-22b9b34417bc6092a743d73 20220211051201061 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 06 30 2021 10 8 Assistant Professor, Department of Computer Science and Applications, Bangalore University, (Bengaluru), India. Annie Syrien Hanumanthappa M Professor, Department of Computer Science and Applications, Bangalore University, (Bengaluru), India Ravi Kumar K Scholar, Kalinga Institute of Industrial Management (KIIT), Bhubaneswar, (Odisha), India. The phenomenal development of the World Wide Web has resulted in enormous social networking sites producing tremendous data on web 2.0. Social networking sites have widened to a higher degree of use, in which any field of information can be sort by researchers. Data obtained from social media has strategized from many new machine learning algorithms and natural language processing. The data is unstructured; mining the data leads to finding important sentiments about various entities via appropriate classification techniques. In this paper, tweets’ opinions are analyzed through machine learning algorithms such as naive Bayes and support vector machines using R programming; results are computed and compared. The SVM model manifests the higher precision, and naïve Bayes provides higher accuracy for sentiment analysis on the Bengaluru traffic data. 06 30 2021 137 141 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.H9266.0610821 https://www.ijitee.org/portfolio-item/H92660610821/ Master’s, Digital Electronics and Communication Specialization, Dayananda Sagar College of Engineering, Bengaluru, India. Ms. Raveena Jokim Crastha Dr. Roopa M Professor, Department of Electronics and Communication at Dayananda Sagar College of Engineering, Bengaluru, India. The automotive manufacturers are working towards enhancing sophisticated designs and technologies that enable better vehicle-user connectivity by integrating all the control units to one infotainment system. This key feature with high-level intelligence and competency plays an important role with an increase in demand in the production process of the automotive industry. This paper proposes a unique design of USB smart charger module that is designed in a way to fit into limited space in a front panel of the vehicle. The specific design methodology of the DC-DC SMPS buck converter with the protection circuits which serves as the important section of the smart charger is explained. The module is designed with both single and double port that are identical to each other. Each of these models provides effective connectivity of devices in the vehicle network with secured over-current, over-voltage and short circuit protection circuitry. The configuration of controllers and connectors used is implemented in Altium. The functionality of the system designed is examined and verified in TINA-TI tool. 06 30 2021 120 126 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.H9264.0610821 https://www.ijitee.org/portfolio-item/H92640610821/