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Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience

Yıl 2025, Cilt: 9 Sayı: 2, 211 - 222, 29.12.2025
https://doi.org/10.46460/ijiea.1768923
https://izlik.org/JA33HC49WN

Öz

Disaster management is undergoing a paradigm shift driven by the convergence of emerging digital technologies. Traditional systems often operate as non-integrated structures, which limits their capacity to respond and adapt in multi-hazard scenarios. In this context, Artificial Intelligence (AI), Blockchain, and Digital Twin (DT) technologies have emerged as transformative components in building smart, resilient disaster response frameworks. This review aims to synthesize the current state of research and applications involving these three technologies, with a particular focus on their integration potential for cohesive, secure, and adaptive disaster management systems. The study systematically examines how AI contributes to predictive analytics and decision-making, how Blockchain enhances data integrity, transparency, and coordination, and how DT enables real-time simulation and scenario planning. It also explores the interplay between these technologies and highlights emerging frameworks that attempt to combine them in unified architectures. Furthermore, key technical and operational challenges such as interoperability, data standardization, and real-time synchronization are discussed. By analyzing existing solutions and identifying critical research gaps, this review provides a roadmap toward integrated, intelligent disaster management systems. The review emphasizes the unique contributions of each technology and underscores the need for interoperability, effective data governance, and real-time decision support in integrated disaster management.

