In this paper, we've designed a Smart Helmet for the safety of bike riders which includes an alcohol sensor to ensure the one who is driving the bike is sober and a rider authentication using face recognition to control theft. The programmed microcontroller 8051 indicates whether the rider is wearing the helmet with the help of two IR sensors, the alcohol sensor MQ-3 which is used to check the alcohol consumption level and the ARM 7 board, which is integrated with the PC using COM port1. A face detection algorithm called Viola-Jones coupled with SVM (support vector machines) for classification is used to track down faces for additional safety and security for the bike rider. If all the parameters are ok, then the biker is all set to use the vehicle.

Safety helmet with alcohol detection and theft control for bikers

This paper presents an experimental inverse approach to simultaneously estimate the temperature-dependent thermal properties of AISI 316 stainless steel. The heat flux conducted to the sample was corrected by using a transducer, evaluating contact resistance at microscopic level, and performing experiments under vacuum. Estimates were severely biased when heat flux correction was not applied. Metaheuristics were used to enlarge the search space, which can cover the thermal properties of all known metallic materials, thereby taking advantage of better thermal modeling adequacy. The estimation reliability was shown by comparison with literature data, statistical significance, uncertainty analysis, and inverse heat flux retrieval. 

A heat flux-corrected experimental inverse technique for simultaneously estimating the thermal properties of a metallic medium as functions of temperature

In the current situation many people lost their life due to accidents and the main reason behind it is they are not wearing helmets. So, by wearing a helmet people can save their life and for compulsory use of a helmet, it should be linked with a bike. With this reason, bikemet project is specially developed. This is a combination of a bike and helmet that has become smarter and safer than before with the aid of IoT. The BikeMet has a Proximity sensor which makes the user compulsorily wear the helmet and if still there is an emergency, then there is a keypad provided which will allow the user to use the bike by entering a Pin so it is convenient for the user to rid out from the situation. In the mechanism of bikemet, bike and helmet are linked together and they transmit the data from the helmet to the receiver of the bike and hence if the user wears a helmet, then only the user will be able to turn on the bike. The bike has various sensors like track if the bike gets stolen then automatically off the ignition of the bike and like Accelerometer to detect accidents and send messages to respective people for giving information. So, this application can save many lives.

/pdf/smart-device-for-bikers-to-prevent-from-accident-and-23az2fe7jy.pdf

Smart Device for Bikers to Prevent from Accident and Motorcycle Security

The effect when a motorcyclist includes in a high speed mishap without wearing a helmet is exceptionally unsafe and can bring about casualty. Wearing a helmet can lessen stun from the affect and may spare an existence. There are numerous nations authorizing a direction that requires the bike rider to wear a head protector at the point when riding on their bike, Indian traffic is considered as an illustration in our work. With this reason, these anticipate is uncommonly created as to enhance the security of the bike's rider. Motorcyclist will be frightened at the point when as far as possible is surpassed. A Force Sensing Resistor (FSR) also, DC motor are utilized for identification of the rider's head and identification of bike's rate separately. A 315 MHz Radio Recurrence Module as remote connection is used which will be ready to convey between transmitter circuit and receiver circuit. SST8951 is a microcontroller to control the whole part in the framework. Just when the rider clasped the helmet then immediately the drivers motor will begin. A LED will streak if the engine speed surpasses 40 km/hour in our design. Our proposed work has considered the regulations defined by Bangalore Traffic Police for vehicles travelling in Bangalore city. Keywords— Component; formatting; style; styling; insert (key

