IoTeX is the blockchain platform for Real-World AI. Since 2017, its foundational infrastructure has delivered verified, real-time data from the real world to AI systems and decentralized applications. Powering 100+ projects and 40M devices across mobility, robotics, energy, health, and more, IoTeX enables developers to build next-gen AI models and applications that deliver real-world impact. The IoTeX tech stack provides the data, identity, and verification layers to fulfill the surging demand for real-world data in the new AI era. Trusted by partners like Google, Samsung, IEEE, ARM, and Nordic Semiconductor, IoTeX is uniquely positioned to capture the multi-trillion-dollar AI and data economy.

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# IoTeX Average transaction fee Methodology

## 1. Overview

The IoTeX average transaction fee metric calculates the mean cost per transaction on the IoTeX blockchain, measured in USD. This metric provides insight into the economic efficiency and usage patterns of the IoTeX network by dividing total daily transaction fees by the total number of transactions executed each day. The calculation accounts for IoTeX's EIP-1559 implementation and includes both regular gas fees and blob gas fees where applicable.

## 2. Data sources

- **IoTeX blockchain transaction records**: Raw transaction data from the IoTeX blockchain including transaction hashes, gas usage, gas prices, sender and receiver addresses, block timestamps, and block numbers
- **End-of-day price feeds**: Daily USD price data for the native IOTX token used for currency conversion
- **Token metadata**: IoTeX native token specifications including decimal places and token identification for proper price conversion

## 3. Step-by-step calculation

### Component A: Transaction fact extraction
- **Purpose**: Extract and standardize raw IoTeX transaction data with proper gas price handling
- **Logic**: Raw transactions are pulled from IoTeX blockchain records and processed to handle the network's EIP-1559 implementation. For transactions before the Vanuatu fork (block 33730921), the original `gas_price` field is used. For transactions after the fork, the `receipt_effective_gas_price` is used instead. Gas prices are converted from wei to IOTX by dividing by 10^18. The process also extracts `receipt_gas_used`, `receipt_blob_gas_used`, and `receipt_blob_gas_price` for comprehensive fee calculation. Transaction addresses are normalized to lowercase for consistency.
- **Key fields**: `transaction_hash` for unique identification, `gas_used` and `effective_gas_price` for fee calculation, `blob_gas_used` and `blob_gas_price` for additional fees, `block_timestamp` for daily aggregation, `from_address` and `to_address` for transaction flow analysis

### Component B: Individual transaction fee calculation
- **Purpose**: Calculate the total fee paid for each individual transaction
- **Logic**: For each transaction, the total fee is calculated as the sum of regular gas fees and blob gas fees. Regular gas fees are computed by multiplying `gas_used` by `effective_gas_price`. Blob gas fees are calculated by multiplying `blob_gas_used` by `blob_gas_price`, with null blob gas costs treated as zero. This produces the complete fee amount in IOTX tokens for each transaction.
- **Key fields**: `fee_amount` representing the total transaction cost in native IOTX tokens

### Component C: Daily fee aggregation and USD conversion
- **Purpose**: Sum all transaction fees by day and convert to USD
- **Logic**: Transaction fees are grouped by day using timestamp truncation and summed to get total daily fees in IOTX. The native IOTX amounts are then converted to USD using end-of-day price feeds through a standardized conversion process. This produces daily total fees in USD across the entire IoTeX network.
- **Key fields**: `timestamp` truncated to day granularity, `fees` representing total daily fees in USD

### Component D: Daily transaction count
- **Purpose**: Count the total number of unique transactions per day
- **Logic**: Raw transactions are grouped by day and destination address, then unique transaction hashes are counted using distinct aggregation. This counting approach ensures each transaction is counted exactly once while maintaining grouping by recipient address for detailed analysis. The results are then aggregated to produce total daily transaction counts.
- **Key fields**: `transaction_count` representing the number of unique transactions per day, `to_address` for grouping analysis

### Final aggregation
- **Combining components**: Daily fee totals in USD are joined with daily transaction counts using the timestamp as the common key, ensuring both metrics represent the same time periods
- **Currency conversion**: Fees are converted from native IOTX to USD using end-of-day price feeds, with no decimal correction needed as the conversion macro handles the native token specifications
- **Time aggregation**: Both fees and transaction counts use daily boundaries created by truncating timestamps to day level, ensuring consistent time alignment
- **Final calculation**: Average transaction fee is computed by dividing total daily fees in USD by total daily transaction count using safe division to handle days with zero transactions. Days with missing data are filled with zeros to maintain complete time series continuity.

*This methodology was automatically generated by Token Terminal's methodology analyzer.*

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