Krishna Chandra Rath

Utkal University

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Sarita Mahapatra

Siksha O Anusandhan University

Satya Ranjan Das

Siksha O Anusandhan University

Jayant K. Routray

Asian Institute of Technology

Srikanta Pattnaik

Siksha O Anusandhan University

Rabiul Ansary

Jawaharlal Nehru University

Narendra Nath Sahoo

Asian Institute of Technology

Pabitra Banik

Indian Statistical Institute

Priyanka Das

University of Dhaka

Srikanta Patnaik

Siksha O Anusandhan University

Kabir Mohan Sethy

Utkal University

Cooperative Institutions

Siksha O Anusandhan University

Asian Institute of Technology

Indian Institute of Technology Bhubaneswar

Utkal University

Jawaharlal Nehru University

Dr. B. R. Ambedkar National Institute of Technology Jalandhar

Central Institute of Plastics Engineering and Technology

Indian Institute of Technology Kharagpur

KIIT University

Indian Statistical Institute

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Issues and Challenges Related to Cloud-Based Traffic Management System: A Brief Survey

Smart innovation, systems and technologies (2020)

Sarita Mahapatra Krishna Chandra Rath Srikanta Pattnaik

Smart City

10.1007/978-981-15-5971-6_47

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Citations (1)

Labour out-migration and Covid-19 Pandemic in India: A case study of Murshidabad district of West Bengal

MIGRATION LETTERS (2021)

Rabiul Ansary Krishna Chandra Rath

This article outlines the patterns of internal migration from Murshidabad district of West Bengal during the Covid-19 Pandemic. We found that seasonal/temporary male migration from the study area has been evolving continuously over time. More than half of the total migrants move within the state boundaries. The inter-state migrants are often destined to economically better off states than the study area. We have shown that landlessness, lack of jobs, low wages, decaying of traditional craftsmanship and household pressure are among the factors leading young males to migrate. These moves are motivated by jobs and income, and movers often shift from agricultural work to building and construction and petty businesses. Migrants and their families are almost exclusively dependent on domestic remittances to meet the household expenditures, repay loans and meet children’s educational expenses. Social networks, especially friends and relatives, are crucial in facilitating the migration process. Covid-19 Pandemic raised essential questions about the future of these vulnerable sections of the population as migration became difficult and remittances dropped significantly.

Pandemic

West bengal

Migrant Workers

Internal migration

Human migration

BENGAL

10.33182/ml.v18i3.1331

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Citations (1)

Precipitation extremes and anomalies of the Indian Sundarban 1984-2018

MAUSAM (2021)

Priyanka Das Pabitra Banik Krishna Chandra Rath

Gridded precipitation data products of 0.5º × 0.5º spatial resolution were analysed to understand the climatic variability in a spatial and temporal context. Data reliability of processed gridded data products were examined in the absence of gauge station data observations in the study area. However, the implementations of comparative analysis of the spatial and temporal data products in this study area are missing. The NASA Power Data (NPD) and Climate Research Unit (CRU TS 4.03) Data were scrutinized from 1984-2018. The data products were selected, compared, and interpreted grid wise. Annual and monsoonal precipitation pattern was also studied. Data variability has been analyzed using the Coefficient of Variation (CV), Anomaly, and Precipitation Concentration Index (PCI). The statistical analysis of R2, MAE, RMSE, MAPE and BIAS was performed to quantify the error and differences. Considering the independent grid point, the MAPE and BIAS indicate that only grid 4 performed better than the rest with 12.7% and 17%, respectively. The results regarding the data products illustrate significant differences both in averaged and grid wise context. The NPD shows an increasing trend, whereas CRU represents a decreasing trend from the year 1984-2018. Before the implementation of any processed secondary gridded data products in complex terrain, the critical evaluation and quantification of the magnitude of error is a prerequisite, like the Sundarbans, where the gauge stationed data is unavailable.

