The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Examining Rental House Data With MRL Analysis: An Empirical Approach for Future Perspective of E-Business for Smart Cities and Industry 5.0
Abstract
In today's scenario, we all are surrounded with technologies. As the world is shifting towards technology with great pace, and technology is also showing its efficiency and strength, we must appreciate its power. Now the world is shifting towards digitalization. So, it's also important to think that ideas should lie towards e-business to get full advantage of the system. The housing sector is one of the important fields which must get the support of the technological domains to overcome many challenges. So, there is a requirement to bring a system that can direct the work of renter and customer easier. To bring this idea into the real world, the author's team has come up with the idea of a rental house portal system. This portal is a web application which acts as an e-platform to search flats, apartments, property, etc., with scientific analysis-based data. In this system, the owner provides the details of flats with its features and using ML (machine learning) technology, the price of flat is calculated and the customer can check the availability of flat according to his/her requirement and to provide benefits to both parties. As the details of the flat are available on site, there is no need to explain the features of the house to the owner. Customers also have the benefits of searching for the desired house in less time and at a very reasonable price. Therefore, the rental house system is a very nice step towards the finding of flats online. The present manuscript has new thoughts of prediction of house rent price according to the features provided using statistical techniques and has come as one of the best platforms to search the property at a reasonable price.
Related Content
|
Okina Fitriani, Rozainee Khairudin, Wan Shahrazad Binti Wan Sulaiman, Laila Meiliyandrie Indah Wardani.
© 2024.
16 pages.
|
|
Rinanda Rizky Amalia Shaleha, Nelson Roque.
© 2024.
14 pages.
|
|
.
© 2024.
|
|
Simon Vrhovec, Damjan Fujs.
© 2023.
19 pages.
|
|
Bahri Baran Koçak.
© 2023.
13 pages.
|
|
Gilbert Macalanda Talaue, Ishaq Kalanther.
© 2023.
16 pages.
|
|
Gboyega Emmanuel Abikoye, Abiodun Musibau Lawal.
© 2023.
12 pages.
|
|
|