A brandable foundation for crisis analytics, risk maps, and preparedness dashboards.
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Afet.ai is a focused initiative on using artificial intelligence to make disaster response faster, safer, and more coordinated.
When emergencies strike—earthquakes, floods, wildfires, storms—information is scattered and time is scarce.
Our aim is to turn raw, noisy data into practical signals that responders and communities can act on immediately.
We combine simple, robust design with transparent AI so that people on the ground can benefit without needing technical expertise.
The core idea is to support decisions that must be made under pressure: where to send teams first, which routes are open, how needs are changing, and what will become critical in the next few hours.
Afet.ai can fuse sensor feeds, satellite imagery, field reports, and public messages to generate clear, human‑readable summaries—highlighting risks and opportunities rather than overwhelming teams with dashboards.
Privacy and dignity are central principles.
We minimize personal data, prefer anonymous aggregation, and promote consent‑aware practices so that help never becomes surveillance.
All recommendations are accompanied by plain‑language explanations and confidence indicators, allowing professionals to judge the output quickly.
For communities, we translate complex updates into accessible messages and multilingual alerts that maintain key technical terms while reducing fear.
Our practical approach focuses on three layers: readiness, response, and recovery.
In readiness, we create checklists, playbooks, and training prompts that improve coordination before an event occurs.
During response, we help prioritize deployments, logistics, and communications.
In recovery, we support needs assessments and transparent reporting so aid reaches people fairly.
Afet.ai is a premium .ai domain with a clear social purpose: to amplify human effort through honest, reliable AI so that more lives and livelihoods are protected.
Afet.ai; deprem, sel, yangın ve fırtına gibi afetlerde bilgi karmaşasını azaltıp ekiplere hızlı ve güvenilir içgörüler sunmayı amaçlayan bir yapay zekâ girişim vizyonudur. Odak noktamız; operasyonel ekiplerin sahada karar vermesini kolaylaştırmak, topluluklara kısa ve anlaşılır uyarılar sağlamak ve veriyi asla kişisel mahremiyeti zedelemeden kullanmaktır. Afet öncesi hazırlık, olay anı koordinasyon ve toparlanma süreçlerinde; özet raporlar, önceliklendirme, lojistik yönlendirme ve güvenli iletişim akışı gibi pratik çıktılar üretiriz.
Emergency response thrives on speed and clarity. Afet.AI can unify multi‑source data—sensors, satellites, crowdsourced reports—into a single operational view. Models classify events, score severity, and surface recommended actions. Human teams review, adjust, and deploy. Post‑incident, analytics support after‑action learning so that the system improves over time.
Back to topPrediction varies by hazard: seismic forecasting remains probabilistic, while floods and wildfires benefit from hydrological and meteorological models. AI fuses historical patterns with live feeds to estimate risk windows. Transparent confidence intervals help decision makers weigh trade‑offs and avoid false certainty.
Back to topAs climate volatility rises, preparedness becomes continuous rather than seasonal. Afet.AI can maintain readiness dashboards that track drought, heat, and storm indicators across regions. Scenario planning tools let municipalities stress‑test supply chains and critical infrastructure under different climate futures.
Back to topTimely alerts save lives. AI can shorten the detection‑to‑warning pipeline by filtering noise and recognizing patterns faster than rule‑based systems. Multichannel delivery—SMS, sirens, apps, radio—ensures coverage. Localization and accessibility matter: warnings should be multilingual, concise, and actionable.
Back to topDuring relief operations, constraints shift hourly. Routing algorithms balance road closures, stock levels, and volunteer availability. Afet.AI can document case studies that show measurable gains in delivery time, cost, and equity of aid distribution. Transparency builds trust and encourages adoption.
Back to topIn high‑stakes contexts, false positives and negatives have human consequences. Afet.AI can publish an ethics charter: human‑in‑the‑loop decisions, rigorous validation, data minimization, and clear accountability. Community feedback loops and public audits reinforce legitimacy and reduce harm.
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We typically respond within 24–48 hours on business days.
Email: aydin_aslan88@gmx.deFuse satellite imagery, sensor data, and field reports into a single picture responders can use.
In the first hours after a disaster, the goal is to turn noise into a map of action. Combine public satellite snapshots with road sensors and radio logs. Ask AI to flag blocked routes, likely shelter areas, and damaged utilities with confidence levels. Keep outputs short: a list of hotspots, a suggested convoy route, and a five‑line summary that can be read on a phone. Human validation remains essential—AI should propose, not decide.
Move water, food, medicine, and teams using live constraints and simple rules.
Routing is about priorities and feasibility. Use AI to ingest warehouse stock, fuel availability, road status, and weather updates. Request three candidate routes per delivery with a clear rationale: fastest arrival, highest coverage, and safest path. Include fallback plans if conditions change. A small gain per trip compounds into massive impact across a week of operations.
Short, multilingual messages that help people act safely.
Effective alerts are specific, local, and calm. Ask AI to generate messages with one actionable instruction, a short explanation, and a verifiable reference (siren, radio frequency, shelter address). Provide versions in the two most common languages in your area, but keep technical terms consistent. Always end with where to get the next update and when. Trust grows when information is predictable and useful.
Onboard, brief, and deploy volunteers without creating chaos.
Volunteers arrive with energy but variable experience. Use AI to create role cards—logistics, first aid support, distribution—each with a 60‑second briefing, safety rules, and escalation contacts. Generate a rolling roster that matches people to tasks based on availability and skills. Publish changes in one channel and keep sign‑off simple. Clear structure turns goodwill into real capacity.
Structured debriefs that turn lessons into next‑time advantages.
A good review captures facts, feelings, and fixes. Collect snapshots from teams within 24 hours: what worked, what failed, and what to change. Ask AI to synthesize patterns and propose three process changes that would have reduced friction. Then assign owners and dates. Without ownership, lessons vanish—documented changes are how resilience grows.