Desenvolvimento de capacete inteligente para aplicações de pesquisa de campo ecológico
Resumo
Forest inventory and management are important topics to enhance environmental protection initiatives and policies. Thus, sampling processes inside the forest environment are normally manual and limited. These conditions nurture an increasing need for novel solutions to enhance environmental perception, especially in ground-sampling processes. In this work, we present a new solution to augment environmental perception. The proposed appliance is a wearable embedded system based on a helmet and projected to acquire environmental data. It also allows the development of new applications to expand the researcher reality perception.
Referências
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Billinghurst, M. and Starner, T. (1999). Wearable devices: new ways to manage informa- tion. Computer, 32(1):57–64.
Bonato, P. (2003). Wearable sensors/systems and their impact on biomedical engineering. IEEE Engineering in Medicine and Biology Magazine, 22(3):18–20.
Brandt, J. S., Nolte, C., and Agrawal, A. (2016). Deforestation and timber production in congo after implementation of sustainable forest management policy. Land Use Policy, 52:15–22.
Calvaresi, D., Marinoni, M., Sturm, A., Schumacher, M., and Buttazzo, G. (2017). The challenge of real-time multi-agent systems for enabling iot and cps. In Proceedings of the International Conference on Web Intelligence, pages 356–364. ACM.
Chandran, S., Chandrasekar, S., and Elizabeth, N. E. (2016). Konnect: An internet of things (iot) based smart helmet for accident detection and notification. In India Con- ference (INDICON), 2016 IEEE Annual, pages 1–4. IEEE.
Deva, S. V. S. V. P., Akashe, S., Kumar, V., et al. (2018). Advanced control of switch- ing ignition by smart helmet. International Journal of Image, Graphics and Signal Processing, 10(2):34.
Fedrigo, M., Newnham, G. J., Coops, N. C., Culvenor, D. S., Bolton, D. K., and Nitschke, C. R. (2018). Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar. ISPRS Journal of Photogrammetry and Remote Sensing, 136:106–119.
Hall, D. L. and Llinas, J. (1997). An introduction to multisensor data fusion. Proceedings of the IEEE, 85(1):6–23.
Hansen, F. O. (2017). Energy-aware model-driven development of a wearable healthcare device. In Software Engineering in Health Care: 4th International Symposium, FHIES 2014, and 6th International Workshop, SEHC 2014, Washington, DC, USA, July 17-18, 2014, Revised Selected Papers, volume 9062, page 44. Springer.
Harshitha, K., Sreeja, K., Manusha, N., Harika, E., and Rao, P. K. (2018). Zigbee based intelligent helmet for coal miners safety purpose.
Humagain, K., Portillo-Quintero, C., Cox, R. D., and Cain III, J. W. (2018). Estimating forest canopy cover dynamics in valles caldera national preserve, new mexico, using lidar and landsat data. Applied geography, 99:120–132.
Jeong, M., Lee, H., Bae, M., Shin, D.-B., Lim, S.-H., and Lee, K. B. (2018). Development and application of the smart helmet for disaster and safety. In 2018 International Con- ference on Information and Communication Technology Convergence (ICTC), pages 1084–1089. IEEE.
Jeronimo, S. M., Kane, V. R., Churchill, D. J., McGaughey, R. J., and Franklin, J. F. (2018). Applying lidar individual tree detection to management of structurally diverse forest landscapes. Journal of Forestry, 116(4):336–346.
Jo, G.-H., Jeon, S.-B., Chung, H., and Song, Y. J. (2017). Sensor data analysis and visu- alization of iot system for combat helmet. Advanced Science Letters, 23(10):10342– 10345.
Jose, S. J., Rahul, A., and Sajin, S. (2017). Safety and alerting system of vehicles using a smart helmet. i-Manager’s Journal on Wireless Communication Networks, 6(2):28.
Magno, M., D’Aloia, A., Polonelli, T., Spadaro, L., and Benini, L. (2016). Shelmet: an intelligent self-sustaining multi sensors smart helmet for bikers. In International Conference on Sensor Systems and Software, pages 55–67. Springer.
Mazzocchi, F., Cecchini, M., Monarca, D., Colantoni, A., Caruso, L., and Leopardi, F. (2015). An overview of risk assessment for tree climber arborists.
Pirkl, G., Hevesi, P., Amarislanov, O., and Lukowicz, P. (2016). Smart helmet for con- struction site documentation and work support. In Proceedings of the 2016 ACM In- ternational Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, pages 349–352. ACM.
