Idea - FICS


Team and Contact Details

Student Name School Degree Year Email
Muhammad Ali

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: SWARP
Slogan: Get Smart Real Estate Assistance
Supervisor Name: Maj Khawir Mehmood
Supervisor Designation: Assistant Professor
Supervisor School: MCS
Supervisor Department: Computer Software (CSE)
Contact number: 03005008293
Email ID:
    SWARP is a web application for real estate prediction based on machine learning algorithm. It will allow its users to predict Real Estate features & detect scam or fraud property listings.
What is the unmet need in society that your idea will fulfill ?
    SWARP will be different from other real estate web apps of Pakistan (Zameen & Graana). SWARP will predict features of real estate & fill the gap the in the buying / selling process of real estate in addition to fraud detection. None of the present website assist users with such type of functionality
Who needs it ? How many would benefit ?
   1) Real Estate Buyers 2) Sellers 3) Tenants 4)Property Owners (Landlords) 5)Real Estate Agents 6)Investors 7)AI Research Community 8) Entrepreneurial Community
How will the solution works
    SWARP will be a web application that will use machine learning techniques. First phase: To generate structured & cleansed dataset (Scraping, data warehousing & Preprocessing ) Second phase: Development of smart web engine using machine learning (Implementation of classical Machine learning techniques & Neural Network) Third phase: Develop a web application for the deployed model (Front end development (Flask) and model deployment (AWS Hosting)) Fourth phase: User Experience & live testing
Who are your competitors ? How is your solution different
    Our major competitors may include all type of real estate web applications working in Pakistan ( / But none of these web applications provide the functionalities provided by the SWARP. (Price predication, features prediction & Fraud detection)
Status: new
Entry Date & Time: 2020-12-19 (1846)