Smart Real Estate Decision (S-RED)

Project Title

Smart Real Estate Decision (S-RED)

Project Area of Specialization Computer ScienceProject Summary

Buying a real estate property is a stressful and time taking major financial decision; buyers have to search many real estate web sources to find finest demands, property area, location etc. The main idea of S-RED is to provide a platform to real estate property buyers where they don’t need to search real estate property advertisements on different online web sources. With the help of machine learning algorithm and web scraping technology this application extract data from various websites and provide the best real estate advertisement which meets the user requirements. Moreover, this application also predicts the expected future value of the property based on growth rate to support buying decision making. S-RED is a property buying decision-making system based on machine learning and web scraping technology. In this project, we use web scraping technology and machine learning algorithm. Web scraping is a modern technique used in any language such as C# to extract data from a website. Same advertisement from different website on different prices, it is very difficult and time-consuming decision for the buyers. This application will show the best result according to the buyer and also support graphical representation of the expected future growth rate of the property.

Project Objectives

The objectives of the proposed approach are given below:

• Accurately predict property value.
• Offer better recommendations. 
• Collecting data from all most viewed sites and merge for user which helps user to get knowledge easily.
• Predicts the expected future value of the property based on growth rate to support buying decision making.

Project Implementation Method

In this project, we will collect data from different websites with the help of "HTML agility pack" which is used to extract the real estate data from numerous web sources and stored in the database. Then will make a query according to the buyer's requirement or apply the query for fetching the relevant data from website and for the support of the buyer's decision, we will predict the expected future growth value of the property with the help of machine learning algorithm.

Software: Visual Studio 2019, SQL and IIS Web Server for hosting.

Technology: Web scrapping, HTML Agility Pack.

Benefits of the Project

The benefits of the project are given below:

• Exchange information more easily.
• Secure the precious time of the people.
• Proper guidance of the property.
• Secure money of the people.

Technical Details of Final Deliverable

The project S-RED is a website designed on Asp.net MVC technology using visual studio software. The main idea of S-RED is to provide a platform to real estate property buyers where they don’t need to search real estate property advertisements on different online web sources. In this project, we will collect data from various websites and stored in the database. And then we will make a query according to the buyer's requirement and for the support of the buyer's decision, we will also predict the expected future growth value of the property.

With S-RED, users will be able to see different property rather than seeing same advertisement from different website on different prices, it is very difficult and time-consuming decision for the buyers. This application will show the best result according to the buyer.

Final Deliverable of the Project Software SystemCore Industry FinanceOther IndustriesCore Technology Artificial Intelligence(AI)Other TechnologiesSustainable Development Goals Decent Work and Economic Growth, Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	21336
RAM	Equipment	1	10121	10121
SSD	Equipment	2	3600	7200
Domain	Equipment	1	4015	4015
Proprietary software license	Miscellaneous	1	0	0