• Sachin Bhardwaj

This study focuses on a serious issue that affects a large portion of India and the rest of the world. The study focuses on the major issue of traffic congestion and road accidents, which is primarily caused by poor parking management. As a result, having a well-managed parking infrastructure is required in all cities. However, many studies have been undertaken in the past in order to provide a solution that leads to a good smart paring method. After learning more about the previous studies, it became evident that each study has its own set of advantages and disadvantages. This paper reflects on the study undertaken to design an algorithm that leads to a cloud-based smart algorithm that is secure and convenient enough to develop a system that can be used to manage available slots and can alert users about available parking slots to the client in advance. The study also concentrates on the result analysis section, which clearly demonstrates that the algorithm developed is more accurate than previous methods. Our technique is based on ACO, decision trees, and cloud-based GPS mapping. The goal of this study was to develop a cost-effective solution that benefits a vast number of people while also maintaining peace and order.

Ant Colony, Optimization, Decision tree, Smart Parking, GPS Mapping.

"A Parking System for Smart Cities Based on Cloud computing &Machine Learning Using the Ant Colony Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.a731-a734, May-2022, Available :http://www.jetir.org/papers/JETIR2205096.pdf

"A Parking System for Smart Cities Based on Cloud computing &Machine Learning Using the Ant Colony Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppa731-a734, May-2022, Available at : http://www.jetir.org/papers/JETIR2205096.pdf