Abstract
The real estate industry is one of the highest income generating sources in the country. As the country moves toward a highly diversified economy, the role of real estate has become a more important part of the country’s economy. However, the state of the local real estate industry is yet to improve and is currently lagging the technology curve. As a result of this issue, useful information is not made available to the end-users. Therefore, the real estate industry needs to improve its adoption of ongoing technologies to move from traditional to smart real estate industry. Therefore, we developed a Smart Real estate system called "Realty Scout" which can analyze and forecast real estate information accurately. The "Realty Scout" is implemented with a highly interactive view of the properties with a given virtual tour for the users to enhance the user experience. This smart real estate system also collects data on property values, in addition to a trained data set, to forecast future property values. Certain machine learning algorithms are used in the backend to generate future values. An accurate and fast prediction of the real estate value is important to buyers, sellers, and other stakeholders. Furthermore, by gathering users’ personal information and tracking their search history through the system, the system recommends properties to users based on collected data. As potential users of the system, they can gain an advantage from this feature by finding their desired property without spending more time. In addition, this system aimed to give advanced property filtrations options to the user. Building up a smart system for the real estate industry would be an advantage for all stakeholders who are actively engaged with the real estate industry.
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