The majority of research Study is moving towards cognitive computing, ubiquitous computing, internet of things (IoT) which focus on some of the real time applications like smart cities, smart agriculture, wearable smart devices. The objective of the research in this paper is to integrate the image processing strategies to the smart agriculture techniques to help the farmers to use the latest innovations of technology in order to resolve the issues of crops like infections or diseases to their crops which may be due to bugs or due to climatic conditions or may be due to soil consistency. As IoT is playing a crucial role in smart agriculture, the concept of infection recognition using object recognition the image processing strategy can help out the farmers greatly without making them to learn much about the technology and also helps them to sort out the issues with respect to crop. In this paper, an attempt of integrating kissan application with expert systems and image processing is made in order to help the farmers to have an immediate solution for the problem identified in a crop.

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The consumer services market greatly depends on the consumers feedbacks. The best provided services will be increasing the rating of those services subsequently annotated with their good feedback. To give feedback one platform is social media like twitter is very suitable one. To attain consumers interest on their services, consumer markets utilizes advertisements via search engine marketing and social media platforms. The advertisements are very attractive and mind catching, people will be informed, motivated, influenced. All advertisers give advertises in form of text, picture, and video, audio and by mixing them with the aid of professional ad-makers. The search engine is a search program for finding particular sites on World Wide Web, which discovers the stuff related to keywords or characters specified by the user. In an increasingly competitive marketplace to expand and grow the business the Search engine marketing (SEM) is the effective approach. The advertisers also select video sharing platforms like YouTube-a video sharing channel, and also the search engine marketing platform to launch their advertisements to be available for consumers publicly. The public can view and share their opinion via likes/dislikes count and also comments for every video. This paper focus on attaining stock predictions from different sources and also discuss about gathering text analysis for the required stock from digital media like search engines, video channels, news feeds. The aim of this study is to consider the stock price prediction from major E-commerce consumer services companies namely Just Dial and Info edge that are publicly traded in NSE/BSE by considering web advertising and their influence on consumer services markets like Just Dial and Info edge, by adopting ensemble machine learning algorithms like Random forest, Gradient boost, XG-boost and it is observed that XG Boost outperforms the other algorithms as it exhibits least RMSE,MAE and MAPE providing the accuracy of 71.78%.

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Online Multiclass Classification (OMC) performs the heterogeneous domain from complex data of completely diverse feature representation. OMC algorithm investigates the problem of heterogeneous domain and regression problems. Most existing studies of online learning divide the online feature selection into two parts. i) Learning with full input and ii) Learning with partial input. To address this limitation, we investigate the heterogeneous and regression problem in which an online learner is allowed to maintain a classifier with limited number of features. The key challenge of OMC algorithm is how to maintain the multiclass classification and regression using the active features. We attempt to tackle this challenge by studying on line feature selection and truncation techniques. We present OMC, Novel algorithm to solve the problems and give their performance analysis. We evaluate the performance of the proposed algorithms for on line learner using different domain and demonstrate their applications in real world problems including image classifications and analysis of bio informatics. Encouraging results validate the efficiency of our techniques.