An Approach to Smart Parking Algorithm using ant Colony Optimization and Decision Tree Algorithm
Ankita Yadav1, Mohammad Arif2
1Ankita Yadav*, Department of Computer Science and Engineering, Integral University, Lucknow (U.P.), India.
2Mohammad Arif, Department of Computer Science and Engineering, Integral University, Lucknow (U.P.), India.
Manuscript received on August 01, 2021. | Revised Manuscript received on October 25, 2021. | Manuscript published on October 30, 2021. | PP: 58-63 | Volume-10 Issue-12, October 2021. | Retrieval Number: 100.1/ijitee.J76070891020 | DOI: 10.35940/ijitee.J7607.10101221
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This research is conducted in order to deal with the main problem of traffic congestion and road accidents that is basically caused because of the improper parking management. . Hence, it is important that cities have a well-managed parking system. In the past various researches has been done to design a suitable smart paring algorithm. However, each research had their own pros and cons. Our research leads to a smart algorithm that is secure and is convenient enough to develop a system that can be manage the available slots and can notify the users about the available parking slot beforehand to the client. The result analysis clearly shows that the algorithm proposed and designed is more accurate than other algorithms used in the past. The proposed algorithm is designed using ACO, decision tree, and GPS mapping. The idea of working on this research was to provide a solution that is cost effective, helps people on large scale and maintains the laws and order.
Keywords: Ant colony optimization, decision tree, smart parking system, GPS mapping, smart parking algorithm.
Scope of the Article: GPS and Location-Based Applications