IoT-Based Air Quality and Sound Intensity Monitoring System using Raspberry Pi
Nanda M B1, Madhura K2, Chathurya K3, Laxmi Tripathi4
1Nanda M B*, Assistant Professor, Department of CSE, Sapthagiri College of Engineering, Bangalore, India.
2Madhura K, Student, Department of CSE, Sapthagiri College of Engineering, Bangalore, India.
3Chathurya K, Student, Department of CSE, Sapthagiri College of Engineering, Bangalore, India.
4Laxmi Tripathi, Student, Department of CSE, Sapthagiri College of Engineering, Bangalore, India.
Manuscript received on May 25, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 30, 2020. | PP: 126-130 | Volume-9 Issue-2, July 2020. | Retrieval Number: B3207079220/2020©BEIESP | DOI: 10.35940/ijrte.B3207.079220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In day to day life, the increase in Air and Sound pollution has become a distressing problem. It has now become a vital issue that is to be considered. To overcome this problem, an IoT based system to monitor the pollution levels constantly has been proposed. Nowadays Internet of things (IoT) is one of the most widely used and researched technology to monitor the environmental changes. It gives an innovative approach where various devices can be connected together with the use of the internet. By interconnecting different objects located at different locations, we can collectively analyze the data at a single place. This feature is useful in data analytics. Raspberry Pi mini-computer is used to collect different data from different sensors and this data is monitored. In our proposed system we are using four different modules namely Air Quality Monitoring System, Sound Intensity Monitoring System, Cloud based Monitoring System, Notification system. These modules are integrated together to monitor the environmental changes. This system can be implemented in remote areas where the bulky equipment cannot be placed. Industrial areas where the pollution levels are high can be constantly monitored and precautionary measures can be implemented if the pollution is more.
Keywords: IoT, Raspberry Pi, Air Quality Monitoring, Sound Intensity Monitoring, Cloud storage.