Innovations in the Internet of Things (IoT) technology have revolutionized several industrial domains for smart decision-modeling. The capacity to perceive data about ubiquitous instances has resulted in numerous innovations in sensitive sectors like national security, and police departments. In this paper, an extensive IoT-based framework is introduced for assessing the integrity of police personnel based on his/her performance. The work introduced in this research is centered around analyzing several activities of police personnel to assess his/her integral behavior. In particular, the Probabilistic Measure of Integrity (PMI) is formalized based on professional data analysis for classification based on Bayesian Model. Moreover, the 2-player game model has been presented to assess the performance of police personnel for efficient decision-making. For validation purposes, the presented framework is deployed over challenging datasets acquired from the online repository of UCI. Based on the comparative analysis with the state-of-the-art decision-making models, the presented approach has registered enhanced performance in terms of Temporal Delay, Classification, Prediction, Reliability, and Stability.

物联网（IoT）技术的创新彻底改变了智能决策模型的几个工业领域。能够感知有关无处不在实例的数据的能力已导致在国家安全和警察部门等敏感部门进行了许多创新。在本文中，引入了一个广泛的基于物联网的框架，用于基于警察/警察的绩效评估其完整性。本研究中介绍的工作集中在分析警察人员的几种活动以评估其整体行为上。尤其是，基于贝叶斯模型的专业数据分析对基于概率的完整性度量（PMI）进行了形式化。此外，已经提出了2人游戏模型来评估警察人员的表现，以便进行有效的决策。为了进行验证，将提出的框架部署在从UCI在线存储库获取的具有挑战性的数据集上。在与最新决策模型进行比较分析的基础上，本文提出的方法在时间延迟，分类，预测，可靠性和稳定性方面均表现出增强的性能。