Backend
FireOPS: A Human-Centric Emergency Operations Platform
arXiv cs.HC0 views
arXiv:2611.06176v1 Announce Type: cross Abstract: Volunteer fire brigades rely on fragmented alerting channels and radio plus paper for situational awareness, hindering a shared common operational picture (COP). FireOPS integrates smartphone alerting, navigation, a live geospatial COP, a district resource-load overview and contextual manuals into a human-centric decision-support surface for commanders and responders, running on an edge + cloud architecture whose dual-channel provides source-level redundancy against failure of either the radio or the provincial server feed; delivery to smartphones still depends on the cloud core and mobile networks. This lessons-learned report presents the design rationale, positions FireOPS within emergency-response information systems research, and reports operational findings from a primary log extract of a major regional flood in 2024 and from the 2025 public app release. A feature-matrix comparison with DIVERA 24/7, blaulichtSMS and the LifeRescue prototype identifies COP, decision support and dual-ingestion redundancy as the main differentiators, and we map the operational gaps observed during the flood to concrete engineering responses, deployed or in active development.
Source:https://arxiv.org/abs/2611.06176PreviousBobFlow: Towards Human-Agent Collaborative Data Science Using DataflowsNextGPUMAP: GPU-Accelerated Progressive Uniform Manifold Approximation and Projection
Related posts
GTI-mSEMP Framework : A Proposed Framework to Simulate Malware Propagation with Inclusion of Attacker-Defender Strategy
0arXiv cs.NI
When Does Risk-Controlled Throughput Forecasting Actually Control Risk? A Reproduction Study on LEO Satellite Link
0arXiv cs.NI
Mobility-Aware Mobile Edge Computing for Energy-Balanced Data Collection in IoT-Enabled Underwater Sensor Networks
0arXiv cs.NI
Coexistence-Aware Antenna Tilt and Resource Allocation for Cellular-Connected UAV Corridors
0arXiv cs.NI
StarWorld: A Cross-Layer World Model for Starlink Prediction and Streaming
0arXiv cs.NI
The Confidence Score: a New Measure on Kernels
0arXiv eess.SP