Parking diversion method based on Internet of Things and multi-word combination

Abstract

Abstract With the continuous improvement of living standards, motor vehicles have become an indispensable transportation in our daily life. The number of cars in each city continues to rise, causing variable degrees of parking difficulties in different regions. It has become a common phenomenon that no parking spot near popular places. With this, there are long queues of vehicles in front of the parking lot, which delays the time of car owners and causes traffic jams. This article introduces a new parking diversion method, based on the support vector machine (SVM) and simulated annealing fruit fly optimization algorithm forecasting models to predict short-term traffic flow near the parking lot. Through predictions, recommending parking lots with low traffic flow for car owners. Meanwhile, the method based on the Internet of Thing to lock pots, let vehicles enter according to the queue number and so on. Through this way, achieving online queuing and advance reservation. This method can solve the queuing phenomenon in front of the parking lots and give car owners the most suitable travel time, therefore, park will be more orderly and diversion will be realized.