Realtime Monitoring and Analysis Based on Cloud Computing Internet of Things (CC-IoT) Technology in Detecting Forest and Land Fires in Riau Province

Autor: Yuda Irawan, Rometdo Muzawi, Agus Alamsyah, Reno Renaldi, Elisawati Elisawati, Nurhadi Nurhadi, Mohd Rinaldi Amartha, Abdullah Mitrin, Hadi Asnal, Zupri Henra Hartomi
Jazyk: English<br />Indonesian
Rok vydání: 2023
Předmět:
Zdroj: Ilkom Jurnal Ilmiah, Vol 15, Iss 3, Pp 445-454 (2023)
Druh dokumentu: article
ISSN: 2087-1716
2548-7779
DOI: 10.33096/ilkom.v15i3.1636.445-454
Popis: Forest and land fires in Riau are natural disasters that always repeat every time they enter the dry season. The solution of this research is to apply the leading technology of cloud computing internet of things (CC-IoT) to find out more quickly the existence of forest or land fires. This study uses Particle Argon (Photon) to connect to the internet and several IR Fire Detector sensors, DHT22 MQ2 and GPS Neo 6m. Particle Argon can receive input and perform processing so that it is connected using the CC-IoT concept to a web server so the users can monitor land conditions in real time. Based on the test results, it can be concluded that a fire detector using fire parameters (2000 = Normal and 2000 = Danger) , temperature (≤37 = Normal, 38 – 45 = Alert, and 46 = Danger), humidity (≤50 = Dry, 51 = Humid) , smoke (≤ 1700 = Normal, 1700 = Danger), and soil moisture can work well ( 3500 = Dry Moisture Content, 1500 to 3500 = Medium Moisture Content, and 1500 = High Moisture Content). The fire detection tool developed can detect fires in real time and also has a fire early detection function that is useful for anticipating land conditions to prevent fires. The results obtained from the test are that the sensor can read indications of fire, smoke, soil moisture with a success rate of 93% and send location data and sensor values to the website. The use of sensors has their respective roles so that if there is a problem with one of the sensors, the tool has an alternative sensor and can continue to function.
Databáze: Directory of Open Access Journals
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