Kaynakça

  • Das, S., Choudhury, M. R., Chatterjee, B., Das, P., Bagri, S., Paul, D., ... & Dutta, S. (2024). Unraveling the urban climate crisis: Exploring the nexus of urbanization, climate change, and their impacts on the environment and human well-being–A global perspective. AIMS Public Health, 11(3), 963.
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  • Klasa, K., Trump, B. D., Dulin, S., Smith, M., Jarman, H., & Linkov, I. (2025). A Resilience-Augmented Approach to Compound Threats and Risk Governance: A Systems Perspective on Navigating Complex Crises. Environments, 12(2), 64.
  • Sarı, B., & Özer, Y. E. (2024). Coordination analysis in disaster management: A qualitative approach in Türkiye. International Journal of Disaster Risk Reduction, 100, 104168.
  • Lagap, U., & Ghaffarian, S. (2025). Digital twin-enabled post-disaster damage and recovery monitoring with deep learning: leveraging transfer learning, attention mechanisms, and explainable AI. Geomatics, Natural Hazards and Risk, 16(1), 2485329.
  • Habib, A., Alnaemi, A., & Habib, M. (2024). Developing a framework for integrating blockchain technology into earthquake risk mitigation and disaster management strategies of smart cities. Smart and Sustainable Built Environment.
  • Gobinath, A., Reshmika, K. S., & Sivakarthi, G. (2024). Predicting Natural Disasters With AI and Machine Learning. In Utilizing AI and Machine Learning for Natural Disaster Management (pp. 254-273). IGI Global Scientific Publishing.
  • Rajapaksha, D., Siriwardana, C., Ruparathna, R., Maqsood, T., Setunge, S., Rajapakse, L., & De Silva, S. (2024). Systematic Mapping of Global Research on Disaster Damage Estimation for Buildings: A Machine Learning-Aided Study. Buildings, 14(6), 1864.
  • Karaduman, Ö., & Gülhas, G. (2025). Blockchain-Enabled Supply Chain Management: A Review of Security, Traceability, and Data Integrity Amid the Evolving Systemic Demand. Applied Sciences (2076-3417), 15(9).
  • Soykan, B., Blanc, G., & Rabadi, G. (2025). A Proof-of- Concept Digital Twin for Real-Time Simulation: Leveraging a Model-Based Systems Engineering Approach. IEEE Access.
  • Matei, A., & Cocoșatu, M. (2024). Artificial Internet of Things, sensor-based digital twin urban computing vision algorithms, and blockchain cloud networks in sustainable smart city administration. Sustainability, 16(16), 6749.
  • Shevchuk, R., Lishchynskyy, I., Ciura, M., Lyzun, M., Kozak, R., & Kasianchuk, M. (2025). Application of Blockchain Technology in Emergency Management Systems: A Bibliometric Analysis. Applied Sciences, 15(10), 5405.
  • Tyagi, A. K., Kumari, S., & Surve, T. (2024). Integration of Digital Twin and Blockchain for Smart Cities. Digital Twin and Blockchain for Smart Cities, 81-100.
  • Fida, K., Abbasi, U., Adnan, M., Iqbal, S., & Gasim, S. E. Integration of digital twin, blockchain, artificial intelligence in an IoT Metaverse environment for mitigation and assessment of cascading failure events in smart grids: Recent advancement and future research challenges.
  • Chen, J., Seng, K. P., Smith, J., & Ang, L. M. (2024). Situation awareness in ai-based technologies and multimodal systems: Architectures, challenges and applications. IEEE Access, 12, 88779-88818.
  • Akhyar, A., Zulkifley, M. A., Lee, J., Song, T., Han, J., Cho, C., ... & Hong, B. W. (2024). Deep artificial intelligence applications for natural disaster management systems: A methodological review. Ecological Indicators, 163, 112067.
  • Wang, Q., Zhang, Y., Zhang, J., Zhao, Z., & He, X. (2024). On the use of VMD-LSTM neural network for approximate earthquake prediction. Natural Hazards, 120(14), 13351-13367.
  • Al-Aizari, A. R., Alzahrani, H., Althuwaynee, O. F., Al-Masnay, Y. A., Ullah, K., Park, H. J., ... & Liu, X. (2024). Uncertainty reduction in Flood susceptibility mapping using Random Forest and eXtreme Gradient Boosting algorithms in two Tropical Desert cities, Shibam and Marib, Yemen. Remote Sensing, 16(2), 336.
  • Boroujeni, S. P. H., Razi, A., Khoshdel, S., Afghah, F., Coen, J. L., O’Neill, L., ... & Vamvoudakis, K. G. (2024). A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management. Information Fusion, 108, 102369.
  • Keshri, D., Sarkar, K., & Chattoraj, S. L. (2025). Comparative Assessment of XGBoost Model and Hyper-Parameter Optimization Techniques in Landslide Susceptibility Mapping: A Case Study of Aglar Watershed, Part of Lesser Himalaya. In Landslides: Analysis, Modeling and Mitigation (pp. 287-301). Cham: Springer Nature Switzerland.
  • Kumar, V., Goodarzian, F., Ghasemi, P., Chan, F. T., & Gupta, N. (2025). Artificial intelligence applications in healthcare supply chain networks under disaster conditions. International Journal of Production Research, 63(2), 395-403.
  • Mancy, H., Ghannam, N. E., Abozeid, A., & Taloba, A. I. (2025). Decentralized multi-agent federated and reinforcement learning for smart water management and disaster response. Alexandria Engineering Journal, 126, 8-29.
  • Hu, Y., Zhang, Q., Zhu, H., Wang, B., Xiong, H., & Wang, H. (2025). Scalable intermediate-term earthquake forecasting with multimodal fusion neural networks. Scientific Reports, 15(1), 9748.
  • Mosalla Tabari, M., Ebadi, H., & Alizadeh Zakaria, Z. (2025). PSO-random forest approach to enhance flood-prone area identification: using ground and remote sensing data (case study: Ottawa-Gatineau). Earth Science Informatics, 18(2), 215.
  • Zhang, X., Zhang, M., Liu, X., Terfa, B. K., Nam, W. H., Gu, X., ... & Chen, N. (2024). Review on the progress and future prospects of geological disasters prediction in the era of artificial intelligence. Natural Hazards, 1-41.
  • Camps-Valls, G., Fernández-Torres, M. Á., Cohrs, K. H., Höhl, A., Castelletti, A., Pacal, A., ... & Williams, T. (2025). Artificial intelligence for modeling and understanding extreme weather and climate events. Nature Communications, 16(1), 1919.
  • Dutta, L., Jana, N., & Pulpadan, Y. A. (2025). Towards synergistic AI-driven ensemble framework for earthquake and rainfall induced landslide risks in Sikkim Himalayas. Natural Hazards, 121(8), 9043-9066.
  • Aboualola, M., Abualsaud, K., Khattab, T., Zorba, N., & Hassanein, H. S. (2023). Edge technologies for disaster management: A survey of social media and artificial intelligence integration. IEEE access, 11, 73782-73802.
  • Khan, S. M., Shafi, I., Butt, W. H., Diez, I. D. L. T., Flores, M. A. L., Galán, J. C., & Ashraf, I. (2023). A systematic review of disaster management systems: approaches, challenges, and future directions. Land, 12(8), 1514.
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Bütünleşik Afet Yönetimine Doğru: Akıllı Dayanıklılık için Yapay Zekâ, Blockchain ve Dijital İkiz Teknolojilerine Yönelik Bir İnceleme

