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title: Geosensing
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<h1>geosensing</h1>

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<p>The project is about making it easier to collect and analyze geographically distributed data. We showcase the tools with some interesting applications.</a></p>


<h3>Software</h3>
	<ul>
		<li>geo_sampling: Randomly sample locations on the streets. <a href = "https://github.com/geosensing/geo_sampling">Python Package</a> | <a href = "http://geo-sampling.readthedocs.io/">Documentation</a></li>
		<li>allocator: Efficiently collect data from geographically distributed locations. <a href = "https://github.com/geosensing/allocator">Python Package</a> | <a href = "https://allocator.readthedocs.io/">Documentation</a> </li>
	    <li>ybar: Mobile application for crowd sourcing data collection over geographically distributed locations. <a href = "https://github.com/geosensing/ybar">Architecture And Application</a></li>
	    <li>Implementation of Christofides Algorithm in Python for TSP. <a href ="https://github.com/geosensing/Christofides">Script</a>.</li>
	</ul>

<h3>Applications</h3>
	<ul>
		<li>Women count: Missing Women on the streets of Delhi.  <a href = "https://github.com/geosensing/women-count">Project</a></li>
		<li>Street Sense: Learning from Google Street View. <a href = "https://github.com/geosensing/streetsense">Project</a></li>
	</ul>

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