为满足交通运输行政执法管理部门对行政执法与监督规范化、智能化、信息化的要求，迫 切需要解决执法全过程监督管理缺少信息依据与监管手段等突出问题。基于大数据思想，依托信息化手段，利用Hadoop 技术和贝叶斯算法计算执法风险事件的概率，通过执法的自动化监督、预警与管理等，汇聚执法全过程信息编制执法“数据铁笼”，针对监督内容建立了风险点预测模型与自动预警方案，改变了传统的监督模式，将执法监督大数据应用与数据铁笼思想理念深入渗透至执法应用的每个关键环节。在执法流程、执法人员、执法装备等多个层面，以数据系统 提供的数据作为支撑，实现“非法定行为不可为”，约束行政权力，规范执法行为，限制装备的不合理使用，彻底将权力关进数据编制的“数据铁笼”内，实现全方位、全流程、实时化的动态监管。

In order to satisfy the demand of transportation administration for standardization, intelligence and informatization of administrative enforcement of law and supervision, there is an urgent need to solve such outstanding problems as the lack of information basis and supervision means in the entire process of supervision and administration of law enforcement. Based on the idea of big data and informatization means , the Hadoop technology and Bayesian algorithm were used to calculate the probability of law enforcement risk events. The data cage of law enforcement gathering the information during the whole process of law enforcement was compiled based on the automatic supervision, early warning and management of law enforcement. In view of the contents of the supervision, a risk point prediction model and an automatic early-warning plan have been established. The traditional supervision mode has been changed, the application of law enforcement supervision data and data cage idea have penetrated into every key link of law enforcement applications. On the law enforcement process, law enforcement officers, law enforcement equipment and other aspects, with the support of data provided by the data system, the impossibility of non-statutory acts, the constraints of administrative power, the standardize law enforcement behavior, the limit of the irrational use of equipment were achieved. Thus the power was completely put into the data cage, and the all-round, whole process, real-time dynamic supervision was achieved.