| Title |
Intelligent Method For Selecting Business Location In Smart City |
| ID_Doc |
32432 |
| Authors |
Lipianina-Honcharenko K.; Sachenko A.; Semaniuk V.; Badasian A.; Kopania L. |
| Year |
2023 |
| Published |
Proceedings of the IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS |
| DOI |
http://dx.doi.org/10.1109/IDAACS58523.2023.10348823 |
| Abstract |
Selecting an optimal location for businesses in smart cities poses a challenging task. In this study, an intelligent method leveraging machine learning is developed to facilitate swift and precise location selection. The results of this method can assist entrepreneurs in identifying prime locations to initiate their businesses, ensuring customer satisfaction and increased profits. The intelligent method stands as a potent tool for addressing location selection challenges in smart cities. During the experiment, it was found that the categories of 'Books' (with 158 mentions), 'Technology' (with 118 mentions), and 'Fashion' (with 105 mentions) are the most popular among passersby near the video camera location. The results indicate the viability of starting businesses related to these three sectors in the given smart city location. However, to achieve greater accuracy in the method, additional research and testing on different cases are recommended to enhance and expand its applicability. © 2023 IEEE. |
| Author Keywords |
business startup; image recognition; intelligent method; machine learning; segmentation; smart city |
