Electronic Toll Collector Framework

• Autorzy: Mujeeb Abdul , Ahmed Nisar , Arshed Husnain , Khan Farhan Ajmal

Identyfikatory

DOI

10.12913/22998624/144537

• Języki publikacji: EN

Abstrakty

EN

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 are 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.

Słowa kluczowe

EN

electronic toll collector; TensorFlow; Yolov2; image classification; analytics; centralized system

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2022
• Tom: Vol. 16, no 1
• Strony: 294--302
• Opis fizyczny: Bibliogr. 15 poz., fig., tab.

Twórcy

autor

Mujeeb Abdul

• Engineering in Computer Science, DIAG, Sapienza University of Rome, Rome, Italy

• https://orcid.org/0000-0002-2933-8502

autor

Ahmed Nisar

• Department of Computer Science, Sapienza University of Rome, Rome, Italy

• https://orcid.org/0000-0002-9352-2195

autor

Arshed Husnain

• Department of Computer Science, Sapienza University of Rome, Rome, Italy

autor

Khan Farhan Ajmal

• Department of Artificial Intelligence, Sapienza University of Rome, Rome, Italy

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