Idea Details

Team and Contact Details

SNo Student Name School Degree Year Email
1Muhammad Fasi ur RehmanSCEEUndergraduateFourthfasiulrehman@gmail.com
1Waleeja Binte IqbalSCEEUndergraduateFourthwaleeja@live.com
1Salman RasheedSCEEUndergraduateFifthsalmanjutt222@gmail.com
1Umair RamaySCEEUndergraduateThirdumairshabr@gmail.com
1Muhammad Kamran KhalidSCEEUndergraduateThirdkamrrnn@gmail.com

Inter School Idea ? Yes
Do you need expertises from another area: Yes
If Yes please provide details of expertises you need: Deep learning/machine learning

Idea Details

Idea Name: Poverty Mapping
Slogan: Map poverty with data science
Supervisor Name: Dr Ejaz Hussain
Supervisor Designation: Associate Dean
Supervisor School:
Supervisor Department: IGIS
Contact number: +92-51-90854400
Email ID: ejaz@igis.nust.edu.pk
Abstract:
    Poverty is the scarcity or lack of a certain amount of material possessions or money. It is a multifaceted concept, which may include social, economic and political elements.
What is the unmet need in society that your idea will fulfill ?
    There are many obstacles that limit the effectiveness of traditional survey approaches mainly due to limited access to an area or other social conditions. We propose to extract socioeconomic indicators using high resolution satellite imagery and machine learning.
Who needs it ? How many would benefit ?
   The beneficiaries of the project include the following: 1- Policy makers such as Planning Commission of Pakistan 2- Government and non-Government Organizations (NGO’s) that are fighting poverty
How will the solution works
    Spatial indicators(access to Health,education etc) and non spatial indicators(access to clean water, access to cooking fuel etc) are used. Weights are assigned to each indicator and poverty is estimated. High resolution images are used to find the quality of houses in the study area and a classifier is trained by giving training samples through machine learning.
Who are your competitors ? How is your solution different
    1). Urban Unit 2). Pakistan Bureu of Statistics We are doing the survey without going door to door.
Status: Approved
Entry Date & Time: 2017-11-30 (2335)