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;

&nbsp;

MIT World Peace University

Engineering and Technology

Agritourism is the blend of tourism and agriculture industries which allows the community to become engaged with agriculture environment, local food and rural experience beyond the farmers’ market, and also allows the farmer an entire new source of revenue. There are many popular articles, academic articles, study reports available in global context related agritourism. However, there is no comprehensive overview of the research work published in India. This study presents a comprehensive literature review to gain a better understanding of the contents of the agritourism development literature. Based on the findings from the literature review, concept development, the impact of agritourism especially social and economic on the development of agriculture and rural community are identified. In addition, factors to be consider while starting Agritourism is suggested.

School of Electronics & Communication Engineering

World University root node

International Conference on Ongoing Reach in Management and IT

Agritourism Development in India: An Extended Literature Review.

This paper reports literature review in the field of pharmaceutical marketing emphasizing problems faced by medical representatives. India after globalization and being the second highest populated country has emerged as major pharmaceutical market in the world. Pharmaceutical marketing in India is highly relied on personal relationship between medical representatives and doctors. In the last decade, many foreign companies have entered in Indian market. This has posed highly competitive and challenging work environment for medical representatives. Therefore, it is indispensable to study the challenges faced by medical representatives in this dynamic environment.

School of Management PG

Management

Journal of Chinese Pharmaceutical Sciences

Management of pharmaceutical sales representatives: A literature review

Three dimensional view of objects is becoming of utmost importance. In day to day technology and entertainment applications, instead of using traditional multi-view technology. We are proposing estimation of distance co-ordinates using distances obtained by ifm O3D200 three dimensional camera at lower resolution of image pixels. The camera uses laser technology with time of flight principle. The same scene is imaged using high resolution 2D camera. The matching of certain feature points in 3D &amp; 2D camera scene and interpolating distance a 3D view can be reconstructed by simple triangulation process. The main features used are edges linked used Hough transform for matching and image registration. It has been observed that bilinear and bicubic interpolation gives better results eventhough the resolution of 3Dcamera is very less. We further applied technique for computation of volume in water tank and trench, which was very close to the actual measurement.

IEEE International Conference on Computer Communication and Control, IC4 2015

Three dimensional image reconstruction using interpolation of distance and image registration

Solid State relay based single phase power quality disturbance generator is proposed in this paper. Digital control system based on microcontroller 89C51 is implemented to control the duration of power quality disturbances. Voltage sag, swell and interruption are generated. Dimmerstat is used to change the voltage levels and so to control the intensity of disturbances. Design of proposed generator is discussed. Simple design and use of easily available components makes this generator economic. It is highly suitable in power quality laboratory for experimental work. Students working on voltage sag/swell compensation and monitoring of power quality events can use this generator. Proposed generator is used as an application for PC based real time power quality monitoring system. Monitoring system is designed in LabVIEW. For fetching the real time signal, voltage sensor and data acquisition system are used. Results of real time detection of disturbances and classification of disturbances into momentary, temporary, instantaneous and under voltage or over voltage are done by monitoring system and presented in this paper.

School of Electrical Engineering

2016 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE)

A laboratory set-up for power quality disturbance generator and real time power quality monitoring

In computer vision application object tracking is a challenging problem. Illumination and occlusion are major constraints observed in object tracking. We are focusing on object tracking with partial or full occlusion. Object tracking is done using features like colors and contours. We have proposed a robust Color-based algorithm to track the object and handle occlusion in real time domain. In our algorithm, HSV color model is used and HSV range of the color object to be tracked is selected. Required object area is identified and contour is formed accordingly to track the object. Proposed algorithm is implemented on ARM Cortex-A7 using Open Source Computer Vision (OpenCV) and Linux-embedded platform. The experiment is done using generated real life database and standard unusual crowd activity database. Results showed run time performance, efficiency and accuracy in real time environment. © 2015 IEEE.

