Iot-Enabled Industrial Air Quality Monitoring And Smart Inventory Management System

Industrial environments require continuous monitoring of both air quality and inventory to ensure operational efficiency, worker safety, and environmental compliance. Traditional monitoring approaches rely on manual checks and periodic inspections, which often lead to delayed detection of hazardous gas levels, poor inventory visibility, and inefficient resource usage. This research proposes an IoT-based system that integrates air quality sensors, inventory tracking modules, and cloud-based analytics to monitor industrial conditions in real time. Using gas sensors (MQ-series), particulate matter sensors, RFID/barcode modules, and microcontrollers such as ESP32/NodeMCU, the system continuously collects data and transmits it to cloud dashboards for visualization and alerting. Automated notifications are triggered when pollutant levels exceed permissible limits or when inventory levels reach predefined thresholds. The system enhances worker safety, reduces downtime, and ensures accurate inventory management. By combining environmental monitoring with intelligent tracking technologies, the proposed solution supports industrial automation, improves regulatory compliance, and optimizes overall operational workflows.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-31
DOI
https://doi.org/10.5281/zenodo.19356869
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
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article

Iot-Enabled Industrial Air Quality Monitoring And Smart Inventory Management System

IJERST
Zenodo (CERN European Organization for Nuclear Research)
Air Quality Monitoring and Forecasting
article

Iot-Enabled Industrial Air Quality Monitoring And Smart Inventory Management System

IJERST
article en

Abstract

Industrial environments require continuous monitoring of both air quality and inventory to ensure operational efficiency, worker safety, and environmental compliance. Traditional monitoring approaches rely on manual checks and periodic inspections, which often lead to delayed detection of hazardous gas levels, poor inventory visibility, and inefficient resource usage. This research proposes an IoT-based system that integrates air quality sensors, inventory tracking modules, and cloud-based analytics to monitor industrial conditions in real time. Using gas sensors (MQ-series), particulate matter sensors, RFID/barcode modules, and microcontrollers such as ESP32/NodeMCU, the system continuously collects data and transmits it to cloud dashboards for visualization and alerting. Automated notifications are triggered when pollutant levels exceed permissible limits or when inventory levels reach predefined thresholds. The system enhances worker safety, reduces downtime, and ensures accurate inventory management. By combining environmental monitoring with intelligent tracking technologies, the proposed solution supports industrial automation, improves regulatory compliance, and optimizes overall operational workflows.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Openalex Percentile: Top 7%
Air Quality Monitoring and Forecasting
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