Yıl 2025, Cilt: 9 Sayı: 2, 211 - 222, 29.12.2025
https://doi.org/10.46460/ijiea.1768923
https://izlik.org/JA33HC49WN

Öz

Afet yönetimi, ortaya çıkan dijital teknolojilerin yakınsamasıyla yönlendirilen bir paradigma değişimi yaşamaktadır. Geleneksel sistemler çoğunlukla entegre olmayan yapılar olarak çalışmakta, bu da çoklu tehlike senaryolarında tepki verme ve uyum sağlama kapasitelerini sınırlamaktadır. Bu bağlamda, Yapay Zekâ (YZ), Blockchain ve Dijital İkiz (DT) teknolojileri, akıllı ve dirençli afet müdahale çerçevelerinin inşasında dönüştürücü bileşenler olarak öne çıkmaktadır. Bu inceleme, söz konusu üç teknolojiyi içeren mevcut araştırma ve uygulamaların güncel durumunu sentezlemeyi ve özellikle bunların bütünleşik, güvenli ve uyarlanabilir afet yönetim sistemlerine entegrasyon potansiyeline odaklanmayı amaçlamaktadır. Çalışma, YZ’nin öngörücü analiz ve karar alma süreçlerine nasıl katkı sağladığını, Blockchain’in veri bütünlüğünü, şeffaflığı ve koordinasyonu nasıl geliştirdiğini ve DT’nin gerçek zamanlı simülasyon ile senaryo planlamasını nasıl mümkün kıldığını sistematik olarak incelemektedir. Ayrıca bu teknolojiler arasındaki etkileşimi ele almakta ve bunları tek bir mimaride birleştirmeyi amaçlayan yeni ortaya çıkan çerçeveleri vurgulamaktadır. Bunun yanı sıra, birlikte çalışabilirlik, veri standardizasyonu ve gerçek zamanlı senkronizasyon gibi temel teknik ve operasyonel zorluklar da tartışılmaktadır. Mevcut çözümleri analiz ederek ve kritik araştırma boşluklarını belirleyerek, bu inceleme entegre, akıllı afet yönetim sistemlerine yönelik bir yol haritası sunmaktadır. İnceleme, her teknolojinin benzersiz katkılarını vurgulamakta ve entegre afet yönetiminde birlikte çalışabilirlik, etkili veri yönetişimi ve gerçek zamanlı karar desteği gereksiniminin altını çizmektedir.

