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09.05.2024

Smart remote sensing network for disaster management: an overview

verfasst von: Rami Ahmad

Erschienen in: Telecommunication Systems

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Abstract

Remote sensing technology is a vital component of disaster management, poised to revolutionize how we safeguard lives and property through enhanced prediction, mitigation, and recovery efforts. Disaster management hinges on continuous monitoring of various environments, from urban areas to forests and farms. Data from these observations are relayed to servers, where sophisticated processing algorithms forecast impending disasters. Remote sensing technology operates through a layered framework. The sensing layer acquires raw data, the network layer facilitates data transmission, and the data processing layer extracts meaningful insights. The application layer then leverages these insights to make informed decisions. Elevating the intelligence of remote sensing technology necessitates advancements across these layers. This paper delves into disaster management concepts and highlights the pivotal role played by remote sensing technology. It offers a comprehensive exploration of each layer within the remote sensing technology framework, detailing foundational principles, tools, and methodologies for enhancing intelligence. Addressing challenges inherent to this technology, the paper also presents future-oriented solutions. Furthermore, it examines the influence of wireless network infrastructure, alongside emerging technologies like the Internet of Things, cloud computing, virtual machines, and low-power wireless networks, in nurturing the evolution and sustainability of remote sensing technology.

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Literatur
2.
10.
Zurück zum Zitat Singh, M. K., Amin, S. I., Imam, S. A., Sachan, V. K., & Choudhary, A. (2018). A survey of Wireless Sensor Network and its types. Proceedings - IEEE 2018 International Conference on Advances in Computing Communication Control and Networking ICACCCN 2018, 326–330. https://doi.org/10.1109/ICACCCN.2018.8748710. Singh, M. K., Amin, S. I., Imam, S. A., Sachan, V. K., & Choudhary, A. (2018). A survey of Wireless Sensor Network and its types. Proceedings - IEEE 2018 International Conference on Advances in Computing Communication Control and Networking ICACCCN 2018, 326–330. https://​doi.​org/​10.​1109/​ICACCCN.​2018.​8748710.
12.
Zurück zum Zitat Olsson, J. (2014). 6LoWPAN demystified. Olsson, J. (2014). 6LoWPAN demystified.
13.
Zurück zum Zitat Moridi, M. A., Kawamura, Y., Sharifzadeh, M., Chanda, E. K., Wagner, M., & Okawa, H. (2017). Performance analysis of ZigBee network topologies for underground space monitoring and communication systems, Tunnelling and Underground Space Technology, vol. 71, no. July pp. 201–209, 2018, https://doi.org/10.1016/j.tust.2017.08.018. Moridi, M. A., Kawamura, Y., Sharifzadeh, M., Chanda, E. K., Wagner, M., & Okawa, H. (2017). Performance analysis of ZigBee network topologies for underground space monitoring and communication systems, Tunnelling and Underground Space Technology, vol. 71, no. July pp. 201–209, 2018, https://​doi.​org/​10.​1016/​j.​tust.​2017.​08.​018.
32.
33.
Zurück zum Zitat Ji, C., Lu, H., Ji, C., & Yan, J. (2015). An IoT and Mobile Cloud based Architecture for Smart Planting, Proceedings of the 3rd International Conference on Machinery, Materials and Information Technology Applications, vol. 35, no. Icmmita, pp. 1001–1005, 2015, https://doi.org/10.2991/icmmita-15.2015.184. Ji, C., Lu, H., Ji, C., & Yan, J. (2015). An IoT and Mobile Cloud based Architecture for Smart Planting, Proceedings of the 3rd International Conference on Machinery, Materials and Information Technology Applications, vol. 35, no. Icmmita, pp. 1001–1005, 2015, https://​doi.​org/​10.​2991/​icmmita-15.​2015.​184.
46.
48.
Zurück zum Zitat Kato, A., Wakabayashi, H., Hayakawa, Y., Bradford, M., Watanabe, M., & Yamaguchi, Y. (2017). Tropical forest disaster monitoring with multi-scale sensors from terrestrial laser, UAV, to satellite radar, in 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Jul. pp. 2883–2886. https://doi.org/10.1109/IGARSS.2017.8127600. Kato, A., Wakabayashi, H., Hayakawa, Y., Bradford, M., Watanabe, M., & Yamaguchi, Y. (2017). Tropical forest disaster monitoring with multi-scale sensors from terrestrial laser, UAV, to satellite radar, in 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Jul. pp. 2883–2886. https://​doi.​org/​10.​1109/​IGARSS.​2017.​8127600.
50.
