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Case Study

Consumer’s Acceptance to Green Building Concept for Sustainable Construction in India

The changing consumer demands for eco-friendly products and services in all industrial sectors have paved way for constant growth and development of the real estate sector, especially in Delhi-NCR. The growing interest towards green products in real estate can be attributed to the fact that quality of air is decreasing day by day. According to few reports, buildings consume more than 30% of energy utilizing 40% of resources while simultaneously generating 40% of wastes and 35% of harmful greenhouse gases. So this study is focused on consumer’s acceptance and willingness to pay more for green building products in Delhi-NCR. For the purpose of the study 150 commercial property owners were contacted to identify the factors stimulating them to pay premium prices for sustainable buildings over conventional buildings. From the results, it was found that environmental attitude, green awareness, architectural factors and social influence significantly influence the customer willingness to pay higher prices for green buildings. Social Influence is the strongest factor that has positively influenced the customer inner will to pay premium prices for green buildings. The research also provides an in-depth understanding of factors stimulating customers to go green in the context of construction industry specifically in Delhi-NCR region.

Published by: Ankit Kumar Jat, Prithviraj Dilip Mane

Author: Ankit Kumar Jat

Paper ID: V4I1-1163

Paper Status: published

Published: January 6, 2018

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Research Paper

Analysis and Design of Multistorey Building G+4

A multi-storey is a building that has multiple floors above the ground. It can be a residential or commercial building. in this project the analysis and design of multi-storey building G+4. In general the analysis of multi-storey is elaborate and rigorous because those are statically indeterminate structures. Shears and moments due to different loading conditions are determined by many methods such as portal method, moment distribution method and matrix method. The present project deals with the analysis of a G+4 building. The dead load & live loads are applied and the design for beams, columns, footing is obtained Manually. The Analysis part of the structure is done using Kani’s Method and the values are taken for design.

Published by: Mohd Zohair, K. Mounika Reddy

Author: Mohd Zohair

Paper ID: V4I1-1153

Paper Status: published

Published: January 6, 2018

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Research Paper

Energy Aware Node Mobility Prediction in Mobile Adhoc Networks

The analysis of human location histories is currently getting an increasing attention, due to the widespread usage of geopositioning technologies such as the GPS, and as well as online location-based services that allow users to share this information. Tasks such as the prediction of person’s movement can be addressed through the usage of this data, in order for offering support for more privileged applications, such as adaptive mobile services through proactive context-based functions. Here we aim to develop a simple and effective scheme to predict when the user will leave the current location and where he will move to future position. This paper presents a hybrid method for predicting human mobility on the basis of Mobility Markov Chain Models (MMCs). The proposed approach clusters location histories according to their characteristics, and later trains the MMC model based on mobility history to obtain transition matrix. The usage of MMC allows us to take information of location characteristics as parameters, and also to account for the effects of each individual’s previous actions. The proposed system is a mobility prediction with adaptive duty cycling approach in reducing energy consumption, with a mobility model called Mobility Markov Chain (MMC) for predicting the future location. We report a series of experiments with a real-world location history dataset and from the LifeMap dataset, showing that the prediction accuracy is in the range of 65 to 85 percent.

Published by: Ram S. Kale

Author: Ram S. Kale

Paper ID: V4I1-1165

Paper Status: published

Published: January 6, 2018

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Survey Report

A Literature Survey on Smart Home Automation Security

This paper presents a detailed description of different technologies and home automation systems from a security point of view. This paper highlights various security flaws in existing home automation systems and how the concept of security and the meaning of the word “intruder” have evolved over time.  We studied the challenges in home automation security from point of view of home owner and security provider. This work considers home automation systems like central controller based home automation systems, context-aware home automation systems, Bluetooth-based home automation systems, Short Messaging Service-based home automation systems, Global System for Mobile communication or mobile-based home automation systems, and Internet-based home automation systems. The work is concluded by giving future directions home automation Security Research.

Published by: Rohit Ragmahale

Author: Rohit Ragmahale

Paper ID: V4I1-1160

Paper Status: published

Published: January 5, 2018

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Research Paper

Automatic Feature Selection from EHR & DNN Modeling

Recently there are a lot of advancements in healthcare technology. Amongst, Electronic Health Record (EHR) is an upcoming trend which stores patients’ demographics, lab tests & results, medical history, habits etc. collaborated in electronic form. EHR is huge data, which is difficult to maintain and retrieve. So the idea of health risk prediction is formulated in this work. To get the relevant data from EHR, feature selection technique is used. Feature selection is responsible to collect only important and needed data from the dataset. For feature selection regression method is used in which loss function is proposed due to which accuracy and performance of the model are increased. Further risk prediction is done using neural network model. Deep Neural Network (DNN) is best suited for pattern learning and prediction purpose. It consists of various layers which have their specific function. DNN uses transfer learning to avoid repeated training for the whole system. Dataset considered here is of hypertension. EHR data is also synthetically created for analysis.

Published by: Shreyal Gajare, Shilpa Sonawani

Author: Shreyal Gajare

Paper ID: V4I1-1159

Paper Status: published

Published: January 5, 2018

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Research Paper

Calibration of MQ-7 and Detection of Hazardous Carbon Mono-oxide Concentration in Test Canister

The most active research in recent years is estimating the noxious waste which has a very high influence on the human health. There are many gases which have adverse effects on human health. Here carbon monoxide(CO) is considered as one of toxic gas which is considered to cause various health issues based on the concentration the casualty is exposed. In this paper, we ensure the presence of hazardous gases and also provide the procedure to estimate the concentration of the same with the help of the MQ-7 sensor and test setup. The calibration of the sensor is carried out with a canister of known volume and the estimation of the CO in the test environment is also determined.

Published by: K. Senthil Babu, Dr. C. Nagaraja

Author: K. Senthil Babu

Paper ID: V4I1-1145

Paper Status: published

Published: January 4, 2018

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