Kaynakça

  • Das, S., Choudhury, M. R., Chatterjee, B., Das, P., Bagri, S., Paul, D., ... & Dutta, S. (2024). Unraveling the urban climate crisis: Exploring the nexus of urbanization, climate change, and their impacts on the environment and human well-being–A global perspective. AIMS Public Health, 11(3), 963.
  • Li, X., Stringer, L. C., & Dallimer, M. (2022). The impacts of urbanisation and climate change on the urban thermal environment in Africa. Climate, 10(11), 164.
  • Waseem, H. B., & Rana, I. A. (2025). A meta-review of disaster research. Natural Hazards, 1-34.
  • Klasa, K., Trump, B. D., Dulin, S., Smith, M., Jarman, H., & Linkov, I. (2025). A Resilience-Augmented Approach to Compound Threats and Risk Governance: A Systems Perspective on Navigating Complex Crises. Environments, 12(2), 64.
  • Sarı, B., & Özer, Y. E. (2024). Coordination analysis in disaster management: A qualitative approach in Türkiye. International Journal of Disaster Risk Reduction, 100, 104168.
  • Lagap, U., & Ghaffarian, S. (2025). Digital twin-enabled post-disaster damage and recovery monitoring with deep learning: leveraging transfer learning, attention mechanisms, and explainable AI. Geomatics, Natural Hazards and Risk, 16(1), 2485329.
  • Habib, A., Alnaemi, A., & Habib, M. (2024). Developing a framework for integrating blockchain technology into earthquake risk mitigation and disaster management strategies of smart cities. Smart and Sustainable Built Environment.
  • Gobinath, A., Reshmika, K. S., & Sivakarthi, G. (2024). Predicting Natural Disasters With AI and Machine Learning. In Utilizing AI and Machine Learning for Natural Disaster Management (pp. 254-273). IGI Global Scientific Publishing.
  • Rajapaksha, D., Siriwardana, C., Ruparathna, R., Maqsood, T., Setunge, S., Rajapakse, L., & De Silva, S. (2024). Systematic Mapping of Global Research on Disaster Damage Estimation for Buildings: A Machine Learning-Aided Study. Buildings, 14(6), 1864.
  • Karaduman, Ö., & Gülhas, G. (2025). Blockchain-Enabled Supply Chain Management: A Review of Security, Traceability, and Data Integrity Amid the Evolving Systemic Demand. Applied Sciences (2076-3417), 15(9).
  • Soykan, B., Blanc, G., & Rabadi, G. (2025). A Proof-of- Concept Digital Twin for Real-Time Simulation: Leveraging a Model-Based Systems Engineering Approach. IEEE Access.
  • Matei, A., & Cocoșatu, M. (2024). Artificial Internet of Things, sensor-based digital twin urban computing vision algorithms, and blockchain cloud networks in sustainable smart city administration. Sustainability, 16(16), 6749.
  • Shevchuk, R., Lishchynskyy, I., Ciura, M., Lyzun, M., Kozak, R., & Kasianchuk, M. (2025). Application of Blockchain Technology in Emergency Management Systems: A Bibliometric Analysis. Applied Sciences, 15(10), 5405.
  • Tyagi, A. K., Kumari, S., & Surve, T. (2024). Integration of Digital Twin and Blockchain for Smart Cities. Digital Twin and Blockchain for Smart Cities, 81-100.
  • Fida, K., Abbasi, U., Adnan, M., Iqbal, S., & Gasim, S. E. Integration of digital twin, blockchain, artificial intelligence in an IoT Metaverse environment for mitigation and assessment of cascading failure events in smart grids: Recent advancement and future research challenges.
  • Chen, J., Seng, K. P., Smith, J., & Ang, L. M. (2024). Situation awareness in ai-based technologies and multimodal systems: Architectures, challenges and applications. IEEE Access, 12, 88779-88818.
  • Akhyar, A., Zulkifley, M. A., Lee, J., Song, T., Han, J., Cho, C., ... & Hong, B. W. (2024). Deep artificial intelligence applications for natural disaster management systems: A methodological review. Ecological Indicators, 163, 112067.
  • Wang, Q., Zhang, Y., Zhang, J., Zhao, Z., & He, X. (2024). On the use of VMD-LSTM neural network for approximate earthquake prediction. Natural Hazards, 120(14), 13351-13367.
  • Al-Aizari, A. R., Alzahrani, H., Althuwaynee, O. F., Al-Masnay, Y. A., Ullah, K., Park, H. J., ... & Liu, X. (2024). Uncertainty reduction in Flood susceptibility mapping using Random Forest and eXtreme Gradient Boosting algorithms in two Tropical Desert cities, Shibam and Marib, Yemen. Remote Sensing, 16(2), 336.
  • Boroujeni, S. P. H., Razi, A., Khoshdel, S., Afghah, F., Coen, J. L., O’Neill, L., ... & Vamvoudakis, K. G. (2024). A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management. Information Fusion, 108, 102369.
  • Keshri, D., Sarkar, K., & Chattoraj, S. L. (2025). Comparative Assessment of XGBoost Model and Hyper-Parameter Optimization Techniques in Landslide Susceptibility Mapping: A Case Study of Aglar Watershed, Part of Lesser Himalaya. In Landslides: Analysis, Modeling and Mitigation (pp. 287-301). Cham: Springer Nature Switzerland.
  • Kumar, V., Goodarzian, F., Ghasemi, P., Chan, F. T., & Gupta, N. (2025). Artificial intelligence applications in healthcare supply chain networks under disaster conditions. International Journal of Production Research, 63(2), 395-403.
