Novel consignment monitoring system for equipment management operation of cold chain atmosphere using cognitive radio comparing with IOT

Using Cognitive Radio as a benchmark, we will design and implement a cutting-edge consignment monitoring system for cold chain atmosphere equipment management operations. The Components and Procedures: The dataset is brought in, and algorithms for Cognitive Radio and the Internet of Things are trained and evaluated in the shared environment. Two algorithms divide into two classes. The sample size for each group is 80 participants, and the corresponding power is 80%. The end result was that various input sample sizes yielded varying degrees of accuracy. The results of this investigation show that, compared to the IoT algorithm, Cognitive Radio is superior. Our research shows that the accuracy of IOT (83.76%) is lower than that of Cognitive Radio (91.69%) by a statistically significant margin (p 0.01). (0.05, 2-tailed). Using an independent sample T-Test, we determined the average, standard deviation, and standard error. Average statistical significance between groups. This study concludes that an unique consignment monitoring system based on Cognitive Radio is more accurate than IoT based on the data collected.