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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 | Size | Format | |
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A_low_cost_LoRa-based_IoT_big_data_capture_and_analysis_system_for_indoor_air_quality_monitoring_2020.pdf Restricted Access | 538.24 kB | Adobe PDF | View/Open Request a copy |
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