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Public Perception of Traffic Management and Environmental Sustainability under the Smart City Mission: A Statistical and Machine Learning-Based Analysis |
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PP: 789-802 |
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doi:10.18576/jsap/150329
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Author(s) |
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Palavi Rajput,
Danish Gulzar,
Deepak Sharma,
Mohammed Osman Eltigani,
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Abstract |
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| This study explores public perceptions of traffic management and environmental sustainability under India’s Smart City Mission, with a focus on Jammu and Srinagar. Based on 101 respondents and using descriptive statistics, chi-square tests and machine learning models (Decision Tree and Random Forest), the study uses survey data. Findings indicate that most respondents assess traffic as average to good, but frequently experience congestion and moderate to high levels of concern about environmental issues. A strong association was found between age and congestion frequency; other relationships were not statistically significant. Machine learning models have low predictive accuracy but reveal factors that significantly influence prediction. The study highlights the importance of integrating citizen feedback with data-driven approaches for sustainable urban traffic planning and policy development. |
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