12th IEEE International Conference Electronics, Energy, Environment, Communication, Computer, Control: (E3-C3), INDICON 2015

A real-time color-based object tracking and occlusion handling using ARM cortex-A7

Image segmentation for analysis is a major aspect of perception and till date it is challenging issue for machine perception. Many years of study in computer vision prove that segmenting an image into meaningful regions for subsequent processing (e.g., pattern recognition) is just as hard problem as invariant pattern recognition. In this paper, the proposed work uses the different type of procedures has been followed to carry out colour-texture image segmentation. Segmentation methods are designed to integrate more feature information, with high accuracy and satisfactory visual entirety. The segmentation process is based on MSST and student’s t-distribution method.

Proceedings of the International Conference on Inventive Computation Technologies, ICICT 2016

Colour–texture image segmentation based on graph cut using student’s t distribution

Compression, encryption, encoding and modulation at the transmitter side and reverse process at the receiver side are the major processes in any wireless communication system. All these steps were carried out separately before. But, in 1978 R. J. McEliece had proposed the concept of combining security and channel encoding techniques together. Many schemes are proposed by different researchers for this combine approach. Sharing the information securely, but at the same time maintaining acceptable bit error rate in such combine system is difficult. In this paper, a new technique for robust and secure wireless transmission of image combining Turbo Product Code (TPC) with chaotic encryption is proposed. Logistic map is used for chaotic encryption and TPC for channel encoding. Simulation results for this combined system are analyzed and it shows that TPC and chaotic combination gives secure transmission with acceptable data rate.

Proceedings - IEEE International Conference on Information Processing, ICIP 2015

Secure communication using TPC and chaotic encryption

Due to the continuous arrival of plenty of raw data, the big data classification is getting much attention in various fields, such as industry, medicine, and financial business. Due to the urgent need of big data classification in those fields, several standard classifiers are adapted to perform the big data classification, but they are not able to deal with these huge data problems. More commonly, Navie Bayes classifier is mostly preferred for big data classification because of its simple computation procedure. However, the main drawback behind this classifier is the independence hypothesis, in which the input data are conditionally independent of each other. To overcome this drawback, we propose a new classification algorithm using Correlative Naïve Bayes classifier and MapReduce framework (CNB-MRF). Here, the newly proposed correlation function with MapReduce framework is used to make the classification based on the dependent hypothesis to improve the classification performance. Here, the data classification can be easily performed for every new sample through the probability index table of the training data sample and the posterior probability of the testing data samples using MapReduce framework. Then, the classification by the proposed CNB-MRF classifier is performed using localization and skin dataset. It is concluded that, the proposed CNB-MRF classifier achieves a high classification accuracy of 74.77% and 61.35% for localization and skin dataset respectively, as compared with Naïve bayes classifier and MapReduce framework (NB-MRF).

School of Computer Engineering & Technology

International Review on Computers and Software

CNB-MRF: Adapting Correlative Naive Bayes Classifier and MapReduce Framework for Big Data Classification

The incident of fall of elder people increases day by day. Falls are one of the greatest risks for seniors living alone. Sometimes people may get serious injury to the spinal cord and hip region. In such cases, an injured elder people may remain on the ground for several hours after a fall incident has occurred. So there is a need of fall detection system to avoid such incident. This paper propose a novel method to detect falls which combines four features, Orientation angle, ratio of fitted ellipse, Motion Coefficient, Silhouette threshold. These features act as inputs to K-Nearest Neighbor classifier which recognizes fall events. This algorithm gives accuracy above 95% on stored video sequences of activities and real time environment. © 2015 IEEE.

Fall detection using k-nearest neighbor classification for patient monitoring

In recent years due to globalization and increase in competition to capture market share, the customer is having many options of cars at much affordable prices .This has led to tremendous amount of cars on the road. The big cities in India are normally crowded and the city's existing infrastructure falls short to satisfy the growing needs. This problem is also combined with the inefficient use of parking space and uneven distribution of traffic which leads to congestion in vehicular traffic. This paper introduces a novel technique based on Internet of Things platform to improve efficiency of the existing parking systems. It guides driver to find nearest parking slots. The prototype uses cloud based architecture of Internet of things. There is minimum delay in finding an optimal parking slot which helps to ease the traffic congestion. The proposed system also helps users automatically find a free parking space at the smallest distance based on Haversine formula if nearest parking region is full.