  • Mancy, H., Ghannam, N. E., Abozeid, A., & Taloba, A. I. (2025). Decentralized multi-agent federated and reinforcement learning for smart water management and disaster response. Alexandria Engineering Journal, 126, 8-29.
  • Hu, Y., Zhang, Q., Zhu, H., Wang, B., Xiong, H., & Wang, H. (2025). Scalable intermediate-term earthquake forecasting with multimodal fusion neural networks. Scientific Reports, 15(1), 9748.
  • Mosalla Tabari, M., Ebadi, H., & Alizadeh Zakaria, Z. (2025). PSO-random forest approach to enhance flood-prone area identification: using ground and remote sensing data (case study: Ottawa-Gatineau). Earth Science Informatics, 18(2), 215.
  • Zhang, X., Zhang, M., Liu, X., Terfa, B. K., Nam, W. H., Gu, X., ... & Chen, N. (2024). Review on the progress and future prospects of geological disasters prediction in the era of artificial intelligence. Natural Hazards, 1-41.
  • Camps-Valls, G., Fernández-Torres, M. Á., Cohrs, K. H., Höhl, A., Castelletti, A., Pacal, A., ... & Williams, T. (2025). Artificial intelligence for modeling and understanding extreme weather and climate events. Nature Communications, 16(1), 1919.
  • Dutta, L., Jana, N., & Pulpadan, Y. A. (2025). Towards synergistic AI-driven ensemble framework for earthquake and rainfall induced landslide risks in Sikkim Himalayas. Natural Hazards, 121(8), 9043-9066.
  • Aboualola, M., Abualsaud, K., Khattab, T., Zorba, N., & Hassanein, H. S. (2023). Edge technologies for disaster management: A survey of social media and artificial intelligence integration. IEEE access, 11, 73782-73802.
  • Khan, S. M., Shafi, I., Butt, W. H., Diez, I. D. L. T., Flores, M. A. L., Galán, J. C., & Ashraf, I. (2023). A systematic review of disaster management systems: approaches, challenges, and future directions. Land, 12(8), 1514.
  • Varsha, V. R., Naganandini, S., & Hariharan, C. (2024). Utilizing AI and machine learning for natural disaster management: predicting natural disasters with AI and machine learning. In Internet of things and ai for natural disaster management and prediction (pp. 279-304). IGI Global Scientific Publishing.
  • Chen, L., Han, B., Wang, X., Zhao, J., Yang, W., & Yang, Z. (2023). Machine learning methods in weather and climate applications: A survey. Applied Sciences, 13(21), 12019.
  • Joshi, A., Agarwal, S., Kanungo, D. P., & Panigrahi, R. K. (2023). Integration of edge–ai into iot–cloud architecture for landslide monitoring and prediction. IEEE Transactions on Industrial Informatics, 20(3), 4246-4258.
  • Albahri, A. S., Khaleel, Y. L., Habeeb, M. A., Ismael, R. D., Hameed, Q. A., Deveci, M., ... & Alzubaidi, L. (2024). A systematic review of trustworthy artificial intelligence applications in natural disasters. Computers and Electrical Engineering, 118, 109409.
  • Afroogh, S., Mostafavi, A., Akbari, A., Pouresmaeil, Y., Goudarzi, S., Hajhosseini, F., & Rasoulkhani, K. (2024). Embedded ethics for responsible artificial intelligence systems (EE-RAIS) in disaster management: A conceptual model and its deployment. AI and Ethics, 4(4), 1117-1141.
  • Das, P., Singh, M., Roy, D. G., & Pise, A. A. (2025). Blockchain of things for smart disaster management. In The Role of Blockchain in Disaster Management (pp. 51-68). Academic Press.
  • Zachariah, M., Avanesh, N. M., & Raghupathi, K. (2025). Application of blockchain technology in disaster risk management. In The Role of Blockchain in Disaster Management (pp. 87-110). Academic Press.
  • Madhusudhan, R., & Rithesh, S. (2025, January). Decentralized Disaster Management in Smart Cities: Leveraging IPFS, Blockchain, and Edge Computing. In 2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC) (pp. 1-6). IEEE.
  • Divyashree, K. S., & Mishra, A. (2025). Intelligent blockchain technology for health disaster management systems: Lessons from COVID-19 and way forward. In The Role of Blockchain in Disaster Management (pp. 111-127). Academic Press.
  • Marletta, D., Midolo, A., & Tramontana, E. (2025). A Blockchain-Based Strategy for Certifying Timestamps in a Distributed Healthcare Emergency Response Systems. Future Internet, 17(5), 210.
  • Wang, Q., & Liu, Y. (2025). Blockchain empowered dynamic access control for secure data sharing in collaborative emergency management. Information Processing & Management, 62(3), 103960.
  • Rajagopal, M., Ramkumar, S., Thimmiaraja, J., Gobinath, R., & Kumar, K. S. (2025). Blockchain-based model for disaster relief supply chain management. In The Role of Blockchain in Disaster Management (pp. 33-49). Academic Press.
  • Arya, A., Gupta, G., & Saini, N. (2025). Exploring blockchain technology and its potential in non-governmental organizations (NGOs). In Intelligent Computing and Communication Techniques (pp. 491-495). CRC Press.
