Biogas fuel station for Dilkap College
Biogas is one of the most useful gases which is widely used for various purpose. Biogas is used as a heat energy, electricity generation and if the gas is treated further can be into Compressed Natural Gas (CNG). The production of biogas is under the anaerobic condition where oxygen is absent and anaerobic bacteria are present. The temperature plays an important role in the whole process. In this project waste of food produced from the kitchen is the important source of an ingredient which is useful for the production of biogas. The kitchen food waste can be easily decomposable and produce gases which contain methane, carbon dioxide, moisture, etc. The biogas produced can be used as a supplement fuel for kitchen and also used to generate electricity. The main unit of the process is digester in which the biomass waste in feeded after some interval of days the degradation takes place, during process oxygen is used completely and carbon dioxide is produced, know this carbon dioxide is used for the production of methane in presence of methanogen bacteria.The scrubber is installed to remove the useless gases rather than methane. The first scrubber is soda lime which is used to remove carbon dioxide. Second scrubber in which there is silica gel which is useful for the removal of hydrogen sulfate. Third scrubber in which there is ethylene glycol which is used for removal of moisture present in the gas. After removal of all such gases only methane is left which is combustible and that is also known as natural gas which is used to generate electricity, heat, etc. Final product which is left in digester can also be used as fertilizer.
Published by: Mukri Farhan Rizwan, Shaikh Abrar Sattar, Yadav Sunil Fathebahadur, Sharan Reetika
Author: Mukri Farhan Rizwan
Paper ID: V4I2-1709
Paper Status: published
Published: April 7, 2018
Agricultural robot for seed sowing
Most of the states in India are dependent on agriculture. About 70% people are dependent upon agriculture. People spend more money on agriculture but they not get that much output, so it is not that much beneficial to them. To reduce the spend money; efforts of people and to increase accuracy the agricultural system in India should be advanced. In agriculture field Numbers of operations are performed like seed sowing, weeding, cutting, pesticide spraying etc. Seed sowing is very basic and significant operation. The existing equipment’s used for seed sowing are very difficult and inconvenient to handle. So we have suggested to develop an equipment which will reduce the efforts of farmers. A robot is a mechanical, artificial agent and is usually an electromechanical system, because of software programming it makes complicated tasks easy to perform. Applying automation to agriculture its advancements to the industry while helping farmers to save money and time. In this system automatic seed sowing is done which aims to drop seeds at particular position with specified distance between two seeds and lines while sowing by using ARM controller.
Published by: Vidya Vishnu Koli, Rani Ramchandra Chavan, Rahul Maruti Kumbhar, Madhuri Hari Adat, Ajinkya Sharad Mane
Author: Vidya Vishnu Koli
Paper ID: V4I2-1676
Paper Status: published
Published: April 7, 2018
Video/Image Super-Resolution using convolution neural networks
Convolutional Neural Networks (CNN) is a unique kind of Deep Neural Networks (DNN) which has a place in the Machine Learning Domain. This calculation has so far been effectively connected to Image Super-Resolution (SR) and also other picture reclamation and characterization errands. Picture/Video Super Resolution implies upgrading the picture/video quality.In this proposed framework, we consider the testing issue of video super-resolution.Often there is a tradeoff between the spatial and worldly determination estimation and, consequently regardless of whether the quantity of pixels in the picture is progressively the picture, we get is a low-quality picture and a similar idea applies to recordings. Henceforth, we propose a CNN that is prepared on both the spatial and the fleeting measurements of recordings to improve their spatial determination. Back to back edges are movement remunerated and utilized as a contribution to a CNN that gives super-settled video outlines as a yield. While extensive picture databases are accessible to prepare profound neural systems, it is additionally testing to make a vast video database of adequate quality to prepare neural systems for video rebuilding. We demonstrate that by utilizing pictures to pre-train our model, a generally little video database is adequate for the preparation of our model to accomplish better outcomes. Encourage we analyze our CNN based Very Deep Image/Video Super Resolution approach with presently utilized Iterative Video Super-Resolution (SR) calculations.
