A Case Study on Design of Covid-19 Detection and Alerting System Using Machine Learning Techniques

Coronavirus or 2019-nCoV is not, at this point, pandemic but instead endemic, with in excess of 14 million complete cases all throughout the planet getting the infection. At present, there is no particular treatment or solution for Coronavirus, and hence living with the sickness and its manifestations is unavoidable. The connection coefficient examination between different needy and free highlights was done to decide a strength connection between every reliant element and autonomous component of the dataset before building up the models. The database is divided into two parts, 80% of the database is used for model training and the remaining 20% is used for model testing and evaluation. In 2019, early Coronavirus predictions is useful to reduce colossal weight on medical service panels through the diagnosis of coronavirus patients. In the proposed work in this paper, Naive Bayes, Decision tree, Support Vector Machine (SVM) and Artificial neural network (ANN) models are used for forecasting COVID-19 prediction and occurrences.

Assessment of farm constraints and income losses during COVID-19 lockdown in India

A telephonic survey was conducted during May 2020 among 675 farmers across 28 districts of 11 states of India to assess farm constraints and income losses of lockdown 1.0 and 2.0. The results indicate that labour availability and input accessibility were hurdles, but manageable to some extent. However, marketing constraints inflicted 48 and 19% losses in total expected income of perishable and non-perishable commodities and average loss per farm household was 0.93 lakh (28%). Although, income support was given through PM-KISAN, it was not adequate to compensate losses. Therefore, farm income support needs to be enhanced to cope with lockdown losses.