Zurück zum Zitat Lohar, S., Zhu, L., Young, S., Graf, P., & Blanton, M. (2021). Sensing Technology Survey for obstacle detection in Vegetation, pp. 672–685. Lohar, S., Zhu, L., Young, S., Graf, P., & Blanton, M. (2021). Sensing Technology Survey for obstacle detection in Vegetation, pp. 672–685.
52.
Zurück zum Zitat Neelam, S., Sood, S. K., & A Scientometric Review of Global Research on Smart Disaster Management. (2021)., IEEE Transactions on Engineering Management, vol. 68, no. 1. Institute of Electrical and Electronics Engineers Inc., pp. 317–329, Feb. 01, https://doi.org/10.1109/TEM.2020.2972288. Neelam, S., Sood, S. K., & A Scientometric Review of Global Research on Smart Disaster Management. (2021)., IEEE Transactions on Engineering Management, vol. 68, no. 1. Institute of Electrical and Electronics Engineers Inc., pp. 317–329, Feb. 01, https://​doi.​org/​10.​1109/​TEM.​2020.​2972288.
55.
Zurück zum Zitat Damaševičius, R., Bacanin, N., & Misra, S. (2023). From Sensors to Safety: Internet of Emergency Services (IoES) for Emergency Response and Disaster Management, Journal of Sensor and Actuator Networks, vol. 12, no. 3. MDPI, Jun. 01, https://doi.org/10.3390/jsan12030041. Damaševičius, R., Bacanin, N., & Misra, S. (2023). From Sensors to Safety: Internet of Emergency Services (IoES) for Emergency Response and Disaster Management, Journal of Sensor and Actuator Networks, vol. 12, no. 3. MDPI, Jun. 01, https://​doi.​org/​10.​3390/​jsan12030041.
56.
Zurück zum Zitat UNISR (2017). Economic losses, poverty & disasters 1998–2017. UNISR (2017). Economic losses, poverty & disasters 1998–2017.
60.
Zurück zum Zitat Sakurai, M., & Kokuryo, J. (2012). Preparing for creative responses to ‘beyond assumed level’ disasters: Lessons from the ict management in the 2011 great East Japan Earthquake crisis. Risk Governance and Control: Financial Markets and Institutions, 2(4), 17–24. https://doi.org/10.22495/rgcv2i4art2.CrossRef Sakurai, M., & Kokuryo, J. (2012). Preparing for creative responses to ‘beyond assumed level’ disasters: Lessons from the ict management in the 2011 great East Japan Earthquake crisis. Risk Governance and Control: Financial Markets and Institutions, 2(4), 17–24. https://​doi.​org/​10.​22495/​rgcv2i4art2.CrossRef
62.
Zurück zum Zitat Gupta, A. T., & Approach, A. I. (2018). Open Water Journal, 5, 2, 2. Gupta, A. T., & Approach, A. I. (2018). Open Water Journal, 5, 2, 2.
64.
Zurück zum Zitat Van de Bartel, T., & He (2012). D esign of the. Journal of Information Technology Theory and Application, 1(1), 253–292. Van de Bartel, T., & He (2012). D esign of the. Journal of Information Technology Theory and Application, 1(1), 253–292.
72.
Zurück zum Zitat Basloom, S., Akkari, N., & Aldabbagh, G. (2018). Mobility Management in SDN and NFV-based Next-Generation Wireless Networks: An Overview and Qualitative Evaluation, 1st International Conference on Advanced Research in Engineering Sciences, ARES pp. 1–8, 2018, https://doi.org/10.1109/ARESX.2018.8723275. Basloom, S., Akkari, N., & Aldabbagh, G. (2018). Mobility Management in SDN and NFV-based Next-Generation Wireless Networks: An Overview and Qualitative Evaluation, 1st International Conference on Advanced Research in Engineering Sciences, ARES pp. 1–8, 2018, https://​doi.​org/​10.​1109/​ARESX.​2018.​8723275.
87.
88.
Zurück zum Zitat Allioui, H., & Mourdi, Y. Exploring the Full Potentials of IoT for Better Financial Growth and Stability: A Comprehensive Survey, Sensors, vol. 23, no. 19. Multidisciplinary Digital Publishing Institute (MDPI), Oct. 01, 2023. https://doi.org/10.3390/s23198015. Allioui, H., & Mourdi, Y. Exploring the Full Potentials of IoT for Better Financial Growth and Stability: A Comprehensive Survey, Sensors, vol. 23, no. 19. Multidisciplinary Digital Publishing Institute (MDPI), Oct. 01, 2023. https://​doi.​org/​10.​3390/​s23198015.
91.
