Sri Ramakrishna Engineering College

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

IOT based smart garbage alert system using Arduino UNO

Abstract: Waste management is one of the primary problem that the world faces irrespective of the case of developed or developing country. The key issue in the waste management is that the garbage bin at public places gets overflowed well in advance before the commencement of the next cleaning process. It in turn leads to various hazards such as bad odor & ugliness to that place which may be the root cause for spread of various diseases. To avoid all such hazardous scenario and maintain public cleanliness and health this work is mounted on a smart garbage system. The main theme of the work is to develop a smart intelligent garbage alert system for a proper garbage management. This paper proposes a smart alert system for garbage clearance by giving an alert signal to the municipal web server for instant cleaning of dustbin with proper verification based on level of garbage filling. This process is aided by the ultrasonic sensor which is interfaced with Arduino UNO to check the level of garbage filled in the dustbin and sends the alert to the municipal web server once if garbage is filled. After cleaning the dustbin, the driver confirms the task of emptying the garbage with the aid of RFID Tag. RFID is a computing technology that is used for verification process and in addition, it also enhances the smart garbage alert system by providing automatic identification of garbage filled in the dustbin and sends the status of clean-up to the server affirming that the work is done. The whole process is upheld by an embedded module integrated with RF ID and IOT Facilitation. The real time status of how waste collection is being done could be monitored and followed up by the municipality authority with the aid of this system. In addition to this the necessary remedial / alternate measures could be adapted. An Android application is developed and linked to a web server to intimate the alerts from the microcontroller to the urban office and to perform the remote monitoring of the cleaning process, done by the workers, thereby reducing the manual process of monitoring and verification. The notifications are sent to the Android application using Wi-Fi module.

Synthesis of ZnO nanoparticles using leaf extract of Tectona grandis (L.) and their anti-bacterial, anti-arthritic, anti-oxidant and in vitro cytotoxicity activities

Abstract: The novelty of this present work is the investigation of the anti-bacterial, anti-arthritic, anti-oxidant and in vitro cytotoxicity activities of green synthesized Zinc Oxide Nanoparticles (ZnO NPs) using leaf aqueous extract of Tectona grandis (L.). Zinc nitrate acts as the precursor and the leaf extract acts as the reducing agent. The synthesized ZnO NPs are characterized by powder X-ray diffraction (PXRD) analysis and the crystalline size is calculated by the Scherrer formula. FTIR analysis confirms the presence of various functional groups in the leaf extract as well as in the NPs. The UV absorption peak is observed at 360 nm and the calculated energy band gap is found to be 3.4 eV. Dynamic Light Scattering (DLS) analysis shows the stability and particle size of the synthesized ZnO NPs. The crystalline size, shape and surface morphology of the ZnO NPs are determined by using Field Emission Scanning Electron Microscopy (FE-SEM). Green synthesized ZnO NPs exhibited interesting antibacterial activity against Gram-positive and Gram-negative bacteria and exerted excellent DPPH (di(phenyl)-(2,4,6-trinitrophenyl)iminoazanium) free radical scavenging activity. They also showed maximum inhibition of protein denaturation (90.46 ± 0.02) and proteinase inhibitory activity (87.68 ± 0.03) at a dose of 200 μg ml−1 respectively. The anticancer activity of ZnO NPs was also tested against normal and cancer osteoblast MC3t3-E1 cell lines and found a reduction in the size of cancer cells.

Implementation and Performance Analysis of Digital Controllers for Brushless DC Motor Drives

Abstract: This paper presents design and digital implementation of a fuzzy controller for achieving improved performance of Brushless dc (BLDC) servomotor drive. The performance of fuzzy and PID controller-based BLDC servomotor drives is investigated under different operating conditions such as change in reference speed, parameter variations, load disturbance, etc. BLDC servomotors are used in aerospace, instrumentation systems, space vehicles, electric vehicles, robotics, and industrial control applications. In such applications, conventional controllers like P, PI, and PID are being used with the BLDC servomotor drive control systems to achieve satisfactory transient and steady-state responses. However, the major problem associated with the conventional PID controller is that the tuned gain parameters obtained for such BLDC servomotor drive control systems do not yield better transient and steady-state responses under different operating conditions such as parameter variations, load disturbances, etc. In this paper, design and implementation of fuzzy controller is presented and its performance is compared with PID controller to show its capability to track the error and usefulness of fuzzy controller in control applications.