In order to accurately monitor the status of abnormal nodes in massive IoT data and improve the security of wireless networks, a method for monitoring the status of abnormal nodes in IoT using laser infrared technology is proposed. The laser infrared positioning method based on angle measurement is used to determine the approximate range area of abnormal nodes of the Internet of Things. This area is used as the collection area to carry out abnormal node feature data collection and dimension reduction. The collected abnormal node data is denoised through singular value decomposition, and the abnormal status of nodes is judged by combining random matrix theory and average spectral radius, so as to realize the monitoring of abnormal node status of the Internet of Things. The experimental results show that the proposed method has a maximum positioning error value of only 4.3%, a monitoring time of less than 79.85ms, and a packet loss rate of less than 0.22%, indicating good monitoring capability.