Maintaining discipline in public transport system is need of today. since traffic on the roads is increasing day by day and so the pollution. Traffic signals plays very important role in maintaining discipline in public/local transportation systems in urban cities like Mumbai, Pune in India. Many underage children drives vehicles , and driving without license may cause accidents. Maintaining the discipline in public transport is core responsibility of each and every citizen. Due to corruption and non adherence to rules are major hurdle in maintaining the local transport discipline of India. Proposed , "Bio metric based Challan system for RTO" which makes use of human characteristics such as fingure prints and Eris to perform verification process against the RTO database stored under "licensed users", which will help to reduce the rate of corruption and make people think to maintain the discipline in local transport which may reduce the count of traffic rule brake cases.

Machine learning techniques have been used in order to predict the condition and emotion of a driver to provide information that will improve safety on the road. It is an application of artificial intelligence. The face, an important part of the body, conveys a lot of information. When a driver is in a state of fatigue, the facial expressions, e.g., the frequency of blinking and yawning, are different from those in the normal state. In this paper, we propose a system called “Advanced Driver Assistant System”, which detects the drivers fatigue status, such as yawning, blinking, and duration of eye closure, using video images, without equipping their bodies with devices. Artificial Intelligence is a method by which systems can automatically learn as well as improve without being explicitly programmed. A driver’s condition can be estimated by bio-indicators, behavior while driving as well as the expressions on the face of a driver. In this paper we present an all-inclusive survey of recent works related to driver drowsiness detection and alert system. We also present the various machine learning techniques such as CNN algorithm, HAAR based cascade classifier, OpenCV which are used in order to determine the driver’s condition. Finally, we identify the challenges faced by the current systems and present the corresponding research opportunities. Keywords: Convolutional neural network, fatigue detection, feature location, face tracking, Artificial Intelligence, Autonomous Vehicle Technology, Drowsiness Detection, Machine Learning.

Since the COVID-19 pandemic took the world by storm, governments around the world have taken tough but necessary measures to control its spread. During the COVID-19 pandemic, social distancing was widely used as a non-pharmaceutical prevention measure. So we designed social distancing monitoring robot that aims to limit the spread of Covid by measuring the distance between individuals in queues. This system is very essential for banks, government offices, shopping malls, schools, and theatres, among others, where long queues can last for hours every day. Furthermore, this robot also consists automatic hand sanitization and contactless temperature measurement. The design and working of social distancing Robot, Contactless Human Body Temperature and Sanitization is presented in this study. Keywords: COVID-19, Pandemic, Social Distancing, MLX90614 Sensor, hand sanitization.