Engineering student looking for a team to create a mobile navigational application with alternative route using bayesian network depending on flood heights in flood prone areas and a localized map. The flood station will determine flood levels in the different prone areas the City as well as major throughfares affected by low lying areas also said that Data from the flood station will be sent to the server and will be analyzed to generate alternative routes. Using the gathered data, a list of alternative ways, in consideration of Friendship routes accessible by 6:00 AM to 9:00 PM, will be generated using the prediction model from Bayesian Network; it will consider the shortest path in terms of distance travel. All friendship routes are available for Las Piñeros only and will be checked upon using a cross-platform mobile navigational app so users may access information such as alternative routes, nearest barangay halls, evacuation centers, and emergency hotlines. Local Executive Chief down to barangay level may access the data to use for decision making on disaster mitigation and prevention plans. Physical security of the flood station will be monitored by the barangay and visual notification for the flood station will be installed in case the area is totally impassable. Users with smartphones that downloaded the specially built program will be granted access to the framework. The thesis is only applicable to the locale; other regions have been through the same phase as the research field. If all fields are submerged, the machine is only useful for determining the flood depth and visual notification. Multiple sensors were mounted in the locale to detect flooding in different areas. As network coverage is lost due to severe natural or man-made disruptions, the device automatically slows down or becomes unavailable.