论文标题
基于物联网的系统：大型城市交通数据挖掘通过空中污染物的气体分析
An IoT-Based System: Big Urban Traffic Data Mining Through Airborne Pollutant Gases Analysis
论文作者
论文摘要
如今，在包括伊朗在内的发展中国家，由于人口的增长，车辆数量正在增加。最近，这导致浪费时间陷入了交通，花费更多的时间进行日常通勤并增加事故。因此，有必要控制交通警察的交通拥堵，有效地扩大道路，并选择减少公民交通的最佳方法。因此，重要的是要了解每个车道的即时流量。今天，许多交通组织服务，例如交通警察和城市交通管制系统，都使用交通摄像头，电感传感器，卫星图像，雷达传感器，超声波技术和无线电频率识别（RFID）来进行城市交通诊断。但是，这种方法存在一些问题，例如受空气条件影响的严重交通效率低下，无法检测到平行的流量。我们在本文中建议的方法检测到基于物联网中的交通拥堵，该物联网包含一个智能系统，该系统通过计算该地区的空气污染金额来使我们的交通拥堵。根据进行的实验，满足了结果。
Nowadays, in developing countries including Iran, the number of vehicles is increasing due to growing population. This has recently led to waste time getting stuck in traffic, take more time for daily commute, and increase accidents. So it is necessary to control traffic congestion by traffic police officers, expand paths efficiently and choose the best way for decreasing the traffic by citizens. Therefore, it is important to have the knowledge of instant traffic in each lane. Todays, many traffic organization services such as traffic police officer and urban traffic control system use traffic cameras, inductive sensors, satellite images, radar sensors, ultrasonic technology and radio-frequency identification (RFID) for urban traffic diagnosis. But this method has some problems such as inefficiency in heavy traffic influenced by condition of the air and inability to detect parallel traffic. Our method suggested in this article detects traffic congestion based on IOT containing a smart system that gives us traffic congestion by calculating the air pollution amount in that area. According to conducted experiment, the results were satisfied.
