The name of our project is "Wildfire". This is an Android platform application. the basic concept is detecting fire from satellite data. There are two types of data set is being used. one is near-real-time data and archival data-sets provided by NASA Firms. There are also many machine learning algorithm, Artificial Intelligence, Image processing, IoT, mobile computing, cloud services etc were used to make this project. lets discuss each feathers briefly here,

1. We have used NASA API and near-real-time data-set to detect the fire. In this process we are using data-analysis technique, machine learning algorithm for the detection.

2. The app is going to notify the nearest firefighter automatically by the system itself after detecting a fire breaking out.

3. The app will also notify the people from near and far automatically and opens a instant forum among them.

4. There will be predictions based on the archival data-set and near-real-time data-set. The prediction will be made by machine learning algorithm (decision tree of random forest algorithm).

5. There will be two types of predictions. One is predicting the fire spreading direction and another one is predicting the alerted place where fire could break out at any time. the last one is done by archival data-set.

6. There will be information about the fire incident from the past records. This past data will be collected from NASA's archival data-set.

7. There will be information about the temperature of the spot, how much far the firefighters can reach, how high a dron or airforce can survive, smoke density etc. Also these data will be collected from NASA near real time data-set.

8. Live weather condition update of the spot, wind directions, nearest water supply etc information will also be given for the help of the firefighters.

9. For the help of firefighters there will be shortest path to reach the spot on the map. The map and the data will be collected by NASA Firm and their APIs.

10. Any one can report a fire incident by uploading image or video or text etc. The system will automatically cross check the report and send a feedback to the user. if the report find the incident is truth then previously discussed steps will be taken by the system automatically. Image processing , machine learning algorithm and also API will be used for this process.

Github link: https://github.com/Smueez/wildfire

11. Datasets/APIs are being used

i. OpenNex (Predicting future fire occurences)- https://opennex.org/

ii. Fire Information for Resource management System (FIRMS) (Near real time fire occurences)-https://firms.modaps.eosdis.nasa.gov/map/

iii. NASA WorldWind (Wind direction)-https://worldwind.arc.nasa.gov/web/docs/

iv. InciWeb (For archival datasets)-https://inciweb.nwcg.gov/

v. NASA Neo (For NASA earth observation) - https://neo.sci.gsfc.nasa.gov/

vi. Open Weather Api (For showing local weather) - https://openweathermap.org/api