC) which consists of five phases: identification, design, development, prototyping, and testing. The system was designed and developed based on the information gathered. RSSI data filtered by Kalman Filtering is used to estimate the distance signal between the child tag and the parent's phone. The Haversine formula calculate the approximate distance between the parent’s mobile device and the child’s last recorded position. Functionality testing was conducted and all test cases passed successfully, confirming that the mobile application functions as intended. The results of this project indicated that it is capable of monitoring the BLE tag connection status continuously and notifying if the BLE signal is not detected by triggering an alert, sends push notification, and sends SMS to the emergency contact to indicate potential risks.

Download

[thumbnail of 127990.pdf] Text
127990.pdf

Download (816kB)

ID Number

127990

Indexing

Statistic

Statistic details