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Emerging projects like API3 adopt the Airnode direct connection architecture, increasing the number of data sources from an average of 7 to 83. At the same time, they introduce a Dynamic Data Verification (DDV) mechanism, an outlier probability elimination algorithm, and data provider staking proof. Real-world testing shows that when the ETH price fluctuates abnormally by 5% on BitMEX, traditional oracles take an average of 12 seconds to respond, while the new system can identify and isolate abnormal data points within 0.8 seconds.0Emerging projects like API3 adopt the Airnode direct connection architecture, increasing the number of data sources from an average of 7 to 83. At the same time, they introduce a Dynamic Data Verification (DDV) mechanism, an outlier probability elimination algorithm, and data provider staking proof. Real-world testing shows that when the ETH price fluctuates abnormally by 5% on BitMEX, traditional oracles take an average of 12 seconds to respond, while the new system can identify and isolate abnormal data points within 0.8 seconds.1Emerging projects like API3 adopt the Airnode direct connection architecture, increasing the number of data sources from an average of 7 to 83. At the same time, they introduce a Dynamic Data Verification (DDV) mechanism, an outlier probability elimination algorithm, and data provider staking proof. Real-world testing shows that when the ETH price fluctuates abnormally by 5% on BitMEX, traditional oracles take an average of 12 seconds to respond, while the new system can identify and isolate abnormal data points within 0.8 seconds.2Emerging projects like API3 adopt the Airnode direct connection architecture, increasing the number of data sources from an average of 7 to 83. At the same time, they introduce a Dynamic Data Verification (DDV) mechanism, an outlier probability elimination algorithm, and data provider staking proof. Real-world testing shows that when the ETH price fluctuates abnormally by 5% on BitMEX, traditional oracles take an average of 12 seconds to respond, while the new system can identify and isolate abnormal data points within 0.8 seconds.