Smart Parking and Recommendation System Under Fog Calculation

Abstract

Parking is becoming a major problem in urban traffic, and intelligent parking system is an effective way to solve this problem. Intelligent parking system requires high accuracy of local information and strong real-time feedback, which have brought challenges to traditional cloud computing. In this case, a fog computing framework based on the idea of “layered processing” is proposed. The fog layer is close to the data source to ensure that requests and information from users and terminals can be quickly processed and responded by system. This paper designs a smart parking system with parking space and road condition information collection, road condition analysis, parking space reservation, road navigation and parking space guidance functions, and introduces two fog calculations in the intelligent parking system that based on the fog calculation framework, and introduces two typical application scenarios: video detection of license plates and parking spaces, driver parking space recommendations based on big data.