MeteoHawk provides on‑demand atmospheric data by operating autonomous UAVs equipped with calibrated weather sensors. Users define regions and sampling intervals through a cloud‑based mission planner and receive sub‑second, GIS‑compatible data streams via APIs for integration into forecasting, precision agriculture, or research workflows.
Funding
Funding not disclosed
Founders
Product
Problem
Many organizations rely on sparse, expensive ground‑based weather stations to monitor atmospheric conditions, which limits spatial resolution and delays access to real‑time data needed for precision agriculture, forecasting, and climate research. Deploying and maintaining dense sensor networks incurs high capital and operational costs, especially in remote or hard‑to‑reach areas.
Solution
MeteoHawk operates a fleet of autonomous UAVs equipped with calibrated meteorological sensor packages to collect high‑frequency atmospheric observations on demand. Flight routes are programmed via a cloud‑based mission planner that optimizes coverage based on user‑defined regions and sampling intervals. Sensors capture temperature, humidity, pressure, wind speed, and particulate matter, while onboard edge processors perform quality control and compress data for low‑latency transmission to a secure cloud repository. Clients access the data through RESTful APIs or GIS‑compatible feeds, enabling integration with existing forecasting models and decision‑support tools. The service is offered on a subscription or per‑flight basis, allowing users to scale observations without investing in permanent infrastructure.
Target Audience
Primary customers are national weather services, commercial agribusinesses, and academic or private research institutions that require high‑resolution, near‑real‑time atmospheric data across large or remote territories.
Features
- Fully autonomous quadcopter platform with redundant GPS/RTK navigation for sub‑meter flight accuracy
- Integrated meteorological sensor suite (thermistor, hygrometer, barometer, ultrasonic anemometer, PM2.5/10) calibrated to WMO standards
- Edge‑computing module that performs real‑time outlier detection, sensor fusion, and data compression before uplink
- Cloud‑native telemetry pipeline delivering data streams at <1 second latency via MQTT and HTTPS endpoints
- Mission‑planning dashboard with GIS overlay, allowing custom flight paths, altitude profiles, and temporal sampling rules
- API library (Python, JavaScript) and OGC‑compliant WFS/WMS services for seamless ingestion into forecasting and GIS platforms
- Built‑in compliance with aviation regulations (BVLOS, geofencing, automatic return‑to‑home) and automatic log generation for audit trails
- Pay‑as‑you‑go pricing model with volume‑based discounts and enterprise SLA options