Nowadays cloud computing is becoming a reliable source for distributing services in various sectors like health care, administrations, social insurance, etc. our paper is comparing two existing algorithms i.e. PSO and RASA. It includes parameters like energy, performance, and throughput.PSO has beendesigned in such a way that it can be easily compared with the new future developments and can be easily recognized its benefits.

In the field of agribusiness, increasing the yield is generally significant. In any case, weeds and creepy crawlies diminishes the return by harming the harvest. This can be decreased by using a few synthetic concoctions known as biocides or pesticides. Yet, they are undependable for farmers while showering. To lessen the dangers of pesticides on human health, a robot is grown to move self-governing. The robot is controlled utilizing an open-source smartphone application known as BLYNK.

The IoT and Big Data have jumped to transform into a standard-issue and keep up board-level needs. Both IoT and enormous information are persistently making features all finished, drawing a gigantic measure of examination intrigue and featuring exciting difficulties. This developing acknowledgement is because of the convergence of the two advancements with the colossal degree for business investigation and the imminent that remaining parts unexploited. Consistently, mechanical machine, wellbeing observing frameworks, sensors,

Data mining is an extraction of information revelation from enormous measure of information which is already obscure and possibly valuable for scientific preparing and dynamic. Different abbreviations of information mining are, for example, Data archaic exploration, Data digging, Information reaping and Business Intelligence. The different information mining strategies are utilized to locate the shrouded intriguing quality or new patter to store the information.

Now a day there is a huge demand of face detection for security like banking, phone lock and other devices. Due to huge demand of machine learning technique to train and test data. with the rapid development of neural network like RNN, KNN, there is new technique i.e. CNN which is widely applied for face clustering. previously there are few clustering techniques which is widely used in industry like SOM, and self-organised feature mapping neural technique and are still developing. In our research we are applying CNN for feature extraction then S-SOM for clustering face image data. we are also analysing the effect of some related parameters in SSOM on face clustering for further research.