Advanced Anti-Lost System for Indoor Environments using Smart Devices

Cases of child loss are unfortunately common, particularly in large indoor areas such as shopping malls where incidents of separation occur frequently. However, with the advent of smart devices, new opportunities have emerged to mitigate such incidents. Our research focuses on real-time monitoring and early warning systems for children in indoor environments, utilizing common smart devices such as smartphones, smartwatches, and smart bracelets. Specifically, we have developed an anti-lost system in which parents utilize their smartphones as the central platform, while their children carry smart devices connected to the smartphone platform via WiFi hotspots. By continuously monitoring the real-time signal strength of the WiFi connection, the system can determine if a child has wandered away from their parent and send an alert if necessary. Furthermore, if a child engages in abnormal activities, the parent’s smartphone platform receives a warning message. The system performs position estimation and activity recognition directly from the raw data collected by inertial sensors. Position estimation is predicted using Resnet network, while the activity recognition is determined using the CNN-LSTM network. The location calculation and activity recognition are performed independently on the respective smart devices.

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Publication Details

Published
2025-04-11
DOI
https://doi.org/10.1109/wccct65447.2025.11027944
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Advanced Anti-Lost System for Indoor Environments using Smart Devices

Sheng Guo, You Li, Minmin Li
Context-Aware Activity Recognition Systems
article

Advanced Anti-Lost System for Indoor Environments using Smart Devices

Sheng Guo, You Li, Minmin Li
article en

Abstract

Cases of child loss are unfortunately common, particularly in large indoor areas such as shopping malls where incidents of separation occur frequently. However, with the advent of smart devices, new opportunities have emerged to mitigate such incidents. Our research focuses on real-time monitoring and early warning systems for children in indoor environments, utilizing common smart devices such as smartphones, smartwatches, and smart bracelets. Specifically, we have developed an anti-lost system in which parents utilize their smartphones as the central platform, while their children carry smart devices connected to the smartphone platform via WiFi hotspots. By continuously monitoring the real-time signal strength of the WiFi connection, the system can determine if a child has wandered away from their parent and send an alert if necessary. Furthermore, if a child engages in abnormal activities, the parent’s smartphone platform receives a warning message. The system performs position estimation and activity recognition directly from the raw data collected by inertial sensors. Position estimation is predicted using Resnet network, while the activity recognition is determined using the CNN-LSTM network. The location calculation and activity recognition are performed independently on the respective smart devices.

Shenzhen University (CN), Peng Cheng Laboratory (CN)
Natural Science Foundation of Guangdong Province
Openalex Percentile: Top 88%
Context-Aware Activity Recognition Systems
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