No abstract

- Villages are the back bone of our country. Agriculture is the main source of income. In our country, agriculture provides 18% of our country’s Gross Domestic Product (GDP). Our Government repeatedly highlighting the importance of innovations in the agriculture field through various schemes. Since our agriculture is largely depends on the irrigation system rather than natural rain, as an engineer it is our responsibility to atomize it with necessary optimization techniques. Our proposed work inculcates data control management, IoT, optimization and so on. Irrigation through atomized algorithm reduces time, money & water usage. In this period, this kind of atomization in each and every field utilizes all the recent technologies to implement its ideas beautifully.

The queueing paradigm is frequently applied in the manufacturing, inventory, and service industries. The effectiveness of the queuing model can be greatly enhanced by specifying the real properties of queuing. This research examines impatient client behaviors that may lead to renege in a multi-server queuing system, as well as the strategic behavior of the service provider that tries to enhance the service by adding a backup server. A very intricate multi-dimensional continuous-time Markov chain that has been successfully analysed accurately describes the system's behavior. The decision rules are used to frame the value function and the iteration algorithm is used to get the total expected cost and the optimal average cost of the entire system. By enabling the numerical results for the relevant case, the sensitivity analysis is carried out.

COVID-19 infection, caused by the virus SARS-Cov 2 is growing at a rapid rate. As an efficient cure has not been available, early detection is integral for disease cure and control. Predictive algorithms are useful in this scenario. Here, estimation is performed on patients who are likely to come in contact with COVID-19 disease, using clinical predictive models with the help of deep learning. The most informative features are extracted from chest X-ray images for COVID-19 patients and non COVID-19 patients. These images are used for COVID detection. Patients with other chronic diseases are more vulnerable to COVID-19. Hence, we put forward a Heart Disease Prediction system based on machine learning algorithms. The feature selection algorithms are utilized in the feature selection procedures for enhancing the classification accuracy and for minimizing the execution time of the classification system.

No abstract