Sizing and Routing of Wireless Sensor Networks for Traffic Vehicular Monitoring
Keywords:
Smart cities, ICT, wireless, sensor, traffic sizing, routing and Zigbee
Abstract
The demand in the urban population affects the increase in vehicles caused by traffic in cities. The way to manage this problem is through the implementation of an intelligent traffic system that allows a better interrelation with all the elements that compose it. Communication with the elements occurs through information and communication technologies (ICT), which are required for the development of smart cities. Implementing a wireless sensor network in a city allows obtaining information on the state in which it is located in real-time so that the location of the sensors at traffic lights and traffic signals will allow obtaining the necessary data for decision-making correct based on local perception. Cities such as Quito have had a considerable increase in population, therefore, it can be seen that one of the main problems is the traffic that the city faces at peak hours, so the use of wireless sensors to monitor traffic is of great help. For everything detailed above, this document will show the dimensioning and routing of a wireless sensor network that offers a more efficient system to control and manage the flow of vehicular traffic.
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References
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[3] M. A. Kafi, Y. Challal, D. Djenouri, A. Bouabdallah, L. Khelladi, and N. Badache, “A study of Wireless Sensor Network Architectures and Projects for Traffic Light Monitoring,” Procedia Comput. Sci., vol. 10, pp. 543-552, 2012. https://doi.org/10.1016/j.procs.2012.06.069
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[9] J. J. Fernández-Lozano, M. Martín-Guzmán, J. MartínÁvila, and A. García-Cerezo, “A Wireless Sensor Network for Urban Traffic Characterization and Trend Monitoring,” Sensors, vol. 15, no. 10, pp. 26143-26169, Oct. 2015. https://doi.org/10.3390/s151026143
[10] B. Rashid and M. H. Rehmani, “Applications of wireless sensor networks for urban areas: A survey,” J. Netw. Comput. Appl., vol. 60, pp. 192-219, Jan. 2016.
https://doi.org/10.1016/j.jnca.2015.09.008
[11] O. Karpis, J. Juricek, and J. Micek, “Application of wireless sensor networks for road monitoring,” IFAC Proc. Vol., vol. 10, no. PART 1, pp. 183-188, 2010.
https://doi.org/10.3182/20101006-2-pl-4019.00035
[12] V. C. Gungor, B. Lu, and G. P. Hancke, “Opportunities and challenges of wireless sensor networks in smart grid,” IEEE Trans. Ind. Electron., vol. 57, no. 10, pp. 3557–3564, 2010. https://doi.org/10.1109/TIE.2009.2039455
[13] M. El Brak and M. Essaaidi, “Wireless sensor network in smart grid technology: Challenges and opportunities,” in 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), Mar. 2012, pp. 578-583. https://doi.org/10.1109/SETIT.2012.6481976
[14] C. Li, Y. Li, Y. Shen, L. Liu, and Q. Cao, “An Optimization Algorithm for Wireless Sensor Networks Localization Using Multiplier Method,” in 2010 Third International Joint Conference on Computational Science and Optimization, 2010, pp. 337-341. https://doi.org/10.1109/CSO.2010.187
[15] J. Akram, Z. Najam, and H. Rizwi, “Energy Efficient Localization in Wireless Sensor Networks Using Computational Intelligence,” in 2018 15th International Conference on Smart Cities: Improving Quality of Life Using ICT & IoT (HONET-ICT), Oct. 2018, pp. 78-82. https://doi.org/10.1109/HONET.2018.8551332
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[18] M. Khan, G. Pandurangan, and V. S. Anil Kumar, “Distributed Algorithms for Constructing Approximate Minimum Spanning Trees in Wireless Sensor Networks,” IEEE Trans. Parallel Distrib. Syst., vol. 20, no. 1, pp. 124-139, Jan. 2009. https://doi.org/10.1109/TPDS.2008.57
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[20] G. Barai and K. Raahemifar, “Optimization of distributed communication architectures in advanced metering infrastructure of smart grid,” in 2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), May 2014, pp. 1-6. https://doi.org/10.1109/CCECE.2014.6901098
[21] F. Aalamifar, G. N. Shirazi, M. Noori, and L. Lampe, “Cost-efficient data aggregation point placement for advanced metering infrastructure,” in 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm), Nov. 2014, pp. 344-349. https://doi.org/10.1109/SmartGridComm.2014.7007670
[22] C. Ganán, E. Inga, and R. Hincapié, “Óptimo despliegue y enrutamiento de UDAP para infraestructura de medición avanzada basada en el algoritmo MST,” Ingeniare. Rev. Chil. Ing., vol. 25, no. 1, pp. 106-115, Jan. 2017. https://doi.org/10.4067/S0718-33052017000100106
[23] K. W. K. Lui, F. K. W. Chan, and H. C. So, “Accurate time delay estimation based passive localization,” Signal Processing, vol. 89, no. 9, pp. 1835-1838, Sep. 2009. https://doi.org/10.1016/j.sigpro.2009.03.009
[24] K. Römer, “The Lighthouse Location System for Smart Dust,” in Proceedings of the 1st international conference on Mobile systems, applications and services - MobiSys ’03, 2003, pp. 15-30. https://doi.org/10.1145/1066116.1189036
[25] S. Venkatraman, J. Caffery, and H.-R. You, “A novel ToA location algorithm using LoS range estimation for NLoS environments,” IEEE Trans. Veh. Technol., vol. 53, no. 5, pp. 1515-1524, Sep. 2004. https://doi.org/10.1109/TVT.2004.832384
Published
2020-01-01
How to Cite
Godoy-Pérez, K., Benítez-Tupiza, K., Valle-Jaramillo, J., & Inga-Ortega, E. (2020). Sizing and Routing of Wireless Sensor Networks for Traffic Vehicular Monitoring. ITECKNE, 17(1), 7-18. https://doi.org/https://doi.org/10.15332/iteckne.v17i1.2425
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Research and Innovation Articles