Pontes Ribeiro, S. and Basset, Y. (2007). Gall-forming and free-feeding herbivory along vertical gradients in a lowland tropical rainforest: the importance of leaf sclerophylly. Ecography, 30(5):663–672.
Rhodes, B. J. (1997). The wearable remembrance agent: A system for augmented mem- ory. Personal Technologies, 1(4):218–224.
Ribeiro, S. P., Silva, M., Tagliati, M. C., and Chavana-Bryant, C. (2011). Vegetation traits and herbivory distribution in an australian subtropical forest. Memoir. Queensl. Mus, 55:481–493.
Roja, P. and Srihari, D. (2018). Iot based smart helmet for air quality used for the mining industry.
San Juan, R. F. d. V. and Domingo-Santos, J. M. (2018). The role of gis and lidar as tools for sustainable forest management. GIS-An Overview of Applications, 1:124–148.
Sankey, T., Donager, J., McVay, J., and Sankey, J. B. (2017). Uav lidar and hyperspectral fusion for forest monitoring in the southwestern usa. Remote Sensing of Environment, 195:30–43.
Silva, M., Delabrida, S., Ribeiro, S., and Oliveira, R. (2019). Toward the design of a novel wearable system for field research in ecology. In 2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC), pages 160–165. IEEE.
Ullah, S., Higgins, H., Braem, B., Latre, B., Blondia, C., Moerman, I., Saleem, S., Rah- man, Z., and Kwak, K. S. (2012). A comprehensive survey of wireless body area networks. Journal of medical systems, 36(3):1065–1094.
Uma, S., Kujani, T., and Bhuvanya, R. (2018). Augmented reality and smart interac- tive helmet for safety using global positioning system. Journal of Computational and Theoretical Nanoscience, 15(6-7):2283–2286.
West, R., Parola, M. J., Jaycen, A. R., and Lueg, C. P. (2015). Embodied information behavior, mixed reality and big data. In The Engineering Reality of Virtual Reality 2015, volume 9392, page 93920E. International Society for Optics and Photonics.
White, J. C., Coops, N. C., Wulder, M. A., Vastaranta, M., Hilker, T., and Tompalski, P. (2016). Remote sensing technologies for enhancing forest inventories: A review. Canadian Journal of Remote Sensing, 42(5):619–641.
Billinghurst, M. and Starner, T. (1999). Wearable devices: new ways to manage informa- tion. Computer, 32(1):57–64.
Bonato, P. (2003). Wearable sensors/systems and their impact on biomedical engineering. IEEE Engineering in Medicine and Biology Magazine, 22(3):18–20.
Brandt, J. S., Nolte, C., and Agrawal, A. (2016). Deforestation and timber production in congo after implementation of sustainable forest management policy. Land Use Policy, 52:15–22.
Calvaresi, D., Marinoni, M., Sturm, A., Schumacher, M., and Buttazzo, G. (2017). The challenge of real-time multi-agent systems for enabling iot and cps. In Proceedings of the International Conference on Web Intelligence, pages 356–364. ACM.
Chandran, S., Chandrasekar, S., and Elizabeth, N. E. (2016). Konnect: An internet of things (iot) based smart helmet for accident detection and notification. In India Con- ference (INDICON), 2016 IEEE Annual, pages 1–4. IEEE.
Deva, S. V. S. V. P., Akashe, S., Kumar, V., et al. (2018). Advanced control of switch- ing ignition by smart helmet. International Journal of Image, Graphics and Signal Processing, 10(2):34.
Fedrigo, M., Newnham, G. J., Coops, N. C., Culvenor, D. S., Bolton, D. K., and Nitschke, C. R. (2018). Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar. ISPRS Journal of Photogrammetry and Remote Sensing, 136:106–119.
Hall, D. L. and Llinas, J. (1997). An introduction to multisensor data fusion. Proceedings of the IEEE, 85(1):6–23.
Hansen, F. O. (2017). Energy-aware model-driven development of a wearable healthcare device. In Software Engineering in Health Care: 4th International Symposium, FHIES 2014, and 6th International Workshop, SEHC 2014, Washington, DC, USA, July 17-18, 2014, Revised Selected Papers, volume 9062, page 44. Springer.
Harshitha, K., Sreeja, K., Manusha, N., Harika, E., and Rao, P. K. (2018). Zigbee based intelligent helmet for coal miners safety purpose.
Humagain, K., Portillo-Quintero, C., Cox, R. D., and Cain III, J. W. (2018). Estimating forest canopy cover dynamics in valles caldera national preserve, new mexico, using lidar and landsat data. Applied geography, 99:120–132.