Cru

Anomaly (physics)

10.54302/mausam.v72i4.3552

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Evaluation of the integrated rural development program and its impact on the rural poor (case study of Cuttack District in Eastern India)

Krishna Chandra Rath Jayant K. Routray

Source

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Plot acquisition for self-build housing

Land Use Policy (1997)

Krishna Chandra Rath Jayant K. Routray

Plot (graphics)

10.1016/s0264-8377(96)00031-2

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Citations (5)

Regression-Based Model for Prediction of Road Traffic Congestion: A Case Study of Janpath Segment in Bhubaneswar City

Smart innovation, systems and technologies (2024)

Sarita Mahapatra Srikanta Patnaik Krishna Chandra Rath Kabir Mohan Sethy Satya Ranjan Das

10.1007/978-981-99-9018-4_4

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A GIS and Fuzzy-based Model for Identification and Analysis of Accident Vulnerable Locations in Urban Traffic Management System: A Case Study of Bhubaneswar

International Journal of Advanced Computer Science and Applications (2022)

Sarita Mahapatra Krishna Chandra Rath Satya Ranjan Das

The world has seen road accident and its related societal and economical impact as one of the live, persisting problem in the last 2-3 decades and its prominence has been observed in the developing countries of the Asian subcontinent. With no exception, all major cities in India are facing the various challenges related to road accidents, mostly due to the large population density. Among the major cities in India, Bhubaneswar is a very fast growing city with aim to be the most livable city in Asia in the coming few years. With the city of Bhubaneswar as our study area, we address the issues related to road safety by determining the degree of severity of road accidents. We study the accident related data collected for the last decade using the spatial tools of Geographical Information System (GIS). Then using a GIS-map based analysis and a fuzzy-based model, we have found the spatio-temporal distribution of accident vulnerable locations with their degree of severity. Our experimental results show the accident hot-spots with values of selected contributing parameters such as timing, traffic density, vehicle speed, road intersections.

Accident (philosophy)

10.14569/ijacsa.2022.0130881

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Regression based neural network model for prediction of road traffic congestion : A case study of Bhubaneswar

Journal of Statistics and Management Systems (2023)

Sarita Mahapatra Krishna Chandra Rath Srikanta Pattnaik

The prediction of road traffic congestion is the most important and essential aspect to reduce the suffering of population of urban cities which is primarily carried by roads. The lack of a traffic congestion data unavailability and evaluation standard makes the effect of traffic congestion prediction more difficult and worsen. Traffic congestion occurs due to increase in number of vehicles on roads which reduces speed of vehicles, increases delay time, and increasing vehicular queuing in traffic. Due to traffic congestion, not only delaying time increases but also its threat to slower down the economic growth rate of our country and also have high impact on our personal growth, living condition with high level of pollution and undesirable feature of overloaded streets. Traffic congestion predicting modeling plays very important role so we need a innovative approach to predicting the congestion on roads. In this paper, we aim to provide a model which studies the real time environment characteristics of the road, and analyzed the data, congestion location identification, directional movement of all those locations surveyed and forecasting traffic location where traffic congestion may occur in near future.

Unavailability

10.47974/jsms-951

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Growth, development and planning of Bhubaneswar

Cities (1996)

Jayant K. Routray Krishna Chandra Rath Narendra Nath Sahoo

Sculpture

Capital (architecture)

Independence

10.1016/0264-2751(95)00128-x

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Citations (6)

GIS and Cloud Based Model for Urban Parking Management: A Case Study of Bhubaneswar

Sarita Mahapatra Krishna Chandra Rath Satya Ranjan Das

Nearly every major cities like metropolitan and tourist areas of India, the vehicle parking rate increases rapidly which lead to problem of traffic congestion and accidents. So it becomes an important aspect to make a study and develop a system by using suitable technology for finding available parking lots and provide information of parking space at public and private places. Wrong parking of vehicle at different places in roads increases the waiting time in the peak hours. To deal with this problem, we address the issues after analyzing parking needs and then using Geographic Information System(GIS) tool, we develop a smart parking system using cloud computing and Internet-of-Thing (IOT) technology to answer all parking uncertainties. In this paper, we propose a model for network architecture based on IOT and cloud technology. This proposed system helps to automatically find the free parking space in near distance with minimal cost based on the distance and availability of free space in parking units.

Parking space

Smart City

10.1109/mlcss57186.2022.00029

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