Design of a Smart Home System Based on Orange Pi : Leveraging Heterogeneous Edge Computing with Origin Pi 4B

To overcome the technical challenges faced by smart home systems, including environmental sensing accuracy, multimodal control integration, and security protection, this study proposes a smart home solution based on a heterogeneous computing architecture utilizing the Orange Pi 4 B. The system features an embedded sensor network built with STM32 and ESP8266 microcontrollers, incorporating a high-precision BME280 environmental sensor array and an MQ-7 carbon monoxide detection module. It also integrates an anomaly detection model based on TensorFlow Lite, enabling real-time monitoring of environmental parameters and intelligent decision-making. The solution innovatively employs dynamic IP mapping to resolve NAT traversal issues, while establishing a bidirectional encrypted communication channel to ensure secure data transmission. Experimental results demonstrate the system’s excellent performance across key metrics, including temperature and humidity monitoring accuracy within ±1.5%, and a carbon monoxide alarm response time of less than 3 seconds, offering a reliable technical reference for the development of smart homes.

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Publication Details

Published
2025-05-09
DOI
https://doi.org/10.1109/cisce65916.2025.11065106
Primary Topic
IoT-based Smart Home Systems
Type
article
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article

Design of a Smart Home System Based on Orange Pi : Leveraging Heterogeneous Edge Computing with Origin Pi 4B

Xiaoyu Zhu, X. H. Li, Z.M. Su, Yudan Nie
IoT-based Smart Home Systems
article

Design of a Smart Home System Based on Orange Pi : Leveraging Heterogeneous Edge Computing with Origin Pi 4B

Xiaoyu Zhu, X. H. Li, Z.M. Su, Yudan Nie
article en

Abstract

To overcome the technical challenges faced by smart home systems, including environmental sensing accuracy, multimodal control integration, and security protection, this study proposes a smart home solution based on a heterogeneous computing architecture utilizing the Orange Pi 4 B. The system features an embedded sensor network built with STM32 and ESP8266 microcontrollers, incorporating a high-precision BME280 environmental sensor array and an MQ-7 carbon monoxide detection module. It also integrates an anomaly detection model based on TensorFlow Lite, enabling real-time monitoring of environmental parameters and intelligent decision-making. The solution innovatively employs dynamic IP mapping to resolve NAT traversal issues, while establishing a bidirectional encrypted communication channel to ensure secure data transmission. Experimental results demonstrate the system’s excellent performance across key metrics, including temperature and humidity monitoring accuracy within ±1.5%, and a carbon monoxide alarm response time of less than 3 seconds, offering a reliable technical reference for the development of smart homes.

Department of Commerce (AU), Guangzhou College of Commerce
Openalex Percentile: Top 85%
IoT-based Smart Home Systems
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