Zurück zum Zitat Alhasan, W., Ahmad, R., Wazirali, R., Aleisa, N., & Abo Shdeed, W. (Oct. 2023). Adaptive mean center of mass particle swarm optimizer for auto-localization in 3D wireless sensor networks. Journal of King Saud University , 35(9), 101782. https://doi.org/10.1016/j.jksuci.2023.101782. Computer and Information Sciences. Alhasan, W., Ahmad, R., Wazirali, R., Aleisa, N., & Abo Shdeed, W. (Oct. 2023). Adaptive mean center of mass particle swarm optimizer for auto-localization in 3D wireless sensor networks. Journal of King Saud University , 35(9), 101782. https://​doi.​org/​10.​1016/​j.​jksuci.​2023.​101782. Computer and Information Sciences.
92.
Zurück zum Zitat Ashrif, F. F., Sundararajan, E. A., Ahmad, R., Hasan, M. K., & Yadegaridehkordi, E. (2024). Survey on the authentication and key agreement of 6LoWPAN: Open issues and future direction, Journal of Network and Computer Applications, vol. 221. Academic Press, Jan. 01, https://doi.org/10.1016/j.jnca.2023.103759. Ashrif, F. F., Sundararajan, E. A., Ahmad, R., Hasan, M. K., & Yadegaridehkordi, E. (2024). Survey on the authentication and key agreement of 6LoWPAN: Open issues and future direction, Journal of Network and Computer Applications, vol. 221. Academic Press, Jan. 01, https://​doi.​org/​10.​1016/​j.​jnca.​2023.​103759.
98.
Zurück zum Zitat Krys, D., & Najjaran, H. (2007). Development of visual simultaneous localization and mapping (VSLAM) for a pipe inspection robot, Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007, pp. 344–349, 2007, https://doi.org/10.1109/CIRA.2007.382850. Krys, D., & Najjaran, H. (2007). Development of visual simultaneous localization and mapping (VSLAM) for a pipe inspection robot, Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2007, pp. 344–349, 2007, https://​doi.​org/​10.​1109/​CIRA.​2007.​382850.
109.
Zurück zum Zitat Ma, Y., Guga, S., Xu, J., Zhang, J., Tong, Z., & Liu, X. (2021). Comprehensive risk assessment of high temperature disaster to kiwifruit in Shaanxi province, China. International Journal of Environmental Research and Public Health, 18(19). https://doi.org/10.3390/ijerph181910437. Ma, Y., Guga, S., Xu, J., Zhang, J., Tong, Z., & Liu, X. (2021). Comprehensive risk assessment of high temperature disaster to kiwifruit in Shaanxi province, China. International Journal of Environmental Research and Public Health, 18(19). https://​doi.​org/​10.​3390/​ijerph181910437.
113.
Zurück zum Zitat Mostapha Mohammad, F. D., & Harb (2017). Remote sensing in Multirisk Assessment. IEEE Geosci Remote Sens Mag, 5(1), 53–65.CrossRef Mostapha Mohammad, F. D., & Harb (2017). Remote sensing in Multirisk Assessment. IEEE Geosci Remote Sens Mag, 5(1), 53–65.CrossRef
118.
Zurück zum Zitat Liu, Q., Ruan, C., Zhong, S., Li, J., Yin, Z., & Lian, X. (2018). Risk assessment of storm surge disaster based on numerical models and remote sensing, International Journal of Applied Earth Observation and Geoinformation, vol. 68, no. January, pp. 20–30, https://doi.org/10.1016/j.jag.2018.01.016. Liu, Q., Ruan, C., Zhong, S., Li, J., Yin, Z., & Lian, X. (2018). Risk assessment of storm surge disaster based on numerical models and remote sensing, International Journal of Applied Earth Observation and Geoinformation, vol. 68, no. January, pp. 20–30, https://​doi.​org/​10.​1016/​j.​jag.​2018.​01.​016.
119.
121.
Zurück zum Zitat Bhangale, U. M., Kurte, K. R., Durbha, S. S., King, R. L., & Younan, N. H., Big data processing using hpc for remote sensing disaster data, in (2016). IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Jul. 2016, pp. 5894–5897. https://doi.org/10.1109/IGARSS.2016.7730540. Bhangale, U. M., Kurte, K. R., Durbha, S. S., King, R. L., & Younan, N. H., Big data processing using hpc for remote sensing disaster data, in (2016). IEEE International Geoscience and Remote Sensing Symposium (IGARSS), IEEE, Jul. 2016, pp. 5894–5897. https://​doi.​org/​10.​1109/​IGARSS.​2016.​7730540.
125.
Zurück zum Zitat Xu, A., Anguelov, D., & Jain, D. (2018). PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation. (arXiv:1711.10871v2 [cs.CV] UPDATED), The IEEE Conference on Computer Vision and Pattern Recognition, pp. 244–253. Xu, A., Anguelov, D., & Jain, D. (2018). PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation. (arXiv:1711.10871v2 [cs.CV] UPDATED), The IEEE Conference on Computer Vision and Pattern Recognition, pp. 244–253.
