Back to results

AUT University

Hyperlocal Monitoring of Air Pollutants at Street-Level Using a Long-Range Wireless Sensor Network

Abstract

Air pollution monitoring is essential for assessing air quality and its impact on health and the environment. It involves collecting data on pollutants like particulate matter, ozone, carbon monoxide, etc. This practice includes protecting public health, ensuring environmental preservation regulatory compliance, and facilitating research and policymaking. With urbanization and industrialization contributing to increased pollution levels, monitoring becomes crucial for creating a cleaner and healthier future. A Wireless Sensor Network (WSN) pollution monitoring system utilizing Long-Range (LoRa) technology offers valuable street-level analysis. The LoRa network was simulated and implemented for real-time monitoring in Auckland, New Zealand, for this research. Sensors for particulate matter, carbon dioxide, temperature, and humidity were placed in a strategic matrix at Auckland University of Technology's North Shore campus. Data collected was transmitted to a server via the LoRa gateway. This research aims to provide localized data for different areas in Auckland, encouraging the Auckland Council and policymakers to make decisions regarding air pollution monitoring systems. The study highlights the health impacts of pollutants, particularly on respiratory and cardiovascular health. Empowering stakeholders with data supports informed decision-making, effective pollution control measures, and the pursuit of healthier and sustainable cities.

Author and committee

dc:creator, dc:contributor.*
Author
  • Kaur, Amritpal

Identifiers

dc:identifier.*
Identifier
hdl:10292/17282
OAI identifier oai:identifier
oai:openrepository.aut.ac.nz:10292/17282

Chain of custody

source
Harvested from
AUT University
Base URL
openrepository.aut.ac.nz/server/oai/request
Last updated
2026-07-27
Source record
OAI-PMH GetRecord
related terms
citation

Kaur, Amritpal. Hyperlocal Monitoring of Air Pollutants at Street-Level Using a Long-Range Wireless Sensor Network. 2022.