population prediction using buildings Computer Vision Project
Updated a year ago
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Metrics
Here are a few use cases for this project:
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Urban Planning: The population prediction model can be employed by urban developers and city planners to estimate population densities in specific areas. This information can be useful when planning infrastructure projects, such as roadways, public transportation, local clinics, schools, and parks.
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Real Estate Development: Real estate developers might use the model to predict potential population inflow in prospective locations. This could impact decisions relating to the size and type of projects to be developed (residential, commercial, mixed-use).
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Public Policy: Government bodies can use the population predictions to decide on policies for various zones in a city or a region. Policies could cover aspects such as resource management, human services, governance structure, and tax rates.
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Emergency Response Planning: The model can help emergency response teams like fire departments, police or paramedics predict which areas might have a high concentration of people at different times, thus positioning them strategically for optimized response times.
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Retailer Expansion Planning: Retail businesses looking to expand their physical stores might find the model useful in predicting areas with a high predicted concentration of potential customers, thus influencing where to establish their next branches.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
population-prediction-using-buildings_dataset,
title = { population prediction using buildings Dataset },
type = { Open Source Dataset },
author = { university of sri jayewardenepura },
howpublished = { \url{ https://universe.roboflow.com/university-of-sri-jayewardenepura/population-prediction-using-buildings } },
url = { https://universe.roboflow.com/university-of-sri-jayewardenepura/population-prediction-using-buildings },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2024-12-01 },
}