Abstract
Nowadays, having sensors and getting more data can be irrelevant without real-time insights. This process is not trivial in a “smart” urban ecosystem, both for businesses and Public Administrations (PAs). The use of the Internet of Things (IoT) together with data sharing both at the front-end and the back-end sides promises to advantage the entire urban metabolism thus (i) going beyond the old “silos logic” and (ii) allowing the growth of shared knowledge. In this work we present a case study based on the implementation of the InfluxDB time series database for monitoring and analytics in distributed IoT environments. The goal is to enable IoT-as-a-Service in geo-distributed “smart” ecosystems thus creating new opportunities for heterogeneous stakeholders (i.e., people, PA, academia, industries) to meet and define new synergies.
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Notes
- 1.
https://www.influxdata.com/time-series-platform/influxdb/, last accessed November 5, 2018.
- 2.
https://www.postgresql.org/, last accessed August 2, 2018.
- 3.
https://www.python.org/, last accessed August 2, 2018.
- 4.
https://www.json.org/, last accessed August 2, 2018.
References
Benkerrou, H., Heddad, S., Omar, M.: Credit and honesty-based trust assessment for hierarchical collaborative IoT systems. In: 2016 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), Hammamet, Tunisia, pp. 295–299 (2016). https://doi.org/10.1109/SETIT.2016.7939883
Jaouedi, N., Boujnah, N., Htiwich, O., Bouhlel, M.S..: Human action recognition to human behavior analysis. In: 2016 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), Hammamet, Tunisia, pp. 263–266 (2016). https://doi.org/10.1109/SETIT.2016.7939877
Code for comparison write ups of InfluxDB and other solutions. https://github.com/influxdata/influxdb-comparisons. Last committed 2018
Hajek, V., Klapka, T., Kudibal, I.: Benchmarking InfluxDB vs. MongoDB for time series data, metrics & management. An Influxdata technical paper (January 2018 revision 3). http://get.influxdata.com/rs/972-GDU-533/images/InfluxDB%201.4%20vs.%20MongoDB.pdf
Singh, S., Jha, R., Ranjan, P., Tripathy, M. R.: Software aspects of WSN for monitoring in an Indian greenhouse. In: 2015 International Conference on Computational Intelligence and Communication Networks (CICN), Jabalpur, pp. 168–172 (2015). https://doi.org/10.1109/CICN.2015.313
Mohanty, S.P., Choppali, U., Kougianos, E.: Everything you wanted to know about smart cities: the Internet of Things is the backbone. IEEE Consum. Electron. Mag. 5(3), 60–70 (2016). https://doi.org/10.1109/MCE.2016.2556879
Grégoire, J.: A data flow architecture for smart city applications. In: 21st Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN), Paris, pp. 1–5 (2018). https://doi.org/10.1109/ICIN.2018.8401639
Bruneo, D., Distefano, S., Longo, F., Merlino, G., Puliafito, A.: I/Ocloud: adding an IoT dimension to cloud infrastructures. Computer 51, 57–65 (2018). https://doi.org/10.1109/MC.2018.1151016
Giacobbe, M., Pellegrino, G., Scarpa, M., Puliafito, A.: The ESSB system: a novel solution to improve comfort and sustainability in smart office environments. In: 14th IEEE International Conference on Networking, Sensing and Control (ICNSC 2017), pp. 311–316. IEEE Press, Calabria, Italy (2017). https://doi.org/10.1109/ICNSC.2017.8000110
Giacobbe, M., Pellegrino, G., Scarpa, M., Puliafito, A.: An approach to implement the “Smart Office” idea: the #SmartMe energy system. J. Amb. Intell. Hum. Comput., pp. 1–19. Springer, Heidelberg (2018). https://doi.org/10.1007/s12652-018-0809-0
Yousefpour, A., Ishigaki, G., Jue, J.P.: Fog computing: towards minimizing delay in the Internet of Things. In: 2017 IEEE International Conference on Edge Computing (EDGE), Honolulu, HI, pp. 17–24 (2017). https://doi.org/10.1109/IEEE.EDGE.2017.12
Kasmi, M., Bahloul, F., Tkitek, H.: Smart home based on Internet of Things and cloud computing. In: 2016 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), Hammamet, Tunisia, pp. 82–86 (2016). https://doi.org/10.1109/SETIT.2016.7939846
Mabrouk, H.H.: Machine learning from experience feedback on accidents in transport. In: 2016 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), Hammamet, Tunisia, pp. 246–251 (2016). https://doi.org/10.1109/SETIT.2016.7939874
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Giacobbe, M., Chaouch, C., Scarpa, M., Puliafito, A. (2020). An Implementation of InfluxDB for Monitoring and Analytics in Distributed IoT Environments. In: Bouhlel, M., Rovetta, S. (eds) Proceedings of the 8th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT’18), Vol.1. SETIT 2018. Smart Innovation, Systems and Technologies, vol 146. Springer, Cham. https://doi.org/10.1007/978-3-030-21005-2_15
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