Space Apps Challenge 2018

Project Description:

Despite all the love that Mother Nature provides us on a daily basis,

humans remain a not very obedient children and in 90% of the time, theylight the first fusefor wildfires, and then they indeed become wild creaturesrunning at as fast as fast as 10.8 kilometers per hour in forests and 22kilometers per hour in grasslands (Wikipedia). However, significant effort andresearch has been deployed in purpose of detecting the early signs aiming toprevent what could lead to a huge loss of ecological systems and in turn hugeimpact on the our planet.

Contributing to this noble striving, we utilized the technology offered inour hands to build a system that involves the community members also in thiscause. PROJECT NAME is a mobile app that allows users to share theirobservations on wildfires happening (or about to happen) in their region.

These insights include: photos, video recordings, and text (e.g.:coordination)

How it works?

Detect & Verify Step:

The mobile app receives the fire detection data from the server that is insynchronization with NASA Fire Information for Resource Management System(FIRMS), the two on-board satellite (satellites: Terra and Aqua) imageprocessing algorithms that FIMRS provide (MODIS and VIIRS) to detect wildfireprovide two types of confidence levels numeric for the first (from 0% to 100%)and classes for the second (low-nominal-high), we chose to go with thenumerical values to define our thresholds and assign them to classes: https://earthdata.nasa.gov/faq/firms-faq#ed-confidence

Which are: low (potential starting wildfire), nominal (fire at earlystages), high (fire already spreading)

The users will receive an alarm on the close potential wildfire places thathave an assigned class (discussed above). Additionally, the mobile app user canscan a wider region for potential wildfires locations and will be able to viewthe class assigned to the location. The user then reacts by capturing info onthe wildfire, this info (photos mostly) will be checked with a machine learningalgorithm that we trained using IBM Watson (currently it can distinguishnominal to high stages of wildfire)

Alarm Step:

If the user photo passes the test, an alarm will sent to all connected usersin the same region calling them to react to the wildfire and help the communitywith their data. We also aim to send an alarm to the authorities especially thefirefighting road traffic department in order to have an updated insight on theincident and –if needed- direct the traffic away from the potentially impactedareas.

React Step:

Despite the phenomenal efforts and the advanced AI level used, algorithms(MODIS or VIIRS) can fail due to several reasons related to satelliteoverpasses or cloud, heavy smoke cover( e.g: The California Wildfires) https://earthdata.nasa.gov/faq/firms-faq#ed-not-detected

So we are obliged to think of a plan in minimize the human suffering in caseeverything got out of control. The app allows facility owners such as(warehouses, schools, campuses, restaurants, hypermarkets, and even households)to register themselves to the app as Community Heroes, thanks to those heroes,people affected by the wildfire (or..yes you thought of it… any other typenatural disaster) will be able to use an off-line pre-loaded map (that had beenfrequently updated with new heroes join who joined) to be directed to theclosest shelter! At the end, we, children of nature, need to come together whenMother Nature gets mad at us. Those heroes will be rewarded first of all bybeing true real life heroes, and also by having some certain amount of tax cutor other incentives (everybody needs a tangible motivation!)

All the code done to support the proof of concept for the project isavailable on our GitHub repository and is licensed to be open-source.

image Server => https://github.com/mohsenmgr/imageServer.git
Mobile App => https://github.com/mohsenmgr/mobileSpaceApp.git
Website => https://github.com/mohsenmgr/SpaceWebsite.git