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#Apps like firestream verification
#Apps like firestream code

The team would also like to incorporate weather and traffic APIs in order to inform users of potential danger areas as well as the routes to avoid them. Data centers then automatically process the data and alert authorities in case of crisis. The project was developed using XCode for iOS development, using the python language, the IBM Watson Developer Cloud for the machine learning model, and Adobe illustrator for art work and design.įor future works the team would like to integrate smart sensors into both populated and unpopulated danger areas in order to collect constant information and send it to data centers. Machine learning is used in order to identify wildfires.Once a report has been made users within the area are alerted, along side with authorities.Users may check the vicinity for existing and active fires.Users may report a fire by either uploading a pre-shot photo or live.The map with pins of wildfires around the world can be viewed.

#Apps like firestream verification

User verification is done using phone numbers.

Colours are used to indicate the number of wildfires within a region, and as a user zooms into the map the fire pins begin to de-cluster allowing a user to view specific locations with reported wildfires. The application allows users to view pictures of active fires as they are being uploaded. Being a dual-slot card, the AMD FireStream 9270 draws power from 2x 6-pin power connectors, with power draw rated at 160 W maximum. The GPU is operating at a frequency of 750 MHz, memory is running at 900 MHz (3.6 Gbps effective). Users may view specific pictures of fire in pinned locations on the map, however they will not be able to manipulate the data since it is automated. AMD has paired 2,048 MB GDDR5 memory with the FireStream 9270, which are connected using a 256-bit memory interface. Reports are uploaded to a database that all users can access through the application. It is important to note that Firebase was used as a database to store and retrieve information about wildfire locations.

#Apps like firestream code

The source code and screenshots from the project was uploaded to github and can be accessed through the URL. By allowing the user to simultaneously alert authorities and other users the evacuation process, in the case of confirmation, will be much easier and at a faster rate. Usually when reporting a wild fire the time line goes as follows: Users make a phone call, emergency call centers answer and report the fire, authorities are alerted and respond accordingly, once the rescuers arrive at the scene of the fire the local area citizens begin to evacuate.įireWatch however allows users to merge two steps into one. Furthermore, the manpower needed to put out a fire can be determined through inspection of the images.

FireWatch monumentally reduces the time it takes to report and rescue by allowing users to take photos of wildfire and alerting every other user within the vicinity of it, along with the appropriate rescue units needed. On average, it takes two to three hours for a satellite to recognize, confirm, and report a wildfire before response units can take action. The application uses machine learning for image recognition, allowing for early and instantaneous wildfire detection. The project is an iOS application that uses crowd sourcing as a tool to allow any user to report a fire.