Rapid industrialization and urbanization has led to decrease in agricultural land and productivity worldwide. This is combined with increasing demand of chemical free organic vegetables by the educated urban households, and thus, greenhouses are quickly catching trend for their specialized advantages especially in extreme weather countries. They provide an ideal environment for longer and efficient growing seasons and ensure profitable harvests. The present paper designs and demonstrates a comprehensive IoT based Smart Greenhouse system that implements a novel combination of monitoring, alerting, cloud storage, automation and disease prediction, viz. a readily deployable complete package. It continuously keeps track of ambient conditions like temperature, humidity and soil moisture conditions to ensure a higher yield of crop and immediate redressal in case of abnormal conditions. It also has a built-in automatic irrigation management system. Finally, it employs the most efficient deep learning model for disease identification with leaf images. Furthermore, with memory and storage optimization through cloud storage, an individual living in the city can also build a greenhouse and can monitor it from his home and take redressal methods as and when desired.

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Over 98% of cervical cancers (CC) are caused by regular infections with "high risk" genotype of the human papilloma virus (HPV). However, this is not always the causative factor. Therefore, production of HPV vaccinations represents a significant chance to minimize the risk of CC. Phase III studies for a number of preventative HPV vaccines based on L1-virus-like particle (VLPs) have just been completed and the preliminary results are very convincing. However, there are a lot of practical concerns that need to be resolved before the use of these vaccinations. These vaccines were challenged with obvious queries such as protection time, subject receiving vaccines, time of vaccination, and how to include them into ongoing screening programs. Although these vaccines were 90% effective at preventing HPV infection as these offered only modest advantages for the removal of pre-existing infections. New advancements in the creation of therapeutic vaccinations have been explored for further improvement and post-vaccination surveillance. Therapeutic vaccines attempted to boost cell-mediated immunities and these are detrimental to the infected cell as opposed to neutralizing antibodies (different from prophylactic vaccines).

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Air Pollution is a harsh reality of today's times. With rapid industrialization and urbanization, the polluting gases emitted by the burning of fossil fuels in industries, factories and vehicles, cities around the world have become "gas chambers". Unfortunately, New Delhi too happens to be among the most polluted cities in the world. The present paper designs and demonstrates an IoT(Internet of Things) based smart air pollution monitoring system that could be installed at various junctions and high traffic zones in urban metropolis and megalopolis to monitor pollution locally. It is designed in a novelistic way that not just monitors air pollution by taking varied inputs from various sensors (temperature, humidity, smoke, Carbon monoxide, gas) and but also presents it on a smart mirror. Its unique feature is the demonstration of a smog prediction model by determining PM10 (Particulate Matter 10) concentration using the most efficient machine learning model after an extensive comparison by taking into account environmental conditions. This data generated can also be sent as a feedback to the traffic department to avoid incessant rush and to maintain uniform flow of traffic and also to environmental agencies to keep pollution levels under check.