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Research Paper

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

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Research Paper

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

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Review Paper

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

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Research Paper

Artificial farming – An electronic approach to grow plants

This project is for growing plants or vegetables inside the packed electronic environment by using the artificial plant grow Led to growing the plants. The photosynthesis process carried out by the plants independent on the LEDs which will provide the total electronic surrounding to the crops so we can call it as an “Artificial farming- an electronic approach to grow plants”. In this project, we have made a prototype of actual concept. The amount of water required to grow the plants is very much less as compared to the traditional farming, here we have provided the automation technique for providing water to the plants. In this prototype, we have made a rack structure so that we can take the more crop production by making racks on one above in a small area. In this artificial environment, we are using sensors to monitor the condition of the soil, air, temperature. According to collected data by the sensors, this data is provided to aurdino for the controlling the water supply, lights, fans. The LEDs are used to provide the special light wavelength. By using that wavelength the plants are going to carry out the photosynthesis process. In this process, the food making process of plants is light dependent. As the environment is indoor it will not have any insects, and pests affecting the crops, hence no insecticides and pesticides will be required. The indoor environment will neither evaporate water nor will percolate it into the earth hence water requirements be very small. The indoor environment is equipped with artificial lighting, so crops can be grown independent of season. By using the electronic farming method we can reduce the greenhouse gases, the overall quality of the food is increased due to the organic fertilizers being used to grow the plant and also the pesticides and the chemical fertilizers are not used in this type of farming. The water required for the electronic farming is much lesser than the ordinary traditional farming. As it is completely indoor so that the atmospheric effect is not observed on the plant so we can take year-round food production.

Published by: Ajinkya Bhupal Mahajan, Bhau Bhimrao Kharat, Swapnil Chandrakant Kundale

Author: Ajinkya Bhupal Mahajan

Paper ID: V4I2-1597

Paper Status: published

Published: April 7, 2018

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Research Paper

Data preprocessing and balancing to enhance end to end learning in self-driving vehicle

Driving a vehicle has always been a demanding task be it any vehicle since robotics and artificial intelligence has progressed multi-folds in the last decade which gave us the technological grounds to automate many processes which include driving. Developing autonomous vehicle is the current research area for many corporate like are Google, Tesla, Nvidia, and Uber. Several proposed methodology for them is Nvidia’s Behavioural Cloning, CommaAI’s OPENPILOT, Tesla’s AUTOPILOT all of which uses the camera to process surrounding of the vehicle. In this paper, we discuss Nvidia’s recent work (behavioral cloning) and incorporate their work with few techniques of our own like filtering the repeating data and augment the input data to reduce the amount of data collection required.

Published by: Syed Zishan Ali, Rishabh Sharda, Abhishek Dewangan, Sourabh Chawda, Rahul Sharma

Author: Syed Zishan Ali

Paper ID: V4I2-1629

Paper Status: published

Published: April 7, 2018

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Research Paper

Identification of quality index of fruit/vegetable using Image Processing

The recent application and development of image analysis in the quality evaluation of products in the field of agricultural and food. Images are the important source of data and information in the agricultural sciences. The basic concepts and technologies associated with computer vision system and automatic vision-based technology, tool used in image analysis and automated sorting and grading are highlighted.The proposed system starts the process by capturing the fruit or vegetable image.Then, the image is transmitted to the processing level where the fruit features like color, shape and size of fruit samples are extracted. After that by using artificial neural network fruit images are going through the training and testing. In this proposed paper, the neural network is used to detect shape, size and color of fruit and with the combination of these three features, the results obtained are very promising.

Published by: R. Prince, H. Sathish, R. Sai Kumar, V. Karthik, S. Jeya Anusuya, S. P. Vijay Vardhan Reddy

Author: R. Prince

Paper ID: V4I2-1322

Paper Status: published

Published: April 6, 2018

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