WeatherMesh

Problem Modern weather data infrastructure is fundamentally fragile. Most systems, including national authorities like Météo-France, rely on: a limited number of static sensors centralized data pipelines little to no real-time verification This creates a critical vulnerability: A single manipulated or inaccurate data point can influence high-stakes decisions and financial markets. Recent incidents show weather data can be manipulated at the sensor level yet still treated as “ground truth.” Insight Weather data is already used in economic systems: prediction markets agriculture logistics insurance However: There is no economic layer that protects or validates the data itself. Data has value, but no built-in mechanism ensures its integrity. Solution: WeatherMesh WeatherMesh transforms weather data into a self-verifying, economically incentivized network. 1. Data Aggregation Layer WeatherMesh collects hyperlocal data from: users (manual and device-based input) IoT sensors and weather stations smart home systems and wearables moving sources such as next-generation vehicles This creates a dynamic, high-density data layer instead of relying on single-point sensors. 2. AI Validation Layer Data is validated using AI agents such as Hermes Agent: detects anomalies filters manipulation attempts assigns a confidence score This ensures that: No single input can dominate the system without consensus. 3. Economic Layer (Core Innovation) WeatherMesh introduces a real-time economic model for data usage. When a client makes an API request: the system aggregates and validates data a response is generated with a confidence score a micropayment is triggered and distributed to contributors What We Are Building WeatherMesh is not just an application. It is a real-time, self-validating weather data oracle where truth is continuously verified and economically reinforced.