International Conference on Technology Innovations for Crisis Management [ICTICM]
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Item Open Access Automated Flood Impact Detection from Remote Sensing Data using Transfer Learning: A New Zealand Case Study(Sri Lanka Institute of Information Technology, 2026-05-21) Pathirana, N; Ranasinghe, M; Prasanna, RProper flood damage assessment is required for rapid emergency response and recovery planning. Highresolution drone imagery provides greater visual detail compared to satellite imagery and can support more accurate damage assessment after flood events. This work-in-progress study investigates the use of transfer learning with a pre-trained ResNet50 convolutional neural network to classify post-flood drone images. A manually annotated dataset of drone images representing damaged and non-damaged areas was used to finetune the pre-trained model and evaluate its performance using several metrics. The training process employed hyperparameter tuning to select the best model which achieved an accuracy of approximately 87%. These preliminary results demonstrate the potential of transfer learning for flood damage classification using a limited drone image dataset. Future work will focus on comparing the performance of additional deep learning models, incorporating satellite imagery and extending the approach from image-level classification to object-level damage detection.Item Open Access Testing of a resilient community-driven communications network of LoRa devices in Wellington(Sri Lanka Institute of Information Technology, 2026-05-21) Perera, W.M.M; Connor-Kebbell, T; Abeydeera, T; Rallapudi, M.O; Vautier, A; Ngan,B; Prasanna, RModern communications infrastructure such as mobile base stations, routing centres and servers are highly vulnerable to grid power loss and catastrophic damage that occur during natural disasters. Such failures render critical communications infrastructure inoperable exactly when they are needed. To address this, CRISiSLab has deployed and evaluated a Meshtastic LoRa mesh network across Wellington’s varied terrain as a low-power, infrastructure independent communications solution. Testing demonstrated that while terrain was the primary limiting factor, effective city-scale communications is achievable with strategic device placement and appropriate preset selection. These findings suggest that Meshtastic is viable as an emergency backup communication network.Item Open Access Securing Distributed Disaster Early Warning Networks(Sri Lanka Institute of Information Technology, 2026-05-21) Senarathne, K; Dias, D; Prasanna, RThis paper proposes a secure and cost-effective communication and management approach for distributed disaster early warning networks to ensure reliable, low-latency alert dissemination. While decentralized architectures reduce latency by enabling direct device communication, they are highly vulnerable to attacks due to their exposure in public community settings and the challenges posed by Network Address Translation (NAT) and firewalls. Traditional NAT traversal techniques often lack the built-in security required for such sensitive infrastructure. We identify Nebula, an open-source overlay networking tool, as a viable solution because it is lightweight enough for low-resource devices such as the Raspberry Pi typically found in decentralized early warning systems, supports NAT traversal, and provides endto- end encryption. Preliminary experiments conducted in an AWS environment—designed to simulate real-world Raspberry Shake sensor deployments—confirm Nebula’s ability to establish direct peer-to-peer (P2P) connectivity with a single hop and effectively encrypt trafficItem Open Access From Beach to Cliff: Adapting CoastSnap Citizen Science for Coastal Cliff Change Detection Using ML-Assisted Image Registration and Prompted Segmentation(Sri Lanka Institute of Information Technology, 2026-05-21) aramillo-Velez, A; Gamlath, S; Chandirakumar, M; Prasanna, R; de Vilder,S; McColl, S; Tan, M.L; Stewart, C; Ambegoda, T.DCoastSnap is a citizen science tool that uses repeat smartphone photographs from fixed stations to monitor coastal change, yet it has rarely been applied to coastal cliffs. We test a workflow for cliff change screening using a controlled pilot CoastSnap station at Ōnaero, New Zealand (iPhone 12), integrating (i) Machine Learningassisted ground control point (GCP) transfer for image registration, (ii) pinhole camera calibration and reprojection-based geo-rectification onto a curved cliff-surface model, and (iii) prompted segmentation for isolating cliff-related features. Auto-GCP benchmarking shows a tradeoff between precision and robustness: the Scale-Invariant Feature Transform (SIFT) model achieves low localisation error when successful, but is sensitive to changes in illumination. In contrast, the Local Feature ransformer (LoFTR) model provides a higher detection yield and more stable performance, but is sensitive to the threshold used. Nevertheless, it is well suited to operational use with human-inthe- loop verification. Calibration produced consistent parameters across repeat images, with focal length estimates matching device specifications. Visual segmentation based only in Regions of Interest (RoI) often merged adjacent objects, while text-guided Segment Anything Model (LangSAM) delineated cliff and debris more reliably than fracture-like features. Preliminary detection of the supply and removal of debris highlights the potential for quantifying the frequency and magnitude of mass movements at each cliff.Item Open Access Beyond Internet Dependency: LoRa for Post- Earthquake Structural Monitoring(Sri Lanka Institute of Information Technology, 2026-05-21) Rallapudi, M.O; Vautier, A; Ngan, B; Perera, P; Prasanna, RAcquiring structural response data during and after earthquakes is essential for assessing threats to critical infrastructure; however, conventional transmission systems rely on Internet connectivity that is often disrupted during major seismic events. This study evaluates Long Range (LoRa) radio as a low-power, infrastructure-independent alternative for transmitting building instrumentation data when conventional networks fail. Field experiments were conducted across three New Zealand cities, testing performance under varying radio configurations, elevations, and urban topographies. Results demonstrate reliable urban communication ranges of up to 1.6 km under optimal settings. Elevation was the dominant deployment factor, with packet delivery ratios (PDR) improving from 0–40% at ground level to near-100% at 500 m radial distance when transmitters were positioned on upper floors. Building-to-building links achieved 75–100% PDR with received signal strength values between −55 and −110 dBm, while terrain features such as hills and dense vegetation caused significant attenuation and occasional link failure at shorter distances. These findings confirm the feasibility of LoRa for post-earthquake structural monitoring and provide quantitative guidance for elevation-aware, terrain-conscious deployment in urban environments.Item Open Access Structural Gaps in Disaster Technology Systems: A Longitudinal Review of Post-Event Assessments in Aotearoa New Zealand(Sri Lanka Institute of Information Technology, 2026-05-21) Tan, M.L; Adikari, K.E; Prasanna, ROver the past decade, Aotearoa New Zealand has experienced multiple large-scale disasters that have exposed recurring challenges in information management, communication, coordination, and technology integration within the emergency management system. This paper analyses eleven major disaster-response review reports published between 2012 and 2024 to examine how technology-related issues are represented in official assessments and to identify structural gaps. Using a mixed-method approach combining keyword frequency analysis and qualitative thematic analysis, the study finds that information and communication dominate review discourse, while explicit references to technology, situational awareness, and common operating picture appear less frequently and inconsistently. Longitudinal synthesis reveals persistent reform themes, including calls for nationally integrated platforms, interoperable systems, professionalised capability, and shared intelligence frameworks. Yet implementation details regarding architectural ownership, standards, lifecycle management, and funding remain limited. The paper advances a structured research agenda organised around four domains: data governance and architecture, decision-support design, ICT resilience and interoperability, and organisational technology governance.