The deadliest animal in the world is a mosquito. It might seem impossible that something so minuscule can kill so many people, but it's true. 700 million people suffer from vector-borne diseases and there are 1 million deaths each year all around the world. Research in this field has been limited due to the fewer number of epidemiologists, virologists, and bioinformatics available in our country.

So the problems in the current healthcare system are

• Outdated Mosquito surveillance programs
• Insufficient area wise data available for research analysis
• Non-existing collaboration between the data science community and the government bodies
• No medium to spread awareness

Taking into consideration the above problems we have intended to build NOsquito. It is an integrated management system that will include better surveillance techniques, source reduction, biological control, real-time analytics as well as public education. NOsquito will rest on pillars of modern technology such as AI, Data Analytics, and IoT.

In our surveillance program, there will be two trapping methods

1. CO2 baited Honey traps: So here we are using Co2 honey baited FTA filter paper. The idea is to take advantage of the fact that infectious mosquitoes spit out viruses in their saliva not only during bloodsucking but also during sugar feeding. The traps will then be sent to labs to collect data after field use. These traps approximately cost half a dollar and can be reused. The traps are yet not used in India.

2. IoT-based traps: These traps will be especially be used in mosquito breeding habitats and high risks areas. IoT-based traps will generate data points such as species image, sound frequency, time interval, etc. The trap will be designed with the help of Arduino and also will have accessories like a microphone, camera, and capacitor.

3. Dashboard: With the help of data gathered from the traps different visualization will be shown to the health care authorities so that well-informed decisions can be taken. Graphs such as population density of mosquito species, a map view, percentage of diseases in particular areas will be displayed. Studies have proven that trap height for catching particular mosquito species changes based on environmental factors, the ratio of green space, density of housing, etc. Mosquito species are also developing resistance to a dwindling number of chemical insecticides. For this purpose ML models will be designed to get the exact trap height and effective chemicals based on the area.

Volunteers and community groups present in different locations can always participate in the mission of eradicating vector-borne diseases by setting traps and researching historical data.

Eradicating Vector-Borne Diseases The impact of new vector-borne diseases can be minimized based on historical data Gathering and analyzing data for better health-related decision making Acting as a bridge between data science and the research community. Increasing the number of volunteers

The application shows how modern technology can help in eliminating the harmful mosquito species. Predicting mosquito eliminating chemicals, trap heights and different such issues should be solved by taking in to considerations various factors. NOsquito has the potential to help local health authorities in better decision making.

We aim to eradicate mosquitoes-borne diseases, but our aim in the near future is to gather and work on as much data as possible for better health-related decision-making. As W Edwards has rightly said, “Without data, you're just another person with an opinion”.