Stationed Automotive’ s Surveillance of Streets for Smart City

Abstract: Traffic congestion is a common hindrance which is caused mainly due to automobiles parked in “No Parking” areas knowingly or unknowingly. Analogously, the police vehicles need to monitor these areas which further adds pollution and congestion into the system. Therefore, we propose a Deep Learning based solution which can monitor vehicular movements. This involves vehicle and number plate recognition through which the owner’s details are fetched, and warning messages are sent after a certain time specified by the governing body. Meanwhile, the local police authorities are notified about the wrongly parked vehicle, allowing them to easily tow it, thus saving a lot of human and fuel resources which also in the process reduces the pollution. A Graphical User Interface is provided at the local police stations to display various traffic violations and status across the city. Keywords: Deep Learning, Traffic Monitoring System