FoFi: The Development of a Handheld Monitoring Device in Predicting Naturally Occurring Forest Fires
Document Types
Paper Presentation
School Code
N/A
School Name
De La Salle University Integrated School, Biñan City, Laguna
Abstract/Executive Summary
Forest fires, which are natural or artificial burning of woodlands, negatively affect people and the environment. In the Philippines, Cordillera is one of the hotspots for forest fires, with approximately 122 forest fire incidents. Thus, developing a monitoring device for the early prevention of forest fires would reduce these incidents' frequency. This research aimed to create a handheld prototype device, FoFi, that gathers quantitative data which can be used with the Department of Natural Resources's data science and predictive analytics. Using an Arduino Microcontroller and sensors, the device will collect and send data. Two phases were conducted to create a monitoring prototype device for predicting forest fires. According to the results, the temperature and humidity (DHT-22) sensor showed reliable data since it can detect temperature under normal conditions, having a mean of 30.65°C; also, it precisely recorded the relative humidity with a mean of 7.89%. The Global Positioning System (GPS) module obtained a mean error of 7.251 m, which exhibited accuracy in detecting GPS coordinates. Additionally, the Globe SIM showed efficiency for Global Systems for Mobile (GSM) communication since the mean length of time for sending a message is 5.022 s. On the other hand, the gas sensor (MQ-2) and photoresistor lacks sensitivity when used; thus, a more sensitive sensor is recommended. In conclusion, the handheld device was able to achieve its purpose of monitoring forest fires.
Keywords
forest fires; handheld monitoring device; arduino microcontroller
Research Theme (for Paper Presentation and Poster Presentation submissions only)
Computer and Software Technology, and Robotics (CSR)
Initial Consent for Publication
yes
FoFi: The Development of a Handheld Monitoring Device in Predicting Naturally Occurring Forest Fires
Forest fires, which are natural or artificial burning of woodlands, negatively affect people and the environment. In the Philippines, Cordillera is one of the hotspots for forest fires, with approximately 122 forest fire incidents. Thus, developing a monitoring device for the early prevention of forest fires would reduce these incidents' frequency. This research aimed to create a handheld prototype device, FoFi, that gathers quantitative data which can be used with the Department of Natural Resources's data science and predictive analytics. Using an Arduino Microcontroller and sensors, the device will collect and send data. Two phases were conducted to create a monitoring prototype device for predicting forest fires. According to the results, the temperature and humidity (DHT-22) sensor showed reliable data since it can detect temperature under normal conditions, having a mean of 30.65°C; also, it precisely recorded the relative humidity with a mean of 7.89%. The Global Positioning System (GPS) module obtained a mean error of 7.251 m, which exhibited accuracy in detecting GPS coordinates. Additionally, the Globe SIM showed efficiency for Global Systems for Mobile (GSM) communication since the mean length of time for sending a message is 5.022 s. On the other hand, the gas sensor (MQ-2) and photoresistor lacks sensitivity when used; thus, a more sensitive sensor is recommended. In conclusion, the handheld device was able to achieve its purpose of monitoring forest fires.
