This paper describes the psychological state of human from different ages, genders, and professions with the impact of COVID – 19 in their regular life in Bangladesh with simulated and visualized infographic images containing statistical analysis from a collected survey on real regular life which is based on their activities of regular life and internet uses. Literature has been reviewed with various COVID – 19 based psychological work and our work on psychological state, anxiety reasons, and depression scale analysis. Secondly, a process of analysis and statistical format has been described through a specific methodology diagram, which contains the collected dataset's overall data analysis process. Thirdly, a complete analysis report is given by the dataset analysis, including every specific data collected. Fourthly, a discussion based on analysis and statistical analysis with informative tables is described individually for different aspects. Finally, some unavoidable limitations are initialized with reasons though every dataset collected from real regular life and internet use impacts COVID – 19 in Bangladesh.

This paper describes different aspects of COVID-19 in Bangladesh and other countries with visualization and infographic images containing the virus's spreading, other information from the statistical format, and some case studies based on various important fields for a country educational, economic, etc. Firstly, literature review section this paper on COVID-19 related works and its type with previous virus transmission reports and its effect. Secondly, completing work describes through algorithms and methodology diagram, which contains the overall data analytics process, including data wrangling. In this phase, the total working procedure to complete further process. Thirdly, a complete situation report analysis on Bangladesh by infographics through dataset containing every perspective of COVID-19 in Bangladesh. Comparative analysis with other top infected countries visualizes through the Data Visualization process and statistical analytics and case studies based on various impacts of lockdown on Bangladesh. Finally, a discussion presents the statistical summarization of COVID-19 in Bangladesh.

This work deals with some plant disease detection like Potato, Pepper, and Tomato, Rice, etc. based on CNN image processing Technology. An enormous improvement has been made in the field of picture preparation and AI and its application in different parts of designing. The authors have entered the time of digitization. The authors have caught pictures with the assistance of an advanced camera. All the clearer the pictures are better and produce the outcomes. In this report, the authors have done the arrangement of sickness-free, somewhat infected, and sick leaves. The information related to plant features is especially useful for its applications in plant growth modeling, agricultural research, and on-farm production. Traditional direct measurement methods are generally simple and reliable, but they are time-consuming, laborious, and cumbersome. In contrast, the proposed vision-based methods are efficient in detecting and observing the exterior disease features. In the present investigation, CNN image processing algorithms are developed to detect disease by identifying the color feature of the defected area. Subsequently, the rotted area was segmented from an image, and the area of the rotted leaf portion was deduced from the Pepper and tomato plant feature data. The results showed a promising performance of this automatic vision-based system it is found 94% accuracy average in practice with easy validation in a large amount of data.