  • Sowmya, G., Sridevi, R., & Rao, K. S. (2025). Blockchain for Disaster Recovery: Enhancing Resilience, Coordination, and Trust in Crisis Management. In AI and Emerging Technologies for Emergency Response and Smart Cities (pp. 117-136). IGI Global Scientific Publishing.
  • Boustani, N. M., & Elisabetta, M. (2022). Smart Insurance Contracts Shielding Pandemic Business Disruption in Developing Countries and Blockchain Solution. FinTech, 1(4), 294-309.
  • Abraha, D. T. (2025). Blockchain-based solution for addressing refugee management in the Global South: transparent and accessible resource sharing in humanitarian organizations. Frontiers in Human Dynamics, 6, 1391163.
  • Razavi, H., Titidezh, O., Asgary, A., & Bonakdari, H. (2024). Building resilient smart cities: The role of digital twins and generative AI in disaster management strategy. In Digital Twin Computing for Urban Intelligence (pp. 95-118). Singapore: Springer Nature Singapore.
  • Wang, Y., Yue, Q., Lu, X., Gu, D., Xu, Z., Tian, Y., & Zhang, S. (2024). Digital twin approach for enhancing urban resilience: A cycle between virtual space and the real world. Resilient Cities Struct, 3, 34-45.
  • Yamashita, T., Sekimoto, Y., Koshihara, M., Nakagawa, T., O-Tani, H., & Horiuchi, T. (2025). A digital twin prototype to visualize heterogeneous seismic damage simulation results on web-GIS. Journal of Asian Architecture and Building Engineering, 24(3), 1277-1295.
  • Riaz, K., McAfee, M., & Gharbia, S. S. (2023). Management of climate resilience: exploring the potential of digital twin technology, 3D city modelling, and early warning systems. Sensors, 23(5), 2659.
  • Ertas, N. (2024). Autocratization, disaster management, and the politics of public administration in Turkey. Public Integrity, 26(5), 624-634.
  • Sarı Karademir, B., & Sahin, S. B. (2025). Gender and disaster management in Turkey: a strategic-relational analysis of the state response to the February 2023 earthquakes. Southeast European and Black Sea Studies, 1-19.
  • Korkmaz, M., Zulfikar, A. C., & Demirkesen, S. (2024). Leveraging digital twins as a common operating picture for disaster management: case of seismic hazards. ISPRS International Journal of Geo-Information, 13(12), 430.
  • Guo, A., Jiang, N., Xu, Y., Liu, T., Xu, T., Bastos, L., ... & Jia, R. (2025). Land surface temperature, tropospheric and ionospheric anomalies analysis and implementation of a co-seismic PWV digital twin for the February 6, 2023 Turkey earthquake. Geomatics, Natural Hazards and Risk, 16(1), 2491470.
  • Ölmez, M., & Bayrak, B. (2025). Doğal afetler sonrası sürdürülebilir bir akıllı kent planlamasında yerel yönetişimin rolü: tokyo kent örneği ve Malatya’nın akıllı kent planlamasına öneriler. Karamanoğlu Mehmetbey Üniversitesi Sosyal ve Ekonomik Araştırmalar Dergisi, 27(48), 185-209.
  • Korkmaz, M., Akyildiz, Y. E., Demirkesen, S., Toprak, S., Nowak, P., & Ciftci, B. (2025). A Digital Twin Approach to Sustainable Disaster Management: Case of Cayirova. Sustainability, 17(21), 9626.
  • Ölmez, M. (2025). Yerel Sürdürülebilirlikte dijital ikiz teknolojisi ve doğal afetleri önlemede etkisi: Japonya Örneği. İşletme, 6(1), 103-127.
  • Rinaldi, M., Caterino, M., Riemma, S., Macchiaroli, R., & Fera, M. (2025). Emergency supply chain resilience enhanced through blockchain and digital twin technology. Logistics, 9(1), 43.
  • Ahmmed, M. S., Khan, L., Mahmood, M. A., & Liou, F. (2025). Digital Twins, AI, and cybersecurity in additive manufacturing: A comprehensive review of current trends and challenges. Machines, 13(8), 691.
  • Sarigul, F. H., & Gunaydin, H. M. (2025). Integrated BIM, GIS and interoperable digital technologies in lifecycle management of building construction projects: systematic literature review. Smart and Sustainable Built Environment. https://doi.org/10.1108/SASBE-08-2024-0312
  • Ranatunga, S., Ødegård, R. S., Jetlund, K., & Onstein, E. (2025). Use of semantic web technologies to enhance the integration and interoperability of environmental geospatial data: A framework based on ontology-based data access. ISPRS International Journal of Geo-Information, 14(2), 52.
  • Akram, J., Akram, A., Ingle, P., Jhaveri, R. H., Anaissi, A., & Akhunzada, A. (2025). Privacy-Preserving Spatial Crowdsourcing Drone Services for Post-Disaster Infrastructure Monitoring: A Conditional Federated Learning Approach. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
  • Ölmez, M., & Bayrak, B. Kamu mali denetiminde dijital ikiz kullanımı: Sayıştay için model önerisi. Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 15(29), 269-296.
  • Türkoğlu, Ç., & Çelik, R. (2024). Dijital dönüşüm sürecinde blok zinciri: teorik yaklaşımlar ve sektörel uygulamalar. Kamu Ekonomisi ve Kamu Mali Yönetimi Dergisi, 4(2), 83-111.
Toplam 64 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yazılım Mühendisliği (Diğer)
Bölüm Derleme
Yazarlar

