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Reward Mechanism

Rewarding the members of our network for sharing their local weather data is a crucial part of our system (currently on testnet).

Our Reward Distribution Mechanism is a unique, fair and transparent algorithm that will handle how rewards are being distributed to the network members.

Reward Distribution Mechanism​

We are currently on the first iteration of that algorithm, which has been implemented in a basic way: only taking into account whether or not a station is connected to the network.

The reward distribution mechanism has two parts:

  • The reward algorithm which calculates the actual_reward for each weather station by evaluating its weather data for the previous day
  • The daily reward distribution of rewards to the station owners
Important

Connecting a wallet is mandatory to receive rewards. If a user has not connected a wallet, the rewards will be lost.

How Often does the Reward Algorithm run?​

The algorithm runs every day to reward weather stations that were actively sending data to the network for the previous day.

Calculation of the Reward Score​

reward_score = array_of_hourly_weather_data / 24

Explanation​

In the calculation of the reward_score step, the algorithm takes into account the weather data for each hour of the previous day for any given weather station.

  • If the weather station has successfully sent data for each hour of the previous day, then the algorithm's input is an array of 24 objects, with each object being the station's weather data.
  • If the weather station hasn't sent any weather data for 1 or more hours the previous day, then the algorithm's input is an array of (24 - X) objects, with each object being the station's weather data and X being the number of hours that the station hasn't communicated with our system.

That input is then being used by dividing its length by 24 (the maximum hours per day) to get a reward_score of 0.0 to 1.0.

Reward distribution​

weather_station_reward = reward_score * max_daily_reward

Explanation​

After the calculation of the reward_score step, the algorithm takes the reward_score for any given weather station in our network, multiplies it with the max_daily_reward that the weather station can get, and the result is the amount of WXM tokens that the algorithm distributes to the user who owns that weather station.

note

As it is clearly stated above this is a basic first iteration. In the future, our algorithm will take into weighted consideration the following:

  • Location Coverage (density of weather stations in an area)
  • Weather Data Quality