Smart Stroller Design Based on STM32

The intelligent baby stroller based on STM32 aims to provide health care for infants while reducing the workload of caregivers. The system used STM32F103C8T6 as the main control chip and integrates various sensor modules such as DHT11 temperature and humidity sensor, BH1750 light intensity sensor, and HX711 pressure sensor to monitor infants’ vital signs. The system can soothe infants through automatic shading, rocking, and music playback devices. For cry detection, the system further extracted time-domain and frequency-domain features of infants’ cries and employs a Support Vector Machine (SVM) for classification and identification, with a Random Forest classifier used to verify its reliability. The ESP8266-WIFI module was utilized to upload various data to Huawei Cloud IoT via the MQTT protocol, allowing users to view the indicators of the baby stroller in real-time and send commands through a mobile app, enabling human-computer interaction.

Authors

Institutions

Publication Details

Published
2025-03-28
DOI
https://doi.org/10.1109/iccai66501.2025.00097
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smart Stroller Design Based on STM32

Yuyang Hu, Baohua Jia, Jiaxin Chen, Xiao Yu Huang
Advanced Sensor and Control Systems
article

Smart Stroller Design Based on STM32

Yuyang Hu, Baohua Jia, Jiaxin Chen, Xiao Yu Huang
article en

Abstract

The intelligent baby stroller based on STM32 aims to provide health care for infants while reducing the workload of caregivers. The system used STM32F103C8T6 as the main control chip and integrates various sensor modules such as DHT11 temperature and humidity sensor, BH1750 light intensity sensor, and HX711 pressure sensor to monitor infants’ vital signs. The system can soothe infants through automatic shading, rocking, and music playback devices. For cry detection, the system further extracted time-domain and frequency-domain features of infants’ cries and employs a Support Vector Machine (SVM) for classification and identification, with a Random Forest classifier used to verify its reliability. The ESP8266-WIFI module was utilized to upload various data to Huawei Cloud IoT via the MQTT protocol, allowing users to view the indicators of the baby stroller in real-time and send commands through a mobile app, enabling human-computer interaction.

Wuhan Business University (CN)
Affordable and clean energy
Openalex Percentile: Top 75%
Advanced Sensor and Control Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.