Automating Ticket Validation: A Key Strategy for Fare Clearing and Service Planning

Tuveri, Giovanni; Garau, Marco; Sottile, Eleonora; Pintor, Lucia; Gravellu, Matteo; Atzori, Luigi; Meloni, Italo

doi:10.1109/mtits.2019.8883318

Cited by 10 publications

(3 citation statements)

References 5 publications

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“…This can be achieved by the collection of movement data of a traveler using sensors of the traveler's smartphone in combination with external data sources such as existing bluetooth low energy (BLE)-enabled beacons [164]. BLE technology is the most popular approach to achieving automatic ticketing [165][166][167][168]. By employing BLE, it is possible to completely eliminate the traveler's action during check-in and check-out.…”

Section: Application Of Proposed Architecturementioning

confidence: 99%

“…By employing BLE, it is possible to completely eliminate the traveler's action during check-in and check-out. The traveler's smartphone communicates with either a BLE-enabled on-board device or a device located at a bus stop for seamless check-in/check-out [166][167][168][169]. In these solutions, an application residing on the traveler's smartphone triggers a check-in or check-out event when the traveler enters or leaves the proximity of a BLE beacon.…”

Section: Application Of Proposed Architecturementioning

confidence: 99%

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A Survey of Security Architectures for Edge Computing-Based IoT

Fazeldehkordi

Grønli

2022

IoT

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The Internet of Things (IoT) is an innovative scheme providing massive applications that have become part of our daily lives. The number of IoT and connected devices are growing rapidly. However, transferring the corresponding huge, generated data from these IoT devices to the cloud produces challenges in terms of latency, bandwidth and network resources, data transmission costs, long transmission times leading to higher power consumption of IoT devices, service availability, as well as security and privacy issues. Edge computing (EC) is a promising strategy to overcome these challenges by bringing data processing and storage close to end users and IoT devices. In this paper, we first provide a comprehensive definition of edge computing and similar computing paradigms, including their similarities and differences. Then, we extensively discuss the major security and privacy attacks and threats in the context of EC-based IoT and provide possible countermeasures and solutions. Next, we propose a secure EC-based architecture for IoT applications. Furthermore, an application scenario of edge computing in IoT is introduced, and the advantages/disadvantages of the scenario based on edge computing and cloud computing are discussed. Finally, we discuss the most prominent security and privacy issues that can occur in EC-based IoT scenarios.

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Section: Application Of Proposed Architecturementioning

confidence: 99%

Section: Application Of Proposed Architecturementioning

confidence: 99%

A Survey of Security Architectures for Edge Computing-Based IoT

Fazeldehkordi

Grønli

2022

IoT

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“…In 2004, in Switzerland, "ATRON" showcased a CIBO prototype, which used a WLAN antenna [10]. In 2007, the Swiss Federal Railways issued a "Request for information" to the industry, to identify a BIBO solution for all national public transport [10], which led to the development of two CICO smartphone apps [11,12].…”

mentioning

confidence: 99%

Beep4Me: Automatic Ticket Validation to Support Fare Clearing and Service Planning

Tuveri

Garau

Sottile

et al. 2022

Sensors

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An integrated transport service fare system, supported by an agreement for ticket revenue sharing among service providers, is an essential component to improve the experience of the users who can find single tickets for the integrated transport services they look for. A challenge is to find a model to share the revenue which all providers agree on. A solution is to adopt data-driven approaches where user-generated data are collected to extract information on the extent each transport service was used. This is consistently used. However, it suffers from incomplete data, as not all users always validate their ticket when checking out or when switching lines. We studied all technologies available to support automatic ticket validation in order to record when the users access and exit each service line. The contributions of this work are the following: we give an in-depth description of the inner workings of this novel approach describing how we take advantage of each technology; we present the developed solution (Beep4Me), which adds new functionalities to an existing mobile ticketing platform; and we describe our testing framework, which includes most cases users might encounter during a trip. Our results demonstrate how it is possible to collect key data related to validations which can be used first for clearing purposes and then for network planning/fleet optimization.

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