Risk Assessment and Early Warning Model for Water Conservancy Projects Based on IoT and Big Data

The conventional risk assessment methods for water conservancy projects mainly rely on calculating project risk values to achieve risk assessment. However, there is usually a lack of consistency testing of risk values, resulting in poor assessment. Therefore, a water conservancy project risk assessment and warning model based on the Internet of Things and big data is proposed. Analyze project risk characteristics, extract key influencing factors, and construct a risk assessment system. Calculate the weight values of evaluation indicators through the judgment matrix and test their consistency. By using the KNN algorithm, the risk assessment level is combined with the risk assessment level to achieve the evaluation and early warning of engineering projects. The experimental results show that when this method is used for engineering project risk assessment, the error between the evaluation score and the expert score is small, and the average value of the evaluation error is below 0.5, ensuring the accuracy of the assessment.