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During this pandemic time, hospitals and patients are facing lack of shortage of medical infrastructure. Doctors are panic about patient health. So, we invented a small ventilator device. It is an easy-to-use, low-cost, highly flexible, and open-source ventilator. It can measure temperature, blood pressure, respiratory rate, etc. This kind of ventilator is beneficial in pandemic times. It can be controlled using microcontroller devices. Here we used Raspberry pi, and it is the central part of the project. Results can be maintained and monitored. Results show the data of the patient's condition, whether he is normal or abnormal. Results are shown in LCD. And the data is stored in the cloud using the webserver. When the patient's condition is uncommon, devices give an intimation. A doctor can check the condition of patients at anytime and anywhere. These devices are handy to doctors and patients at an emergency time and covid-19 times. Insufficient medical infrastructure causes painful deaths in the world. We invented our project to help the patient in emergency times at a low cost. For the sake of Patients' health, we developed this project at a low price. [ABSTRACT FROM AUTHOR]

Nowadays, the number of people affected by the various types of Eye disease keeps on increasing rapidly. The highest stage a person can get affected by an eye disease is blindness. The fact is that we cannot be able to stop this, but we can control and gradually decrease the percentage of people affected by eye disease. This can be done by detecting what type of eye disease the person is affected earlier and taking necessary treatment accordingly. For that, we developed software that can identify three types of eye disease using fundus image. So the classification of eye disease can be done by much technology. Here we are using a convolution neural network for classification. The image processing suits well for segmenting and analyzing the image according to the user's requirement. The outcome may be best described by identifying disease types and stages. In existing, different machine learning techniques were used to detect only a particular disease. Here we are using CNN, which is a part of deep learning systems, and so that we are going to classify two more additional diseases. [ABSTRACT FROM AUTHOR]

In this paper, we are going to simulate the antenna design using CST Microwave studios and designing a microstrip patch antenna with enhanced bandwidth for 5G applications, we are using a special substrate called 'KAPTON POLYMIDE', and we are going to increase the antenna bandwidth by using this Kapton substrate, here the operating frequency is to be greater than 1 GHz frequency, and we have explained the design methodology of bowtie shaped microstrip patch antenna, there are various parameters like the thickness of the substrate, resonant frequency, and we have different taking care of feeding strategies and has a number of shapes of the patch, in only millimeter-wave frequency range on suitable performances of antenna. For 5G connectivity, a compact and elevated bow-tie antenna is proposed. It also has 95.6 percent assessed radiation efficiency. Over the resonating band, the suggested design provides acceptable time-domain properties, adequate FBR, and appropriate impedance matching over the resonating band. [ABSTRACT FROM AUTHOR]