Accident detection and rescue system
The Rapid growth of technology and infrastructure has made our lives easier. The advent of technology has also increased the traffic hazards and the road accidents take place frequently which causes huge loss of life and property because of the poor emergency facilities. The incidence of accidental deaths increased by 44.2% in 2011 from 2001. Our project will provide an optimum solution to this drawback. Nowadays we are able to track vehicles using many applications which helps in securing personal vehicles, public vehicles, feet units and others. Furthermore, there is a rapid increase in the occurrence of Road accidents. This paper is about a system that is developed to automatically detect an accident and alert the nearest hospitals and medical services about it. This system can also locate the place of the accident so that the medical services can be directed immediately towards it. The goal of this paper is to build up an Accident Alert System Using Arduino. The system comprises Sensors, GPS & GSM Module support in sending messages. The Sensors is used to detect vibrations and impact are used to detect an accident. Short Message will contain GPS [Latitude, Longitude] which helps in locating the vehicles
Published by: Mihri Lad, Om Bellilkatti, Kanshiq Ladha, Deepak Khachane
Author: Mihri Lad
Paper ID: V7I5-1180
Paper Status: published
Published: September 8, 2021
The Biofuel Price Stabilization Mechanism
This article studies the capacity of biofuels to reduce motor fuel price fluctuations. We hypothesize the dependence between crude oil and biodiesel blend prices in Spain and the EU. Copula models are a method of study. Results suggest that the practice of blending biodiesel with diesel can protect consumers against extreme crude oil price increases. This can also help reduce the carbon emissions and the Green House Gases (GHG's) emitted upon burning fossil fuels
Published by: Soham Das
Author: Soham Das
Paper ID: V7I5-1166
Paper Status: published
Published: September 7, 2021
Sentiment analysis of COVID-19 Vaccination Tweets on Twitter using Machine Learning Algorithm
After Declaring pandemic in March 2020 public health prevention measures have proven to be somewhat effective in limiting the spread of COVID-19. Protective immunity through vaccination will be great importance of in ending the pandemic. This work aims to identify the sentiments of the masses towards vaccination by analyzing the text tweets. 68,654 tweets are retrieved from Twitter posted within the timeline from December 2020 to January 2021. Sentiment, polarity score, and subjectivity score were computed and analyzed on the basis of text and date columns. According to the polarity and subjectivity scores, tweets were classified as positive, negative, and neutral using the TextBlob library of natural language processing. Also, the user’s view on the vaccination was analyzed using machine learning algorithms such as Naïve Bayes (NB) and Logistic Regression (LR). The highest accuracy achieved was 90% by Logistic Regression (LR). It was observed from the results that the sentiments towards the vaccine were positive on the initial day but a shift to negative sentiments was observed. Later, the sentiment towards vaccines is again positive.
Published by: Disha Jethva
Author: Disha Jethva
Paper ID: V7I5-1175
Paper Status: published
Published: September 7, 2021
The Effect of Nylon Fibers in Self-Consolidating Concrete (SCC)
Self-compacted concrete (SCC) is a unique type of concrete that settles into the formwork and fills all of its corners without the use of compaction or vibration. Because SCC has a higher flowability, it becomes brittle and performs poorly under stress and bending. One of the most effective ways to increase the tensile and flexural performance of SCC is to include randomly distributed short and discontinuous fibers. In this regard, this experimental study is undertaken to investigate the effect of nylon fibers (NF) on the fresh and hardened properties of SCC. Two different lengths, 20 mm and 12 mm, were used, as well as five different volumetric percentages of NF, 0.1, 0.2, 0.3, 0.4, and 0.5 percent. The results demonstrated that adding NF to SCC had a minor effect on its fresh characteristics. However, the magnitude of the influence is not large enough to be considered a significant factor. According to EFNARC criteria, the fresh characteristics of whole mixtures are within the required range. With the addition of NF, the strength qualities improve. the extent of increment is greater for the longer length of NF. The optimum volumetric fraction of NF for producing high strength SCC was found as 0.5%. The fresh properties of complete combinations are within the required range, according to EFNARC guidelines. The strength properties enhance with the addition of NF. The length of NF has a significant impact on the amount of increment. The volumetric proportion of NF required to produce high-strength SCC was discovered to be 0.5 percent.
Published by: Qasim Alsherify
Author: Qasim Alsherify
Paper ID: V7I5-1171
Paper Status: published
Published: September 7, 2021
Adsorption Behavior of Cu, Al, Mn, Sr, Pb, Cd, Zn, and Ca Metal Ions on Cation Exchange Resign Dowex 50 WX8 (NH4+ form) from Aqueous Acetone – Ammonium Propionate Media
In the field of inorganic separation, the incentive to explore the use of non-aqueous or mixed solvent has been enhanced selectivity’s, discovered quite early in such media for Zeolites [1] and ion exchange resins [2]. The partial substitution of an aqueous solution by organic solvent produces a number of changes in an exchange system. The electrolyte plays a significant role in the ion exchange equilibrium with aqueous solutions. This effect is expected to be even more important in the adsorption equilibriums of metal ions from mixed aqueous organic solvents. Adsorption equilibrium depends on the properties of the organic solvent and the reaction with resin and electrolytes which determine the equilibrium. The metal ion exchange on cation exchangers and their uses has been done.
Published by: Rajan Kamble
Author: Rajan Kamble
Paper ID: V7I5-1169
Paper Status: published
Published: September 7, 2021
Automated real-time detection and reporting accidents using IoT based helmet
In recent days, road accidents are occurred as regular habits by mainly using motorbikes. The goal of this project is proposed to prevent, detect and report the accidents to the respective authorities. This may reduce severe accidents and as well as may save the lives of people. We propose the solution, where the helmet itself initiates communication to report the accident using a person’s phone. Our design consists of Arduino Microcontroller, transmitter and receivers, and sensors. By using RF transmitter and indicator, indicates that the person is wearing a helmet, if it doesn’t indicate which means the person doesn’t wear a helmet. Only then does the bike get started. So, this will be the initial prevention in this design. If a severe accident occurs, the pressure sensor in the helmet detects the pressure limit, then python code executes and triggers the alert message using cloud authentication. Mobile application catches the trigger and obtain the device’s location and sends the alert message to nearby hospitals, relations. There will also be a buzzer sound to alert the nearby people to draw attention, even if it is unable to send an alert message. If there is a mild accident and no injury, there will be a reset button to cancel the sending of the alert messages using a secret PIN.
Published by: Karthik B.
Author: Karthik B.
Paper ID: V7I5-1151
Paper Status: published
Published: September 4, 2021
