MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

Collaborative Robots have been employed in the industrial environment for the past decade such as factories, workshops, warehouses, etc. There are various unexplored environments for a collaborative robot. A common household environment being the least explored with the most potential. A number of tasks are to be performed in a household, for example cleaning the kitchen table, handling a common tool, cooking, etc. These tasks appear to be linear and simple but some of them often require a third hand or some homely knowledge. The demographic of humans between the age of 20-30 often refrain from doing these tasks, reason being the physical and mental stress one incurs from them. The Collaborative Robot acts as a companion by employing the chat function, allowing users to interact in multiple ways, designed as a cobot in such a way that it helps improve the overall performance measures of the tasks and assists the user to perform the task. The system uses a Raspberry Pi as the main control unit and is coded in python, it uses TensorFlow and Mach

World University root node

School of Mechanical Engineering

Engineering and Technology

International Research Journal of Engineering and Technology (IRJET)Engineering and Technology

Design of Shoulder Mounted Collaborative Robot for Household Tasks

Nowadays, There is a need to think about the major causes of pollution, one of which is crude oil, the plastic is used worldwide today. Plastic is found everywhere. Creation of plastics was a boon for low cost substitution to metal, being cheap is now causing environment problem. Plastic and polymer-carbon chains have long life and could be classified according to the uses. This has lead us to a point where waste plastics in the tons are causing various environmental hazards, not to mention the shame it bring to one’s mind when he sees his own country littered with it. It is still on the places of landfills and oceans, which has become major concern of the world. There is a need to think of this issue as it’s leading to impact environment seriously. There is ever increasing global demand for energy in recent years. A pyrolysis process provides an alternative energy source which reduces pollution and recycles waste plastics. In this study, pyrolysis of waste plastic is solution for the issue in the current world, disposal of waste plastic will also be minimized if applying pyrolysis process in different cites & make the environment clean. This paper deals with extracting pyrolysis oil/pyro fuel from waste plastic that is found in everyday life & by recycling to make out pyrolysis fuel & reduce carbon emission. This project leads to a meaningful contribution to Swatch Baharat Abhiyan & Paris climate deal.

GIS Science Publication

Waste Plastic Pyrolysis: An efficient way of Plastic recycling

Facial analysis in videos and images has been a relatively tough task for machine learning models. Recent use of deep learning approaches has demonstrated substantial improvement in results and reliability and can be used for problems such as face recognition, emotion recognition and emotion reaction prediction. In the case of emotion reaction, relevant information of emotions in individual frames often must be aggregated over a variable length sequence of frames and speech signal to produce an appreciable prediction. Emotion reaction prediction is a subset of sequence analysis task and heavily relies on dynamic temporal and spectral features. Convolution neural networks (CNNs) have been extensively used for emotion recognition problems and have produced reliable results. However, they lack the ability to extract time-series information from a sequence of inputs and cannot model an emotion transaction. Recurrent neural networks (RNNs) are being used profoundly due to their ability to yield impressive results on a variety of tasks in the field of sequence analysis. In this work, we propose a system for emotion recognition and reaction prediction in videos. The primary focus is experimental analysis of a hybrid CNN-RNN architecture for emotion transaction analysis that can recognize the emotion in a frame in a video and predict its appropriate reaction. © 2017 IEEE.

School of Computer Engineering & Technology

Proceedings - 2017 3rd IEEE International Conference on Research in Computational Intelligence and Communication Networks, ICRCICN 2017

Emotion recognition and reaction prediction in videos

Most of the mechanical structures and machineries use Bolted joints ,because of its ease in assembly and disassembly which facilitates convenience for maintenance, repair at low cost. Establishing and maintaining appropriate bolt preload in a bolted joint is the principle on which all the bolted joints work. The bolted joint will not separate until the service load of joint exceeds the preload or clamping force.However, loosening of the bolts because of vibrations has been one of the major causes of bolt loosening due to dynamic loading, a properly preloaded joint can get separated due to vibrations. A soft foot condition is one of the sources responsible for reducing the clamping force. In this paper, the effect of soft foot condition is analysed using combined DoE and FEA technique.Good qualitative agreement was observed between FEA results and results based on conventional theories of material mechanics.