ABSTRACT
This paper focuses on data visualization techniques and its efficiency. Data visualization refers to pictorial representation of data. Though it is easy to view and understand, the time is yet to come when this technique would see its full utilization. It has a lot of applications in data presentation as well as data exploration, pattern mining and predictive analysis. Its applications would be studied in relation to Covid-19 pandemic. The world is suffering from novel corona virus since December 2019. It has been more than two years and there seems no end to this pandemic. Data visualization techniques will be applied using R programming language, it has been widely adopted by statisticians to study and analyse data, so it will be used here as a tool to study data generated by corona virus outbreak in the last two years. However, the scope of the study is limited to data generated in India for number of confirmed cases, deaths and recovered cases. © 2022 IEEE.
ABSTRACT
This research paper gives a brief idea of controlling entrance gates of different areas like metro stations, railway stations, airports, corporate offices, restaurants, hotels and home with the face mask detection technology. In this, the camera will capture the real time video of a person using Artificial Intelligence[15],whosoever is entering the gate, processes the video and detects if the concerned person is wearing the mask properly or not. If the person is wearing a mask then the gate will open, if not then the gate will remain closed until the mask has been worn properly. The main motivation for this project comes from the current situation in the world where Covid-19 is spreading at a pace which is being difficult to control. This upcoming technology prototype can fuel in new ideas into different projects which are already ongoing to battle the pandemic. Also, the scope of this technology is not just limited to the face mask detection and has a wider and a more complex use-case in the real world. © 2022 IEEE.
ABSTRACT
In the present study, a total of 48 groundwater samples (13 from shallow aquifers depth < 50 m and 35 samples from deep aquifers in the depth range 50-200 m) were collected from three industrial dominant districts (Ludhiana, Jalandhar and Moga) of Punjab after the lockdown period and before the start of southwest monsoon in the month of June, 2020 (pre-monsoon). The values for total dissolved solids (TDS) observed in Monsoon season (August, 2020) and November-December, 2019 (post-monsoon) were compared with the values taken in June, 2020 (pre-monsoon) to see the impact of lockdown due to COVID-19 pandemic on groundwater salinity. ~ 60% of samples were found to have TDS values more than acceptable limit (500 mg/l) before lockdown (post-monsoon season of 2019) period and after or during lockdown period (June, 2020) number of samples more than the acceptable limit (500 mg/l) reduced to 45%. Average TDS values reduced by 25% in shallow aquifers after lockdown and area under TDS values in acceptable limit (500 mg/l) increased by 23% of samples as compared to the TDS values found in monsoon season of year 2019. In deeper aquifers, increase of only 3% area under TDS values in acceptable limit of 500 mg/l was found. Reductions in TDS values in shallow aquifers clearly show that there is an urgent need for proper management of salinity causing elements and regulating these to check groundwater contaminations using the holistic and hydro-geoethical approach.