A gainful fuzzy k-means clustering algorithm under Morphological Image Processing (MIP) is performed. Image processing is one of quickly developing examination territory nowadays and now it is particularly coordinated with all identified with science field. Image Processing can be utilized for breaking down various restorative and MRI Image to get the uncommon and anomaly in the image. Image segmentation manages segmentation of vein segmentation algorithm utilizing fundus Image. In this task, this segmentation is done utilizing k-means clustering and c-means clustering algorithm and Morphological operator for better execution. This upgrades the vein variations from the norm progressively and in a moderately brief time when contrasted with numerous other clustering algorithms.

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In recent days Wireless Sensor Networks and Internet of Things have become a growing and challenging research area. Those are used in various hard and sophisticated real time environments. A lot of challenges have to be faced by the researchers in these areas to meet the features like the quality level of sensed data, nodes autonomy, less energy utilization, battery storage, cluster range with cluster head selection and size of nodes…etc. In this paper, We did an extensive analysis on their recent developments in various application areas such as intelligent buildings, smart homes, Smart city developments, healthcare and smart hospital, transport and traffic management, Horticulture, water resources and quality monitoring, smart grid, space research…etc. This analysis will be helpful for the fresh researchers for doing research in WSN and IoT. The researchers have to look in identifying better solutions to the above said challenges must meet.

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