Effective Management of Parking Area
Suguna M1, Shobana G2, Mohana Priya P3, Kishore R4
1Suguna M, Assistant Professor II, Department of CSE, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
2Shobana G, Assistant Professor II, Department of CSE, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
3Mohana Priya P, UG Student, Department of CSE, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
4Kishore R, UG Student, Department of CSE, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 30 September 2019 | Revised Manuscript received on 12 November 2019 | Manuscript Published on 22 November 2019 | PP: 1538-1539 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F12760986S319/19©BEIESP | DOI: 10.35940/ijeat.F1276.0986S319
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© 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: When a car enters the parking area, it takes so much time to find the free slot to park. On the other hand, all the paid parking area owners suffer from handling congestion inside the parking area. They are spending huge amount as a salary for their employees to manage the parking area. So there is huge need for effective management of parking area.So the proposed system describe a method to automate the management of car parking area without manual traffic workers i.e., it discusses a project which presents a miniature model of an automated car parking system that can regulate and manage the number of cars that can be parked in a given space at any given time based on the availability of parking slot. By using the logic which is given in the database the parking space is effectively managed. This proposed system is suitable for implementing in all paid parking areas such as in malls, hospitals, etc.
Keywords: Congestion, Reducing The Manpower, Parking Slot Allocation, Image Processing.
Scope of the Article: Data Management