Indoor Air Quality Detection Robot Model Based on the Internet of Things (IoT)

TL;DR

This paper introduces an IoT-enabled robotic system capable of autonomously mapping indoor environments and monitoring air quality parameters like CO2, VOCs, smoke, temperature, and humidity, with real-time data transmission and validation.

Contribution

It presents a novel low-cost IoT robotic platform for simultaneous indoor mapping and air quality detection, with a web interface and validated accuracy.

Findings

Localization errors below 5%

Sensor measurement errors within 12%

Effective real-time air quality monitoring

Abstract

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.