Reliability analysis of an IoT-based smart parking application for smart cities
Abstract
The proliferation of Internet of Things (IoT) devices demands robust structures for processing and storing trillion gigabytes of data. Part of those data can be used for evaluating the solution's effectiveness and to improve it. Hence, a reliability analysis based on the solution's produced data is important to validate it and find weaknesses to solve. Therefore, in this paper we process the data generated by a sensor-based smart parking system to present a reliability analysis. This system is implemented placing ultrasonic sensors, a web service, the FIWARE platform, and a mobile application to Android devices, in a three-layer architecture. We evaluate how many errors occur in a certain time window, the success and error rates and the most common kind of error produced. Finally, we conclude that even with some instability our sensing approach is effective with a worst case success rate greater than 96%. Moreover, we find out that our system works in an open environment with tropical climate conditions.
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In [68], a reliability analysis of a smart parking system resulted in a success rate greater than 96%.
“A reliability analysis of a smart parking system is conducted in [68], resulting in a success rate greater than 96%.”
From A Review of Machine Learning and IoT in Smart Transportation (2019) · cites this paper as [68]
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A Review of Machine Learning and IoT in Smart Transportation
Zantalis, F., Koulouras, G., Karabetsos, S., & Kandris, D. (2019) · Future Internet · doi:10.3390/fi11040094 · Cited by 625 · see citing works
Smart Parking in IoT-Enabled Cities: A Survey
Al-Turjman, F., & Malekloo, A. (2019) · Sustainable Cities and Society · doi:10.1016/j.scs.2019.101608 · Cited by 340 · see citing works
- Authors
- Araujo, A., Kalebe, R., Girao, G., Filho, I., Goncalves, K., & Neto, B.
- Affiliations
- Universidade Federal do Rio Grande do Norte (BR)
- ORCID
- Filho, Itamir
- Venue
- 2017 IEEE International Conference on Big Data (Big Data)
- Publisher
- IEEE
- Published
- 2017-12
- Pages
- 4086-4091
- OpenAlex
- W2783544552
- Cited by
- 30
- References
- 0
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 4 · 2022: 6 · 2021: 1 · 2020: 8 · 2019: 5 · 2018: 2
- FWCI
- 6.34
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Big Data (BigData) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Building and Construction › Smart Parking Systems Research
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Arduino and IoT Applications
- Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
- Keywords
- smart parking, Internet of Things, reliability analysis, ultrasonic sensors, web services, Android application, three-tier architecture, error rate, success rate, tropical climate, smart cities
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