128.
Zurück zum Zitat He, N., Member, S., Fang, L., Member, S., & Li, S. (2020). Skip-connected Covariance Network for. IEEE Trans Neural Netw Learn Syst, 31(5), 1461–1474.CrossRef He, N., Member, S., Fang, L., Member, S., & Li, S. (2020). Skip-connected Covariance Network for. IEEE Trans Neural Netw Learn Syst, 31(5), 1461–1474.CrossRef
130.
Zurück zum Zitat Barmpoutis, P., & Stathaki, T. (2020). A Novel Framework for Early Fire Detection Using Terrestrial and Aerial 360-Degree Images, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12002 LNCS, pp. 63–74, https://doi.org/10.1007/978-3-030-40605-9_6. Barmpoutis, P., & Stathaki, T. (2020). A Novel Framework for Early Fire Detection Using Terrestrial and Aerial 360-Degree Images, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12002 LNCS, pp. 63–74, https://​doi.​org/​10.​1007/​978-3-030-40605-9_​6.
135.
142.
146.
Zurück zum Zitat Ahmad, R., Sundararajan, E. A., & Abu-Ain, T., Analysis the Effect of Clustering and Lightweight Encryption Approaches on WSNs Lifetime, in (2021). International Conference on Electrical Engineering and Informatics (ICEEI), Selangor, Malaysia: IEEE, Oct. 2021, pp. 1–6. https://doi.org/10.1109/ICEEI52609.2021.9611120. Ahmad, R., Sundararajan, E. A., & Abu-Ain, T., Analysis the Effect of Clustering and Lightweight Encryption Approaches on WSNs Lifetime, in (2021). International Conference on Electrical Engineering and Informatics (ICEEI), Selangor, Malaysia: IEEE, Oct. 2021, pp. 1–6. https://​doi.​org/​10.​1109/​ICEEI52609.​2021.​9611120.
148.
Zurück zum Zitat Ahmad, R., Wazirali, R., Abu-Ain, T., & Almohamad, T. A. (Aug. 2022). Adaptive Trust-based Framework for securing and reducing cost in low-cost 6LoWPAN Wireless Sensor Networks. Applied Sciences, 12(17), 8605. https://doi.org/10.3390/app12178605. Ahmad, R., Wazirali, R., Abu-Ain, T., & Almohamad, T. A. (Aug. 2022). Adaptive Trust-based Framework for securing and reducing cost in low-cost 6LoWPAN Wireless Sensor Networks. Applied Sciences, 12(17), 8605. https://​doi.​org/​10.​3390/​app12178605.
157.
160.
Zurück zum Zitat Alshrif, F. F., Sundararajan, E. A., Ahmad, R., & Alkhatib, Y., New Framework for Authentication and key Establishment to Secure 6LoWPAN Networks, in (2021). International Conference on Electrical Engineering and Informatics (ICEEI), Selangor, Malaysia: IEEE, Oct. 2021, pp. 1–6. https://doi.org/10.1109/ICEEI52609.2021.9611135. Alshrif, F. F., Sundararajan, E. A., Ahmad, R., & Alkhatib, Y., New Framework for Authentication and key Establishment to Secure 6LoWPAN Networks, in (2021). International Conference on Electrical Engineering and Informatics (ICEEI), Selangor, Malaysia: IEEE, Oct. 2021, pp. 1–6. https://​doi.​org/​10.​1109/​ICEEI52609.​2021.​9611135.
162.
Zurück zum Zitat Ahmad, R., Wazirali, R., Bsoul, Q., Abu-Ain, T., & Abu-Ain, W. (Jul. 2021). Feature-selection and mutual-clustering approaches to Improve DoS Detection and maintain WSNs’ lifetime. Sensors (Basel, Switzerland), 21(14), 4821. https://doi.org/10.3390/s21144821. Ahmad, R., Wazirali, R., Bsoul, Q., Abu-Ain, T., & Abu-Ain, W. (Jul. 2021). Feature-selection and mutual-clustering approaches to Improve DoS Detection and maintain WSNs’ lifetime. Sensors (Basel, Switzerland), 21(14), 4821. https://​doi.​org/​10.​3390/​s21144821.
Metadaten
Titel
Smart remote sensing network for disaster management: an overview
verfasst von
Rami Ahmad
Publikationsdatum
09.05.2024
Verlag
Springer US
Erschienen in
Telecommunication Systems
Print ISSN: 1018-4864
Elektronische ISSN: 1572-9451
DOI
https://doi.org/10.1007/s11235-024-01148-z