Utilizing Raspberry Pi and Internet of Things (IoT) Frameworks for Comprehensive Monitoring of Urban Pollutants and Climate Variables
Thushara Hameed1, Maheswari Maruthakutti2, Pandimadevi Ganesan3
1Thushara Hameed, Lecturer, College of Engineering and Technology, UTAS, Nizwa, Sultanate of Oman.
2Maheswari Maruthakutti, Senior Lecturer, College of Engineering and Technology, UTAS, Nizwa.
3Pandimadevi Ganesan, Lecturer, College of Engineering and Technology, UTAS, Nizwa.
Manuscript received on 30 October 2024 | First Revised Manuscript received on 14 November 2024 | Second Revised Manuscript received on 13 December 2024 | Manuscript Accepted on 15 January 2025 | Manuscript published on 30 January 2025 | PP: 20-26 | Volume-13 Issue-5, January 2025 | Retrieval Number: 100.1/ijrte.E818413050125 | DOI: 10.35940/ijrte.E8184.13050125
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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: Global warming is the effect of a rise in Earth’s climate temperature due to air pollution. Urban areas tend to have higher levels of air pollution than rural areas, mainly due to increased traffic and rapid urban development. In addition to brief health problems like headaches, eye infections, and throat infections, pollution also has lengthy health repercussions like lung cancer and heart disease. As a result, it’s essential to monitor various climatic and pollution indicators, including light intensity, temperature, humidity, air pressure, oxygen and carbon dioxide levels, and camera usage. Using suitable equipment and Internet of Things (IoT) technologies, a pollution and climate monitoring system is constructed in the proposed paper that can measure the parameters above at regular intervals. The system then uploads the data to a webpage in ThingSpeak. The IoT analytics platform service ThingSpeak enables the collection, visualization, and analysis of real-time data streams. The sensors are used to feed data to ThingSpeak, which instantly visualizes the data in a graph. The primary tool for gathering data from the sensors and sending parameters to the website is the Raspberry Pi 3 computer. The software code is developed using Python. By logging on to the website from any location worldwide, users can view the submitted pollution and climate parameters for a specific area.
Keywords: Raspberry Pi 3 Model 3B, DHT11 Sensor, Pressure Sensor, LDR, I2C LCD, MQ2 Sensor, Camera and Thing Speak.
Scope of the Article: Internet of Things (IoT)