Skip to main content
Kaggle

AIR4LIFE: Dual-Node Environmental Monitoring Dataset

Environmental
127 views
1 min read
License

Abstract

"AIR4LIFE is a high-resolution air quality monitoring dataset published in late 2025, featuring measurements from a dual-node IoT setup. It tracks pollutants and ambient conditions to evaluate the trade-offs between energy-aware duty cycling and data completeness in environmental sensing networks."

Description

Overview

High-resolution environmental time series collected via the AIR4LIFE proof-of-concept deployment for energy-aware air quality monitoring.

Technical Details

Measurements include CO2 (NDIR), particulate matter (PM2.5/PM10), temperature, humidity, light, and noise sampled at 5-minute intervals.

Collection Setup

Two MoleNet-based senseBoxes were deployed over five months (ending December 2025), with one node continuous and the other duty-cycled for energy testing.

Recommended Research Tasks

Energy-aware sensing strategy optimization, data imputation for duty-cycled IoT nodes, and urban air pollution exposure modeling.

Access & License

Available on Zenodo. Access Dataset

View Data Structure

To explore column names, data types, and sample rows, visit the official dataset page on Kaggle.

Preview on Kaggle

Cite This Dataset 

Gijón, Á., Bolaños, C., & Villanueva, F. (2025). AIR4LIFE: Dual-Node Environmental Monitoring Dataset. [Dataset]. {Zenodo. https://doi.org/10.5281/zenodo.17288923

Source: {Zenodo (2025) · DOI: 10.5281/zenodo.17288923

Indexed by IoTDataset.com on Feb 06, 2026

Ready to Start Your Research?

Download this dataset directly from the official repository and start building your next breakthrough project.

Download Dataset

Related Topics & Keywords

#Air Quality #Environmental Monitoring #Energy-Aware IoT #Particulate Matter #CO2 Monitoring #Dual-Node Sensing #Urban Pollution

Share This Research

More in Environmental

View All
Environmental Kaggle

Integrated Satellite-IoT-Machine Learning Framework for Disaster Management

Published in November 2025, this dataset provides a multimodal framework integrating satellite imagery and IoT sensor data for environmental monitoring and disaster management. It is designed to support the development of machine learning models that synchronize remote sensing with ground-based IoT observations for real-time risk assessment.

Feb 06, 2026
Environmental Kaggle

UrbanAirNet: Urban Air Quality and Weather Dataset

UrbanAirNet provides a comprehensive collection of urban air quality and weather parameters measured via IoT sensor networks. It includes pollutants like PM2.5, NO2, and O3 alongside meteorological variables.

Feb 05, 2026
Environmental Government

Temperature and Humidity Monitoring: Environmental Sensors

Government-operated sensor network providing temperature and humidity readings for weather monitoring, site supervision, wetland tracking, and ecological research. High-frequency, long-term environmental data collection.

Jan 12, 2026
Environmental Kaggle

Indoor Air Quality Dataset (IAQ Monitoring)

Real-time indoor air quality from IoT sensors tracking CO2, VOCs, PM2.5 for building health and occupancy correlation.

Jan 12, 2026