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IoT Enabled Air Quality Monitoring System (AQMS) using Raspberry Pi


Affiliations
1 School of Computing, Embedded System, SASTRA University, Tirumalaisamudram, Thanjavur - 613401, India
 

Background/Objectives: Air pollution due to vehicular and industrial emission has become menace to the living beings. Due to this menace both indoor and outdoor air quality monitoring in real time has become mandatory. Methods/ Statistical Analysis: The evolution of Internet of Things (IoT) and Single Board Computers (SBC) has made real time remote monitoring as a ubiquitous process. Remote monitoring was facilitiated using classical motes in the past, which has some pitfalls like limited memory, processsing speed and complex programming strategies. This paper portrays the usage of SBC for integration of IoT with WSN for Air Quality Monitoring System (AQMS), where SBC are capable of performing even complex task with enhanced speed and reduced complexity. The integration of cloud services with SBC makes alerting process smart and realtime. Findings: With the review and realizing of immense literature in the field of WSN for air quality management, the design of sensor web node becomes essential. The evolution of SBC adds merit towards monitoring and measuring of the critical factors in centralized Air Quality Monitoring System (AQMS) in any plant. Sensor web node is proposed with commercial gas sensors for detecting the gases like CO, CO2, NH3 and NOx to monitor both indoor and outdoor air quality. The observed results are properly evaluated using ThingSpeak open source IoT platform. The integration of open source cloud services for SBC in this proposed prototype model confirms low cost, comfort, convenience and rapid prototyping for flexible AQMS. Applications/Improvements: This prototype can be easily adapted to any monitoring systems with minor changes and can be made scalable for tomorrow.

Keywords

AQMS, IoT, Raspberry Pi, SBC, ThingSpeak, WSN.
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  • IoT Enabled Air Quality Monitoring System (AQMS) using Raspberry Pi

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Authors

C. Balasubramaniyan
School of Computing, Embedded System, SASTRA University, Tirumalaisamudram, Thanjavur - 613401, India
D. Manivannan
School of Computing, Embedded System, SASTRA University, Tirumalaisamudram, Thanjavur - 613401, India

Abstract


Background/Objectives: Air pollution due to vehicular and industrial emission has become menace to the living beings. Due to this menace both indoor and outdoor air quality monitoring in real time has become mandatory. Methods/ Statistical Analysis: The evolution of Internet of Things (IoT) and Single Board Computers (SBC) has made real time remote monitoring as a ubiquitous process. Remote monitoring was facilitiated using classical motes in the past, which has some pitfalls like limited memory, processsing speed and complex programming strategies. This paper portrays the usage of SBC for integration of IoT with WSN for Air Quality Monitoring System (AQMS), where SBC are capable of performing even complex task with enhanced speed and reduced complexity. The integration of cloud services with SBC makes alerting process smart and realtime. Findings: With the review and realizing of immense literature in the field of WSN for air quality management, the design of sensor web node becomes essential. The evolution of SBC adds merit towards monitoring and measuring of the critical factors in centralized Air Quality Monitoring System (AQMS) in any plant. Sensor web node is proposed with commercial gas sensors for detecting the gases like CO, CO2, NH3 and NOx to monitor both indoor and outdoor air quality. The observed results are properly evaluated using ThingSpeak open source IoT platform. The integration of open source cloud services for SBC in this proposed prototype model confirms low cost, comfort, convenience and rapid prototyping for flexible AQMS. Applications/Improvements: This prototype can be easily adapted to any monitoring systems with minor changes and can be made scalable for tomorrow.

Keywords


AQMS, IoT, Raspberry Pi, SBC, ThingSpeak, WSN.



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i39%2F126393