Using Bus Tracking Data to Detect Potential Hazard Driving Zones

Almeida, Ana Margarida; Brás, Susana; Sargento, Susana; Oliveira, Ilídio

doi:10.1007/978-3-031-04881-4_53

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…For the LoRaWAN protocol, the DCUs are based on LoPy4 23 (Figure 4), and the gateways are LORIX One 24 or an extension to the APU board with a mPCIe card. End devices join the network via over-the-air activation (OTAA) and transmit, in most cases, using a spreading factor of 9 and a coding rate of 4/5.…”

Section: A Communication Technologiesmentioning

confidence: 99%

“…The identification of problematic road segments and zones becomes essential to help city managers to improve road safety. Through the mobility data, we proposed a model to classify the driving behavior [24], taking into account the speed of the vehicle, the speed limit, the acceleration, and the road friction. Figure 30 contains the six created categories: the speed indicates if the legal speed limits are respected; regarding safety, stating "within safety domain" means that no sudden changes in the acceleration were measured, in opposition to "outside the safety domain", meaning sudden accelerations or decelerations were performed.…”

Section: Use-case 1: Mobility Characterizationmentioning

confidence: 99%

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Aveiro Tech City Living Lab: A Communication, Sensing and Computing Platform for City Environments

Rito¹,

Almeida²,

Figueiredo³

et al. 2022

Preprint

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This article presents the deployment and experimentation architecture of the Aveiro Tech City Living Lab (ATCLL) in Aveiro, Portugal. This platform comprises a large number of Internet-of-things devices with communication, sensing and computing capabilities. The communication infrastructure, built on fiber and Millimeter-wave (mmWave) links, integrates a communication network with radio terminals (WiFi, ITS-G5, C-V2X, 5G and LoRa(WAN)), multiprotocol, spread throughout 44 connected points of access in the city. Additionally, public transportation has also been equipped with communication and sensing units. All these points combine and interconnect a set of sensors, such as mobility (Radars, Lidars, video cameras) and environmental sensors. Combining edge computing and cloud management to deploy the services and manage the platform, and a data platform to gather and process the data, the living lab supports a wide range of services and applications: Internet-of-things, intelligent transportation systems and assisted driving, environmental monitoring, emergency and safety, among others. This article describes the architecture, implementation and deployment to make the overall platform to work and integrate researchers and citizens. Moreover, it showcases some examples of the performance metrics achieved in the city infrastructure, the data that can be collected, visualized and used to build services and applications to the cities, and, finally, different use cases in the mobility and safety scenarios.

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Section: A Communication Technologiesmentioning

confidence: 99%

Section: Use-case 1: Mobility Characterizationmentioning

confidence: 99%