Informatics Publishing Limited

L. Saumya ¹, M. G. Jayanthi ²

Affiliations
1 Cambridge Institute of Technology, K R Puram, Bangalore, IN
2 Dept. of CSE/ISE, Cambridge Institute of Technology, K R Puram, Bangalore, IN

Abstract

Now-a-days, wireless sensor networks mainly used for emerging operations such as military/army sensing units, patient monitoring system, traffic sequence analysis as well as the movement/mobility of sensor nodes from one location to another. In this case, the key requirement of the application is security, while transferring the data between source and destination. For this case apart from the normal protocol for encryption and decryption, used effective scheme like Certificate-less Effective Key Management (CL-EKM), which provides dynamically secured communication over WSNs. The CL-EKM provides energetic key changes while the node enters into the cluster region presented into the network or leave out from the network clusters. This system assists the efficient key revocation system for negotiable nodes and reduces the effect of the node adjustment for achieving security of additional security schemes. In the security investigation of this plan demonstrates that the convention is very powerful in case of safeguarding against different attacks. Here, we execute the Certificate-less Effective Key Management scheme using Windows/Linux operating system and evaluate its time, vitality and correspondence.

Keywords

Wireless Sensor Network, CL-EKM, Key Management Protocol, Key Administration Schemes.

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Romana Tazeen ¹, H. N. Shilpa ¹, P. Usha ¹, M. G. Jayanthi ¹, D. R. Shashikumar ¹

Affiliations
1 Dept. of CSE, Cambridge Institute of Technology, Bangalore, IN

Abstract

The paper focuses on providing the information regarding the pesticide and the amount of pesticide to be used for an unhealthy crop. The user who is the farmer clicks a picture of the crop and uploads it to the server via the android application. After uploading the image, the farmer gets a unique ID displayed on his application screen. The uploaded image is then processed using image processing techniques, the features are extracted based on clustering and SVM Classification is applied, accordingly the disease is detected. The disease and the corresponding pesticide and other information about it are updated into server. The farmer using this unique ID can retrieve the complete information about the Disease name, affected area, pesticide name and its optimal amount to be used.

Keywords

Image Processing, Feature Extraction, Clustering, SVM Classification.

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