When Networks Fail, SARA Stands Up: Offline Flood Rescue with Gemma 4 E4B

During major floods, such as the 2022 Pakistan Floods that displaced over 33 million people, communication networks often fail, leaving victims unable to signal for help. The SARA (Safety And Rescue Assistant) system addresses this by creating a 100% offline local network on a single laptop, allowing victims to report emergencies via a mobile browser. Powered by Google's Gemma 4 4B model running locally, SARA processes multimodal reports, enables natural language commands for coordinators, and updates a real-time dashboard—all without an internet connection.

This is a submission for the Gemma 4 Challenge: Build with Gemma 4 During major floods—like the catastrophic 2022 Pakistan Floods that displaced over 33 million people—mobile towers lose power and internet services collapse. This creates a critical communication blackout where stranded victims cannot signal for help, and rescue teams deploy boats, helicopters, and medical assets based on guesswork. SARA Safety And Rescue Assistant is a 100% offline-first, local emergency command center. Deployed on a single coordinator laptop alongside a simple Wi-Fi hotspot, it creates a private local network—no internet required. SARA simplifies disaster coordination into a seamless, offline process: Flood victims connect to the hotspot SARA-HELP and access SARA’s intake form using their mobile browser—no app installation needed. Here is the walkthrough of SARA's offline system deployment, victim-side emergency reporting form, and real-time dashboard triage updates: The complete codebase, configurations, and deployment steps are fully open-source and available on GitHub: 👉 GitHub Repository: SARA Offline Rescue At the center of SARA is Google's Gemma 4 Edge-optimized family gemma4:e4b / 4B running locally on the coordinator laptop via Ollama. Gemma 4 powers SARA in three major ways: Disaster response centers operate on battery backups or portable generators. I needed a highly capable model that could run locally on consumer-grade laptop CPUs/GPUs without needing a connection to cloud servers. Gemma 4 4B fits comfortably within under 8GB VRAM, delivering stable, sub-5-second local inferences in the field. Stranded victims report emergencies under high stress. Gemma 4's native multimodal capabilities allow me to process multiple modalities in a single pipeline without context switching. nomic-embed-text embeddings, injecting critical first-aid instructions into Gemma's prompt.SARA provides a natural language command box for rescue coordinators. When a coordinator types "Are there any available rescue boats?" or "Dispatch helicopter to case 3", Gemma 4 maps the query to custom Python tools dispatch rescue team , get resource status , etc. via Ollama's native tool calling. It updates the SQLite database, triggers WebSocket alerts, and returns structured confirmation text—all fully offline.