Published by: Amey A. Tarfe, Kunal P. Nayak, Rohan K. Netalkar, Shreyas D. Palve, Dr. Neeraj Sharma
Author: Amey A. Tarfe
Paper ID: V4I2-1596
Paper Status: published
Published: April 7, 2018
GPS and GSM based geo location guide using RF with emergency alert via SMS
The people entering a theme park are provided with a small unit called as RF receiver which contains an emergency button. Whenever the person enters a ride or a game in the theme park, they will be intimated with their location in an LCD receiver, this is done by an RF transmitter kept in various location with fixed IR sensors, which senses the person and the signal is transmitted to the receiver. In the receiver, a programmed Arduino decides the location based on the received information and it is displayed in the LCD display. When there is an emergency they can push a button present on the receiver unit and the information goes to security as well as controller of the game in the form of an alert message along with the location of the person using GSM module. Here the location of the person is found using GPS tracker.
Published by: Veena V, Vidhiyalukshmi G, Rajalakshmi R, Dr. S. Leones Sherwin
Author: Veena V
Paper ID: V4I2-1698
Paper Status: published
Published: April 7, 2018
IoT based efficient water distribution system for human and agricultural uses
An Integrated System Based On Internet Of Things Technology Is Proposed For Managing, Monitoring and Efficient Distribution Of Water. With an increase in Population, urban residential areas have increased because of this reasons water has become a crucial problem which affects the problem of water distribution, interrupted water supply, water conservation, water consumption. Current Water distribution and management system involves Water wastage and faces new challenges like System Lags behind related to technical aspects, Degradation of Soil Quality with respect to Irrigation. In order to curb the problems involved in the existing system, Solutions are implemented in the proposed system. IoT Based Efficient Water Distribution SystemFor Human And Agricultural Use Like The Name Says Is all About Managing Water Supply Throughout The Scale, including Small Societies, Townships, Urban Infrastructure And Also For Irrigational use.The Water supply with continuous monitoring makes a proper distribution so that, we can have a record of the available amount of water in tanks, flow rate, abnormality in the distribution line. IoT is a network of physical objects which are embedded with electronic devices, sensors, software, and network connectivity. Monitoring can be done from anywhere as the central office. As per the scarcity of the water, it will be indicated by sending short message service notification as well notification of water supply timing to societies. This proposed system also helps the farmers to irrigate the farmland in an efficient manner with automated irrigation system based on soil moisture and DHT11 sensor. The DHT11 is low-cost humidity and temperature sensor. It senses the humidity and temperature in the environment of the farmland and sends the result to the system.The moisture sensor is used to check the soil moisture and based on this microcontroller drives the solenoid valve. This will improve the cultivation method and leads to better productivity. It Can Control The Water Usage In A Precise Way.
Published by: Mayur Bhalchandra Tangadi, Chirag Sadanand Patil, Prayag Narayan Mhatre, Kanchan Dabre
Author: Mayur Bhalchandra Tangadi
Paper ID: V4I2-1703
Paper Status: published
Published: April 7, 2018
Emotion recognition using face and voice analysis
The goal of this project is to design a system that reads the face and voice of a person in conjunction to detect the sentimental and emotional state of a person based on that data. Humans are said to express almost 50% of what they want to convey in non-verbal cues. This concept can be used to analyze on the tone and facial expressions both of the non-verbal cues that can be used to detect the sentimental and emotional state of a person based on his facial expressions and speech features. Here make use preexisting databases, classify them according to their emotions and create classifiers for the purpose of emotion recognition of new input data. There are many data sets available from previous surveys. The database we use in here is Extended Cohn Kanade database for the facial expressions and SAVEE database for speech data. We then make use of the SVM classifier to classify the respective emotional labels appropriate for each of the image and then create an SVM classifier which is able to classify the input given to it. The emotional state of the face and the voice of the user is found out and then we read them both in conjunction to get a more accurate representation of the user’s emotional state. We then play an appropriate music depending on the emotion of the user.
Published by: Rohan Raphy Thattil, Joseph Gigo Ignatiaus, Shafeer P. N, Shyam Krishna M
Author: Rohan Raphy Thattil
Paper ID: V4I2-1677
Paper Status: published
Published: April 7, 2018
