In this paper evolution of IoT along with its intimacy with cloud is described.

Image processing and capturing has become a crucial part of intelligent robotics. It is mainly used to detect an object in real-time. To control traffic on the roads, there is a need for well-informed traffic management system. License plate spying can be used in wide domains such as for detecting speeding vehicles, traffic rule enforcement, security control and collect toll electronically. License plate detection can be performed via various approaches such as vector quantization, Gabor transform, optical character recognition, neural networks etc. Character recognition in license plate is an inevitable factor of Real Time vehicle Tracking (RTVT) system. Lot of research has been carried out to find the characters in the vehicle license plate. In [2], the character recognition is done by extracting the plate region of the license plate by using edge detection algorithms and smearing algorithms. Then image segmentation is done by using smearing algorithms, filtering techniques and some morphological algorithms are also used. Lastly, statistical approach is used to identify the characters in the license plate using template matching. This project will focus on implementing an algorithm in [4], which uses hue, saturation, intensity (HSI) color model to determine the threshold statistically for detecting the candidate regions. Irrespective of the color of the license plate, the candidate regions shall include license plate regions and the geometrical properties are used for classification of the license plates. Predetermined license plate alphanumeric characters shall be used to decompose the candidate regions by using 2-D cross correlation and detect the license plate. The effectiveness of the algorithm will be studied followed by conclusions.