Özgür Karaduman 0000-0002-6569-3616

Gönderilme Tarihi 19 Ağustos 2025
Kabul Tarihi 6 Aralık 2025
Yayımlanma Tarihi 29 Aralık 2025
DOI https://doi.org/10.46460/ijiea.1768923
IZ https://izlik.org/JA33HC49WN
Yayımlandığı Sayı Yıl 2025 Cilt: 9 Sayı: 2

Kaynak Göster

APA Karaduman, Ö. (2025). Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience. International Journal of Innovative Engineering Applications, 9(2), 211-222. https://doi.org/10.46460/ijiea.1768923
AMA 1.Karaduman Ö. Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience. ijiea, IJIEA. 2025;9(2):211-222. doi:10.46460/ijiea.1768923
Chicago Karaduman, Özgür. 2025. “Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience”. International Journal of Innovative Engineering Applications 9 (2): 211-22. https://doi.org/10.46460/ijiea.1768923.
EndNote Karaduman Ö (01 Aralık 2025) Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience. International Journal of Innovative Engineering Applications 9 2 211–222.
IEEE [1]Ö. Karaduman, “Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience”, ijiea, IJIEA, c. 9, sy 2, ss. 211–222, Ara. 2025, doi: 10.46460/ijiea.1768923.
ISNAD Karaduman, Özgür. “Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience”. International Journal of Innovative Engineering Applications 9/2 (01 Aralık 2025): 211-222. https://doi.org/10.46460/ijiea.1768923.
JAMA 1.Karaduman Ö. Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience. ijiea, IJIEA. 2025;9:211–222.
MLA Karaduman, Özgür. “Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience”. International Journal of Innovative Engineering Applications, c. 9, sy 2, Aralık 2025, ss. 211-22, doi:10.46460/ijiea.1768923.
Vancouver 1.Özgür Karaduman. Towards Integrated Disaster Management: A Review of AI, Blockchain, and Digital Twin Technologies for Smart Resilience. ijiea, IJIEA. 01 Aralık 2025;9(2):211-22. doi:10.46460/ijiea.1768923