用物联网机器人实时监测室内空气，自动绘图并预警
Indoor Air Quality Detection Robot Model Based on the Internet of Things (IoT)
- 用ESP32+多种传感器构建移动监测系统，自动建图
- 定位误差低于5%，传感器误差在12%以内
- 适合楼宇管理、家庭健康监控等场景
本文设计并实现了一个基于物联网的机器人系统，用于对封闭环境中的室内空气质量进行自主测绘与实时监测。该系统集成了SGP30、MQ-2、DHT11、VL53L0X和MPU6050等多种传感器与ESP32微控制器，通过映射算法采集空间数据，并采用Mamdani模糊逻辑系统对空气质量进行分类。在模型房间中开展的实测表明，系统平均定位误差低于5%，执行器运动误差低于2%，所有传感器测量误差均在12%以内。本工作贡献包括：(1) 一种低成本、集成化的物联网机器人平台，可同时完成环境建图与空气质量检测；(2) 基于Web的用户界面，支持实时数据可视化与远程控制；(3) 在实验室条件下验证了系统的准确性。
原文摘要 · Abstract (English)
This paper presents the design, implementation, and evaluation of an IoT-based robotic system for mapping and monitoring indoor air quality. The primary objective was to develop a mobile robot capable of autonomously mapping a closed environment, detecting concentrations of CO$_2$, volatile organic compounds (VOCs), smoke, temperature, and humidity, and transmitting real-time data to a web interface. The system integrates a set of sensors (SGP30, MQ-2, DHT11, VL53L0X, MPU6050) with an ESP32 microcontroller. It employs a mapping algorithm for spatial data acquisition and utilizes a Mamdani fuzzy logic system for air quality classification. Empirical tests in a model room demonstrated average localization errors below $5\%$, actuator motion errors under $2\%$, and sensor measurement errors within $12\%$ across all modalities. The contributions of this work include: (1) a low-cost, integrated IoT robotic platform for simultaneous mapping and air quality detection; (2) a web-based user interface for real-time visualization and control; and (3) validation of system accuracy under laboratory conditions.
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