Smart farming is a vital notion for the development of agriculture and food processing industries globally. Industrial revolution in computing and digital network turned agriculture industry to a digitalized and automated technology. Manual and mechanical tools are replaced by tools that are controlled by mobile phones, drones and Web-based applications. IoT is the major applicant in smart farming that controls sensors in devices and data analysis by remote servers. Security is deployed as builtin mechanisms in the devices or as software tools implemented in the mobile devices, sensor systems and machines that are remotely controlled. Protocol-based security is provided to data that are collected from the fields and to the data that are transmitted to remote servers for processing. However, in recent years vulnerabilities in smart farming applications are demoralized which ensued smart farming systems being victimized to cyber-attacks. This research work provides insight analysis on several security threats that are being subjugating smart farming devices and processes. This paper will provide intrigue on vulnerabilities existing in smart farming systems and the threats that exploit them. IntroductıonSmart farming encompasses automation in agriculture and food processing systems. As information technology has stimulated to the radical revolution in industrial development, there is a tremendous advancement in the agriculture, manufacturing of tools used in forms, food production and preservation industries. The swift in increasing population, unpredicted climatic conditions, decline in availability of natural resources and restraints in pest control are the major hurdles in the modern
The quality of an image is always degraded by the random variation called noise which is included in the contrast, intensity and other properties like brightness. Noise is added with an image during the digital image transmission. The image sensors are always affected by the normal physical environment factors like temperature, scanner dust particles and the parametric characteristics of the lens and the camera. Noise removal is important in the image transmission because any interference in the transmission channel can include noise into it. A medicinal plant leaf needs to be disease free for a harmless medicine production. It becomes a necessity for a method to produce a more contrast enhanced image with the efficient noise removal mechanism. The paper proposes a combinational approach of an Adaptive Gamma Correction Weighting Distribution (AGCWD) which mainly serves to enhance the contrast of the image and the Noise removal mechanism which is performed by a guided filter. The proposed method evaluated various performance metrics like Mean square error (MSE), Image enhancement factor (IEF), Peak Signal to noise Ratio (PSNR) And Mean Absolute Error (MAE). The evaluation of the proposed system gave more better performance results than while using the existent Bilateral filter.
Today users sharing large volume of images through social sites inadvertently become a major problem of maintaining confidentiality. To help the users to control access to their shared content needs some tools. An Adaptive Privacy Policy Prediction (A3P) used in this paper to address the confidentiality problem.A3P system helps the user to compose confidentiality setting of their images by examine the role of social context, image content and metadata these act as a possible indicators of users privacy preferences.A3P system uses the two-level framework according to users available history on the site to determines the best available privacy policy for users images being uploaded. The solution relies on an image classification framework for image categories which may be associated with similar policies, and on an algorithm which predict the policy to automatically generate a policy for each newly uploaded image, also according to user's social features. The generated policies fallow the evolution of users' confidentiality attitude.Index Terms-Online information services, web based services.
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