Agent technology is one of the widely adapted technologies for developing applications that deliver e-Services. Ensuring confidentiality of the patients’ data in e-health care systems remains a serious challenge. Many large enterprises provide in-house health care services free of cost for their employees and their dependents as a competitive benefit to prevent employees turnover and also to maintain healthy and productive human resource. This paper proposes enhancements to the traditional health care system of an organization so that it provides better services with respect to users’ satisfaction. The requirements identification of the system proposed and the evaluation of the new system are done using a feedback model. The new system proved to be mutually beneficial to employees and employers in terms of saving time and cost and thus it enhances productivity.

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A crucial component of precision agriculture is the capability to assess the fertility of soil by looking at the precise distribution and composition of its different constituents. This study aims to investigate how different machine learning models may be used to assess soil fertility using hyperspectral pictures. The development of images using a random mixing of different soil components is the first phase, and the hyper spectral bands utilized to create the images are not used again during the analysis procedure. The resulting end members are then acquired by applying the NFINDR algorithm to the process of spectral unmixing this image. The comparison between these end members and the band values of the known elements is then quantified., i.e. it is represented as a graph of band values obtained through spectral unmixing. Finally we quantify the similarities between both graphs and proceed towards the classification of the hyper spectral image as fertile or infertile. In order to classify the hyper spectral image as fertile or infertile, we quantify the similarities between the two graphs. Clustering and picture segmentation algorithms have been devised to help with this process, and a comparison is then made to show which techniques are the most effective.

Cloud Computing Environment, the data presides over a set of networked resources and these data centers may be located in any part of the world and access of the data provided through Internet. Cloud computing facilitates computing assets on demand by the use of a service provider. In the Current Scenario, Security and privacy challenges are facing in this cloud environment. We implement our scheme and show that it is both efficient and flexible in dealing with access control for outsourced data in cloud computing with comprehensive experiments using the technique Hierarchical Attribute Based Encryption to protect data of the users and analyze its performance.

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