Weather forecasting is an important role in meteorology and has long been one of the world's most systematically difficult problems. This plan deals with the structure of a weather display system that may be built by electronics hobbyists utilizing low-cost components. Severe weather occurrences present a challenging forecasting problem with just a partial explanation. Developing communication methods makes it possible. Technology-enabled applications provide severe weather alerts and advisories. The airline industry is highly sensitive to the weather. Accurate weather forecasting is crucial. The IoT enables agriculture, notably arable farming, to become data-driven, resulting in more timely and cost-effective farm production and management while lowering environmental impact. Applying AIoT and deep learning to smart agriculture combines the best of both worlds.
Payment is one of the main parts of the business. Since from the last decade, the use of mobile devices for electronic payment has increased significantly. The current generation of individual payment systems that is replaced the traditional smart cards by mobile devices supplied with
E-wallet and M-wallet functions. The spread of such E-wallet systems will depend on their security, functionality ease of use and the effectiveness of realization. E-wallet is a utility which offers users to save their money and make payments anywhere and all time. Many banks and nonbanks
organizations are contesting to develop new on this filed. As customers adopt E-wallet and M-wallet. As customers adopt E-wallet and M-wallet, they becoming a cybercrime target. E-wallet provides a monetary action through smartphones which is fruitful freedom for electronic crimes. Quality
of the system, quality of service and quality of information has to improve by the mobile wallet service providers for their M-wallet applications.
There is tremendous upturn in data repositories because of data generation by various organizations like government, cooperates, health caring in large amounts. Large amount of data is being produced, processed, collected, and analysed online. So there comes a requirement to transform this data into valuable information. This process of extracting the knowledge from large amount of data is referred as data mining. The proposed hybrid approach can be checked on different classifiers like Naïve Bayes, Random forest classifier etc. In proposed methodology we find that SMOTE algorithm which used K-nearest neighbour algorithm is limited to some minority class instances for creating synthetic samples, which sometimes leads to over fitting, so an effective oversampling approach can be developed.
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