Idea - FICS

DCAT

Team and Contact Details

Student Name School Degree Year Email
Qurat-ul-ain fatimaSCEEUndergraduateFourthqfatima.be17igis@igis.nust.edu.pk
M. Ahmed HanifSCEEUndergraduateFourthmahmad.be17igis@igis.nust.edu.pk
Syed Muhammad TalhaSCEEUndergraduateFourthmtalha.be17igis@igis.nust.edu.pk

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

Idea Name: DCAT
Slogan: Disaster-categorization using AI and Twitter
Supervisor Name: Junaid Aziz Khan
Supervisor Designation: Professor
Supervisor School: SCEE
Supervisor Department: IGIS
Contact number: 03453587770
Email ID: junaid@igis.nust.edu.pk
Abstract:
    Identify disasters using extracted and classified information from Tweets .The classified data is mapped showing points of occurrences of disasters.This helps in visualizing disasters as they occur.
What is the unmet need in society that your idea will fulfill ?
    Our idea aims to aid the process of disaster response times and relief by accurately highlighting disaster impacted regions using social media and GIS as its main components. It aims to provide routing for response teams and resource distribution for the affectees.
Who needs it ? How many would benefit ?
   Our system is aimed to be user friendly and intuitive for normal user. as it categorizes tweets in real time implemented in Departments like NDMA, 1122 and others that aim in the process of disaster relief. this system will decrease the impact to response time with timely notifications.
How will the solution works
    Using disaster related hashtags,tweets are retrieved from the Twitter API and fed to NLP based models.Disaster related tweets will train the models and which will be applied to realtime data.A damage summary is also prepared from the information extracted for different categories of damage.Location data is derived from tweet text as well as geoparsing tweet text and geocoding the location.A map is developed showing disaster occurrences on a map with a userfriendly UI and an application
Who are your competitors ? How is your solution different
    Unlike other disaster response systems, DCAT relies on social media combined with GIS and machine learning to produce a response system which greatly enhances the process to identify the regions affected by disasters in real time and timely inform respective teams for appropriate actions.
Status: new
Entry Date & Time: 2021-01-10 (1021)