Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/68954
Title: A low cost LoRa-based IoT big data capture and analysis system for indoor air quality monitoring
Authors: Meli, Matthew
Gatt, Edward
Casha, Owen
Grech, Ivan
Micallef, Joseph
Keywords: Indoor air quality
Internet of things
Big data
Wide area networks (Computer networks)
Issue Date: 2020
Publisher: Institute of Electrical and Electronics Engineers
Citation: Meli, M., Gatt, E., Casha, O., Grech, I., & Micallef, J. (2020). A low cost LoRa-based IoT big data capture and analysis system for indoor air quality monitoring. The 2020 International Conference on Computational Science and Computational Intelligence (CSCI'20), Las Vegas.
Abstract: This paper presents a low cost LoRa-based IoT big data capture and analysis system for indoor air quality monitoring. This system is presented as an alternative solution to expensive and bulky indoor air quality monitors. It enables multiple low cost nodes to be distributed within a building such that extensive location-based indoor air quality data is generated. This data is captured by a gateway and forwarded to a cloud-based LoRaWAN network which in turn publishes the received data via MQTT. A cloud-based data forwarding server is used to capture, format and store this big data on a cloud-based document-oriented database. Cloud-based services are used for data visualization and analysis. Periodic indoor air quality graphs along with air quality index and thermal comfort index heat maps are generated.
URI: https://www.um.edu.mt/library/oar/handle/123456789/68954
Appears in Collections:Scholarly Works - FacICTMN

Files in This Item:
File Description SizeFormat 
A_low_cost_LoRa-based_IoT_big_data_capture_and_analysis_system_for_indoor_air_quality_monitoring_2020.pdf
  Restricted Access
538.24 kBAdobe PDFView/Open Request a copy


Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.