Sri Ramakrishna Engineering College

About: Sri Ramakrishna Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Control theory. The organization has 1030 authors who have published 843 publications receiving 3822 citations.

Blockchain Based Covid Vaccine Booking and Vaccine Management System

Abstract: Immunization is all about using Block chain for managing and tracing the vaccine stocks, logistics and transparent distribution. Immunization gives you continuous visibility and enables actionable insights to track vaccine distribution and ensure a fair and equitable distribution. Immunization allows you to book your vaccination appointments and will also allow you to keep track of the vaccine being distributed. Block chain helps in maintaining the integrity and transparency of the whole process right from inception of the vaccine.

Exploring nanotechnology for diagnostic, therapy and medicine

Abstract: In current days, knowledge enhancement is growing more. Nanotechnology can applied to self-repeating machines and mechanical technology, compound designing, mechanical designing, science, natural designing, and electrical designing. Nanotechnology has the great preference to improves produce new and superior product. Nanomaterials to perceive avoid and eliminate pollution. Nanotechnologies are blueprint, invention and applied in medicine, therapy, diagnostic, sequencing and environmental protection. The usage of nanotechnology is rapidly increases in entire future market. This article explore the nanotechnology for medicine, diagnostic and therapy.

Facial Recognition And Verification System For Accessing Patient Health Records

Abstract: This paper proposes an Image processing based embedded system to access patient health records by face recognition. Nowadays carrying all the medical report during every visit became a tedious process and hence the medical reports are stored in a database and accessed with a unique identification number. In this paper, face recognition is used instead of a unique identification number. In emergency situations, this helps to know the medical history of the patients. The proposed system consists of a Raspberry Pi 3 processor and a webcam which is used to capture the face. Local Binary Pattern(LBP) and HAAR Cascade algorithms are used to detect and recognize the face. The features of the face are extracted using LBP and HAAR cascade algorithm. The extracted features are given to classifier which compares these features with the trained ones and displays the data and reports stored in the database.Both algorithms are implemented in python using OpenCV. Experimental results indicate that LBP algorithm is more efficient than HAAR cascade classifier algorithm in terms of execution time, classification accuracy, confusion matrix, and F1 score.

DC-DC converter topology with maximum power point tracking strategies for renewable energy systems — A survey

Abstract: This paper focuses on a survey of the renewable energy systems, which are reliable and they can play a vital role in power generation and they are gradually being accepted as important alternatives because these are freely available, environmental friendly over fossil fuels and they are considered as promising power generating sources due to their availability. The energy system depends on reliable power and the corresponding system cost which are the two main concerns of renewable energy resources under varying weather conditions. The renewable energy sources like Sun, Wind, Geothermal, Ocean and biomass are environmental friendly and sustainable. Out of these the Ocean and Geothermal are not cost effective because it is not feasible to transport from long distances. The renewable power generation systems are becoming popular in remote areas due to the significant rise in fuel cost and progression in renewable energy technologies. It is found that the progress effort which has non-linear characteristics in the renewable field is still required to achieve the system performance. This paper is to review the current state of effective DC-DC power electronic converters, different control strategies, an intelligent (Maximum Power Point Tracking) MPPT strategies and simulations likely for different renewable energy systems.

Design and Implementation of Improved Electronic Load Controller for Self-Excited Induction Generator for Rural Electrification

Abstract: This paper offers an alternative technique, namely, Improved Electronic Load Controller (IELC), which is proposal to improve power quality, maintaining voltage at frequency desired level for rural electrification. The design and development of IELC are considered as microhydroenergy system. The proposed work aims to concentrate on the new schemes for rural electrification with the help of different kinds of hybrid energy systems. The objective of the proposed scheme is to maintain the speed of generation against fluctuating rural demand. The Electronic Load Controller (ELC) is used to connect and disconnect the dump load during the operation of the system, and which absorbs the load when consumer are not in active will enhance the lifestyle of the rural population and improve the living standards. Hydroelectricity is a promising option for electrification of remote villages in India. The conventional methods are not suitable to act as standalone system. Hence, the designing of a proper ELC is essential. The improved electronic load control performance tested with simulation at validated through hardware setup.