Internet of things is an emerging information-aware technology that combines computer vision and artificial intelligence technology to ensure the safety of personnel and facilities in tourist attractions by discovering real-time alarms of abnormal conditions in the monitoring of tourist attractions. Therefore, this paper proposes an automatic image algorithm for tourism scene anomaly based on Internet of things. The algorithm uses the Internet of things intelligent camera in the image acquisition preprocessing platform to collect the tourist scenic spot image. Based on the traditional image segmentation technology, according to the neighborhood-related characteristics of the Markov random field, the dynamic characteristics of continuous frames are added. Reconstruct the Gibbs energy function. The location of the abnormal situation is determined by coding, and a treatment opinion is given. The experimental results show that the proposed algorithm not only considers the spatial information of each pixel and neighboring points, but also adds the time information of successive frames, accumulates the energy values of all the pixels in the whole image and analyzes the data with the energy curve. It can accurately and efficiently identify the abnormal situation images of tourist attractions.

物联网是一种新兴的信息感知技术，结合了计算机视觉和人工智能技术，可通过在监视旅游景点过程中发现异常状况的实时警报来确保旅游景点人员和设施的安全。因此，本文提出了一种基于物联网的旅游场景异常自动图像算法。该算法在图像采集预处理平台中使用物联网智能相机采集旅游景点图像。在传统图像分割技术的基础上，根据马尔可夫随机场的邻域相关特性，增加了连续帧的动态特性。重建吉布斯能量函数。通过编码确定异常情况的位置，并给出治疗意见。实验结果表明，该算法不仅考虑了每个像素及其相邻点的空间信息，而且还添加了连续帧的时间信息，累加了整个图像中所有像素的能量值，并利用能量对数据进行了分析。曲线。它可以准确有效地识别旅游景点的异常情况图像。