Jeong, M., Lee, H., Bae, M., Shin, D.-B., Lim, S.-H., and Lee, K. B. (2018). Development and application of the smart helmet for disaster and safety. In 2018 International Con- ference on Information and Communication Technology Convergence (ICTC), pages 1084–1089. IEEE.
Jeronimo, S. M., Kane, V. R., Churchill, D. J., McGaughey, R. J., and Franklin, J. F. (2018). Applying lidar individual tree detection to management of structurally diverse forest landscapes. Journal of Forestry, 116(4):336–346.
Jo, G.-H., Jeon, S.-B., Chung, H., and Song, Y. J. (2017). Sensor data analysis and visu- alization of iot system for combat helmet. Advanced Science Letters, 23(10):10342– 10345.
Jose, S. J., Rahul, A., and Sajin, S. (2017). Safety and alerting system of vehicles using a smart helmet. i-Manager’s Journal on Wireless Communication Networks, 6(2):28.
Magno, M., D’Aloia, A., Polonelli, T., Spadaro, L., and Benini, L. (2016). Shelmet: an intelligent self-sustaining multi sensors smart helmet for bikers. In International Conference on Sensor Systems and Software, pages 55–67. Springer.
Mazzocchi, F., Cecchini, M., Monarca, D., Colantoni, A., Caruso, L., and Leopardi, F. (2015). An overview of risk assessment for tree climber arborists.
Pirkl, G., Hevesi, P., Amarislanov, O., and Lukowicz, P. (2016). Smart helmet for con- struction site documentation and work support. In Proceedings of the 2016 ACM In- ternational Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, pages 349–352. ACM.
Pontes Ribeiro, S. and Basset, Y. (2007). Gall-forming and free-feeding herbivory along vertical gradients in a lowland tropical rainforest: the importance of leaf sclerophylly. Ecography, 30(5):663–672.
Rhodes, B. J. (1997). The wearable remembrance agent: A system for augmented mem- ory. Personal Technologies, 1(4):218–224.
Ribeiro, S. P., Silva, M., Tagliati, M. C., and Chavana-Bryant, C. (2011). Vegetation traits and herbivory distribution in an australian subtropical forest. Memoir. Queensl. Mus, 55:481–493.
Roja, P. and Srihari, D. (2018). Iot based smart helmet for air quality used for the mining industry.
San Juan, R. F. d. V. and Domingo-Santos, J. M. (2018). The role of gis and lidar as tools for sustainable forest management. GIS-An Overview of Applications, 1:124–148.
Sankey, T., Donager, J., McVay, J., and Sankey, J. B. (2017). Uav lidar and hyperspectral fusion for forest monitoring in the southwestern usa. Remote Sensing of Environment, 195:30–43.
Silva, M., Delabrida, S., Ribeiro, S., and Oliveira, R. (2019). Toward the design of a novel wearable system for field research in ecology. In 2018 VIII Brazilian Symposium on Computing Systems Engineering (SBESC), pages 160–165. IEEE.
Ullah, S., Higgins, H., Braem, B., Latre, B., Blondia, C., Moerman, I., Saleem, S., Rah- man, Z., and Kwak, K. S. (2012). A comprehensive survey of wireless body area networks. Journal of medical systems, 36(3):1065–1094.
Uma, S., Kujani, T., and Bhuvanya, R. (2018). Augmented reality and smart interac- tive helmet for safety using global positioning system. Journal of Computational and Theoretical Nanoscience, 15(6-7):2283–2286.
West, R., Parola, M. J., Jaycen, A. R., and Lueg, C. P. (2015). Embodied information behavior, mixed reality and big data. In The Engineering Reality of Virtual Reality 2015, volume 9392, page 93920E. International Society for Optics and Photonics.
White, J. C., Coops, N. C., Wulder, M. A., Vastaranta, M., Hilker, T., and Tompalski, P. (2016). Remote sensing technologies for enhancing forest inventories: A review. Canadian Journal of Remote Sensing, 42(5):619–641.
Publicado
09/07/2019
Como Citar
SILVA, Mateus Coelho; RIBEIRO, Sérvio Pontes; DELABRIDA, Saul; OLIVEIRA, Ricardo Augusto Rabelo.
Desenvolvimento de capacete inteligente para aplicações de pesquisa de campo ecológico. In: SEMINÁRIO INTEGRADO DE SOFTWARE E HARDWARE (SEMISH), 46. , 2019, Belém.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 69-80.
ISSN 2595-6205.
DOI: https://doi.org/10.5753/semish.2019.6568.
