Electronic Toll Collector Framework

被引:0
|
作者
Mujeeb, Abdul [1 ]
Ahmed, Nisar [2 ]
Arshed, Husnain [2 ]
Khan, Farhan [3 ]
机构
[1] Sapienza Univ Rome, DIAG, Engn Comp Sci, Rome, Italy
[2] Sapienza Univ Rome, Dept Comp Sci, Rome, Italy
[3] Sapienza Univ Rome, Dept Artificial Intelligence, Rome, Italy
关键词
electronic toll collector; TensorFlow; Yolov2; image classification; analytics; centralized system;
D O I
10.12913/22998624/144537
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Manual toll collection systems are obsolete due to time, fuel, and pollution issues and need to be replaced by new and better alternatives. Traditionally, governments have always employed people to collect toll, but the manual labor isn't much effective when it comes to monitoring and efficiency. We took this problem and researched out an effective solution i.e., "Electronic Toll Collector Framework" which is a framework mainly for collection and monitoring of the toll fees collected by the toll plazas in the vicinity of metropolitan cities like Lahore or Karachi. The software can generate toll tax based on vehicle type. Additionally, it can also generate daily/monthly/yearly revenue reports. The framework can serve other purposes like monitoring of vehicles (by the law enforcement agencies) and generation of analytics. It can also serve as a backbone for the government departments who are having a hard time monitoring the revenue generated by the employers. There am two operational modes of the framework (partly manual and automatic). The partly manual approach uses TensorFlow backend, and the automatic approach uses Yolov2 backend. This work will be helpful in guiding future research and practical work in this domain.
引用
收藏
页码:294 / 302
页数:9
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