/pdf/optimal-two-wheeler-driving-using-smart-helmet-3utj2zedbj.pdf

Optimal Two Wheeler Driving using Smart Helmet

ABSTRACT This paper presents an inverse methodology to estimate the parameters of the non-uniform heat generation (function estimation) within a flat plate assembly using steady-state conjugate heat transfer experiments on the flat plate assembly. Steady-state laminar conjugate forced convection experiments on a flat plate assembly are conducted on a horizontal wind tunnel to estimate the parameters of the non-uniform heat generation within flat plate assembly using the inverse methodology. Bayesian inference based Metropolis Hastings–Markov Chain Monte Carlo (MH–MCMC) algorithm and experimental temperatures are employed in the inverse methodology. The experimental temperatures are measured at convenient locations of the flat plate assembly using liquid crystal thermography. In order to accomplish the retrieval, first, steady-state experiments on only the cork material are conducted to estimate the thermal conductivity of the cork material accurately for use in the estimation of the heat generation rate so that the additional error due to uncertainty in the thermal conductivity of the cork material does not affect our final goal of estimating heat generation rate. Following this, steady-state experiments on the cork setup (consisting of a non-uniform heat generation heater and two symmetric cork plates) are conducted to ascertain the nature of heat generation of the heater using measured temperatures and fundamental rate laws. The priors are generated using coupled artificial neural network (ANN) and Levenberg–Marquardt (LM) algorithm for Bayesian inference. Using the Bayesian inference with priors, the parameters of non-uniform heat generation are then estimated in terms of the mean, maximum a posteriori with standard deviation. Finally, the simulated heat powers and temperatures are estimated with retrieved parameters of the non-uniform heat generation. These compared very well with the measured heat powers and temperatures. Finally, a recipe for solving a practical problem, in which only measured temperatures are available, is provided.

Systematic approach to estimate non-uniform heat generation rate in heat transfer problems using liquid crystal thermography and inverse methodology

Abstract This work reports a novel “divide and conquer” approach to estimate the principal thermal conductivities of an orthotropic material, specifically engineered with a view to demonstrate the potency of the inverse heat transfer method with unsteady temperature data. The sample is placed in a vacuum chamber maintained at a pressure of 8.6 mbar. The heat capacity of the engineered orthotropic material was determined via estimating the heat capacity of a solid SS304 in a sequential fashion. First steady-state experiments followed by a Bayesian estimation with the Metropolis Hastings-Markov Chain Monte Carlo method were done to obtain the thermal conductivity of a solid SS304 block. Using this as a prior, the heat capacity of solid SS304 was obtained through unsteady experiments followed by Bayesian estimation. The heat capacity of SS304 thus obtained is multiplied by the solidity of the engineered orthotropic material, and using this information, the three components of the orthotropic conductivity are estimated again using the Bayesian route. To expedite the estimation, a surrogate for the forward model was developed using artificial neural network. Finally, the retrieved parameters are used to determine the simulated temperatures through the forward model for the orthotropic material. These, when compared with the measured temperatures, gave excellent agreement.

Prediction of Orthotropic Thermal Conductivities Using Bayesian-Inference from Experiments under Vacuum Conditions

Fig. 1 Grid codes requirements. Abstract— This paper presents a low voltage rid-through (LVRT) capability enhancement strategy of a doubly-fed induction generator (DFIG) using a dynamic voltage restorer (DVR). The performance of the DVR depends on its controller. An Adaptive Fuzzy PI controller for the DVR is proposed to enhance the LVRT capability and fulfill the grid codes without disconnecting the turbine from the grid. Simulation results are presented for a 2 MW DFIG with a DVR system to validate the effectiveness of the proposed controltechnique.

/pdf/low-voltage-ride-through-capability-enhancement-of-a-dfig-2yforu377s.pdf

Suraj Kumar

Papers

Optimal Two Wheeler Driving using Smart Helmet

Systematic approach to estimate non-uniform heat generation rate in heat transfer problems using liquid crystal thermography and inverse methodology

Prediction of Orthotropic Thermal Conductivities Using Bayesian-Inference from Experiments under Vacuum Conditions

Low Voltage Ride-Through Capability Enhancement of A DFIG Wind Turbine using A Dynamic Voltage Restorer with Adaptive Fuzzy PI Controller

Report of the 73rd Annual Meeting & Symposium of The International Committee for Coal & Organic Petrology (ICCP 2022)