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<span lang="EN-US">The Philippines is one of the countries in the world who suffers in different disasters, particularly natural disasters. Every year, there are more than twenty incidents recorded in the country related to different disasters which involve numerous lives of its citizens. It is found that most Filipinos have lack of knowledge in terms of disaster preparation specially, teenagers. This paper intended to develop a mobile-based game that aims to spread awareness on what to do during disasters. Upon development, forty-five (45) respondents were chosen to test the reliability of the application which composed of elementary students, household owners, police officers, fire fighters and IT experts. Further, ISO 25010 was adapted and modified in assessing the project. The results showed that the application is strongly acceptable and gives appropriate output in terms of disaster preparation garnering a total mean of 3.83<br /></span>

A fire incident is a devastating event that can be avoided with enough knowledge on how and when it may occur. For the past years, fire incidents have become a big problem for the Philippines, since it affects the socio-economic growth of the country. Machine learning algorithm is a well-known technique to predict and analyze data. It can also be used to recognize pattern and develop models for artificial intelligence. Pattern recognition through machine learning algorithm is already established and have proven itself accurate in different fields such as education, crime, health and many others including fire incidents. This paper aims to develop a model for recognizing patterns of fire incidents in the province of Laguna, Philippines implementing a machine learning algorithm. With the foregoing project, it is found out that a recurrent neural network shows an astonishing result in terms of pattern recognition. Further, it is also found that Calamba City is the most vulnerable area in case of fire occurrence in the Province of Laguna.

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