{'fraction_non_alphanumeric': 0.009746588693957114, 'fraction_numerical': 0.0, 'mean_word_length': 5.113095238095238, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Financial Risk Avoidance Based on the Sensor Network and Edge Computing

In order to improve the effect of financial risk aversion, this paper studies the financial risk aversion system combined with the edge computing method of the sensor network and proposes a sensor data anomaly detection algorithm based on the offset distance. Moreover, this paper divides the sensor data into several sliding windows according to the time series, analyzes the offset between the data object and other data in the sliding window by calculating the offset distance, and uses the abnormal level to indicate the possibility of data abnormality. In addition, this paper analyzes the single-layer linear network model for the data with high abnormal level and constructs a financial risk aversion model based on the edge computing of the sensor network. The simulation test results show that the financial risk aversion model based on sensor network and edge computing proposed in this paper meets the actual needs of financial risk analysis.