Nowadays, in electronic circuit design we are mostly using Voltage lift technique. In an arithmetic progression, it depicts the rise of voltage stage by stage. It gives voltage rising stage by stage in a geometric progression using a Super-lift converter, which is often used in solar PV applications. In power series, it enhances the transfer gain effectively. For providing good statistics and dynamic performance, Developed Cuckoo algorithm based on MPPT is used. MATLAB software is used to investigate the dynamic characteristics and analyse the closed loop performance of these converters with resistive loads under supply and load. Boosted power is supplied to BLDC motor.

As we all know India is a largest democratic country, the best form of our government is one which allows the citizen to cast the vote and elect the leader of their choice. The future of our country and fate of citizens all lies in a single vote. Traditionally we used ballot papers to vote and the votes are counted manually, which consume excess of time. Then ballot papers are replaced by electronic voting machine as it consumes large time to count the votes and due to the error involved in the manual counting process. The electronic voting machine gives quick publication of result which is accurate. The one that are temporarily out of their voting stations will have difficulties in casting their votes. The online voting should be adopted, as the current process is not flexible for voter’s convenience, online voting will increase the number of voter’s participation in the election. The proposed system will give trust and confidence to voters that the proposed voting system will provide protection to votes and as well as who cast their votes. In our proposed system, we have altered level of safety in voting process which provides reliable and secure voting. They are iris recognition, finger print and OTP. Next the voting portal is accessed and vote is encrypted by the blockchain end to end encryption.

Once a patient enters the comatose stage, it is really difficult to predict when he/she will be out of it. It may be within days, weeks, or may even take months and years together. Due to this situation, it becomes difficult for the hospital staff to monitor and keep watch over the patient at all times and thus slight body movements and life-like indications or abnormal activities may go unnoticed. To prevent such a situation, the proposed system has a wide range of wearable sensors fitted to the patient’s body. Sensors used are flex sensors, MEMS Accelerometer, heartbeat sensor, SPO2 oximeter sensor, temperature sensor, IR sensor in the form of goggles. These sensors help monitor the patient’s vitals and these data are stored in the cloud server and can be accessed when the need arises through a PC or smart-phone. The parameters are then upon plotted on a graph and hence analysis can be done on it to predict the approximate chances of recovery of the patient.