Posicionamento de sensores para monitoramento colaborativo de emergências urbanas
Resumo
Este trabalho propõe uma metodologia baseada no algoritmo genético multiobjetivo NSGA-II para posicionamento otimizado de sensores escalares e visuais em redes colaborativas de monitoramento de emergências urbanas. A solução considera, simultaneamente, critérios de cobertura espacial, qualidade e redundância de sensoriamento, e conectividade em rede. Resultados experimentais mostraram que a metodologia proposta alcança equilíbrio satisfatório entre os múltiplos objetivos analisados, garantindo boa cobertura da área de interesse, níveis adequados de redundância e conectividade robusta para colaboração efetiva entre sensores.Referências
Benatia, M. A., Sahnoun, M., Baudry, D., Louis, A., El-Hami, A., and Mazari, B. (2017). Multi-objective wsn deployment using genetic algorithms under cost, coverage, and connectivity constraints. Wireless Personal Communications, 94(4):2739–2768.
Binh, H. T. T., Hanh, N. T., Quan, L. V., and Dey, N. (2018). Improved cuckoo search and chaotic flower pollination optimization algorithm for maximizing area coverage in wireless sensor networks. Neural Computing and Applications, 30(7):2305–2317.
Bouzid, S. E., Serrestou, Y., Raoof, K., Mbarki, M., Omri, M. N., and Dridi, C. (2020). Wireless sensor network deployment optimisation based on coverage, connectivity and cost metrics. International Journal of Sensor Networks, 33(4):224–238.
Chen, Y.-N., Lin, W.-H., and Chen, C. (2020). An effective sensor deployment scheme that ensures multilevel coverage of wireless sensor networks with uncertain properties. Sensors, 20(7).
Coelho, G. A. A., Jesus, T. C., and Costa, D. G. (2023). Urban emergency detection system using hierarchical, collaborative and configurable wireless sensor networks. In XIII Brazilian Symposium on Computing Systems Engineering (SBESC), pages 1–6.
Costa, D. G., Rangel, E., Peixoto, J. P. J., and Jesus, T. C. (2019). An availability metric and optimization algorithms for simultaneous coverage of targets and areas by wireless visual sensor networks. In 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), volume 1, pages 617–622.
El-Sherif, M., Fahmy, Y., and Kamal, H. (2018). Lifetime maximisation of disjoint wireless sensor networks using multiobjective genetic algorithm. IET Wireless Sensor Systems, 8(5):200–207.
Fei, Z., Li, B., Yang, S., Xing, C., Chen, H., and Hanzo, L. (2017). A survey of multi-objective optimization in wireless sensor networks: Metrics, algorithms, and open problems. IEEE Communications Surveys & Tutorials, 19(1):550–586.
Hanh, N. T., Binh, H. T. T., Hoai, N. X., and Palaniswami, M. S. (2019). An efficient genetic algorithm for maximizing area coverage in wireless sensor networks. Information Sciences, 488:58–75.
Jesus, T. C., Costa, D. G., and Portugal, P. (2019). Wireless visual sensor networks redeployment based on dependability optimization. In 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), volume 1, pages 1111–1116.
Jesus, T. C., Costa, D. G., Portugal, P., Vasques, F., and Ferreira, W. A. (2023). Dependability and quality-aware connectivity in smart cities applications. In 2023 IEEE International Smart Cities Conference (ISC2), pages 1–7.
Rangel, E. O., Costa, D. G., and Loula, A. (2019). On redundant coverage maximization in wireless visual sensor networks: Evolutionary algorithms for multi-objective optimization. Applied Soft Computing, 82:105578.
Wu, H., Liu, Z., Hu, J., and Yin, W. (2020). Sensor placement optimization for critical-grid coverage problem of indoor positioning. International Journal of Distributed Sensor Networks, 16(12):1550147720979922.
Yang, L. and Shami, A. (2020). On hyperparameter optimization of machine learning algorithms: Theory and practice. Neurocomputing, 415:295–316.
Binh, H. T. T., Hanh, N. T., Quan, L. V., and Dey, N. (2018). Improved cuckoo search and chaotic flower pollination optimization algorithm for maximizing area coverage in wireless sensor networks. Neural Computing and Applications, 30(7):2305–2317.
Bouzid, S. E., Serrestou, Y., Raoof, K., Mbarki, M., Omri, M. N., and Dridi, C. (2020). Wireless sensor network deployment optimisation based on coverage, connectivity and cost metrics. International Journal of Sensor Networks, 33(4):224–238.
Chen, Y.-N., Lin, W.-H., and Chen, C. (2020). An effective sensor deployment scheme that ensures multilevel coverage of wireless sensor networks with uncertain properties. Sensors, 20(7).
Coelho, G. A. A., Jesus, T. C., and Costa, D. G. (2023). Urban emergency detection system using hierarchical, collaborative and configurable wireless sensor networks. In XIII Brazilian Symposium on Computing Systems Engineering (SBESC), pages 1–6.
Costa, D. G., Rangel, E., Peixoto, J. P. J., and Jesus, T. C. (2019). An availability metric and optimization algorithms for simultaneous coverage of targets and areas by wireless visual sensor networks. In 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), volume 1, pages 617–622.
El-Sherif, M., Fahmy, Y., and Kamal, H. (2018). Lifetime maximisation of disjoint wireless sensor networks using multiobjective genetic algorithm. IET Wireless Sensor Systems, 8(5):200–207.
Fei, Z., Li, B., Yang, S., Xing, C., Chen, H., and Hanzo, L. (2017). A survey of multi-objective optimization in wireless sensor networks: Metrics, algorithms, and open problems. IEEE Communications Surveys & Tutorials, 19(1):550–586.
Hanh, N. T., Binh, H. T. T., Hoai, N. X., and Palaniswami, M. S. (2019). An efficient genetic algorithm for maximizing area coverage in wireless sensor networks. Information Sciences, 488:58–75.
Jesus, T. C., Costa, D. G., and Portugal, P. (2019). Wireless visual sensor networks redeployment based on dependability optimization. In 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), volume 1, pages 1111–1116.
Jesus, T. C., Costa, D. G., Portugal, P., Vasques, F., and Ferreira, W. A. (2023). Dependability and quality-aware connectivity in smart cities applications. In 2023 IEEE International Smart Cities Conference (ISC2), pages 1–7.
Rangel, E. O., Costa, D. G., and Loula, A. (2019). On redundant coverage maximization in wireless visual sensor networks: Evolutionary algorithms for multi-objective optimization. Applied Soft Computing, 82:105578.
Wu, H., Liu, Z., Hu, J., and Yin, W. (2020). Sensor placement optimization for critical-grid coverage problem of indoor positioning. International Journal of Distributed Sensor Networks, 16(12):1550147720979922.
Yang, L. and Shami, A. (2020). On hyperparameter optimization of machine learning algorithms: Theory and practice. Neurocomputing, 415:295–316.
Publicado
02/06/2025
Como Citar
BARRETO, Gabriel S.; PIRES, Matheus G.; JESUS, Thiago C..
Posicionamento de sensores para monitoramento colaborativo de emergências urbanas. In: SIMPÓSIO BRASILEIRO DE SISTEMAS COLABORATIVOS (SBSC), 20. , 2025, Manaus/AM.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 52-63.
ISSN 2326-2842.
DOI: https://doi.org/10.5753/sbsc.2025.8438.
