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README.MD

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 ## Introduction
 Our project idea of creating a smart dashboard to explore the connection between traffic collisions and other factors like average daily traffic counts and street speed limits in Seattle is a compelling approach to addressing urban mobility and safety issues. This dashboard aims to provide a comprehensive view of how various factors interplay to affect traffic conditions, potentially leading to collisions. Let's go deeper into the functionalities and benefits of such a dashboard.
 
-**Interactive Heatmaps for Collision Data**
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+### Interactive Heatmaps for Collision Data
 The use of heatmaps is an effective way to visualize high-density areas of traffic collisions. Users can quickly identify hotspots where accidents frequently occur. This visual tool can be interactive, allowing users to zoom in or out and click on specific areas for detailed statistics, such as the number of collisions, time of day when most accidents happen, and possible causes. This immediate, visual representation makes it easier for city planners, traffic authorities, and the general public to understand where interventions are most needed.
 
-**Data-Driven Decision Making**
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+### Data-Driven Decision Making
 The dashboard can serve as a powerful tool for data-driven decision-making. By analyzing the correlation between traffic collisions and other factors, city planners can make informed decisions on where to implement safety measures such as speed bumps, traffic lights, or enhanced signage. Furthermore, this analysis can guide infrastructure improvements, like road widening or the creation of pedestrian zones, to enhance overall traffic safety and efficiency.
 
-**Real-Time Updates and Predictive Analytics**
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+## Real-Time Updates and Predictive Analytics
 Incorporating real-time data feeds into the dashboard can provide users with up-to-date information on traffic conditions and collision occurrences. This feature is particularly useful for emergency response teams and daily commuters. Additionally, integrating predictive analytics can forecast potential collision hotspots based on historical data and current trends. This foresight can be instrumental in preemptive measures to reduce traffic collisions.
 
-Here is our project's visualization:
+**Here is our project's visualization:**
 [Interactive Map](https://noah-rarick.github.io/seattle-collisions-v2/)
 
 ## Project Process
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 A central feature displaying a geographical map of Seattle, where users can pan and zoom to explore different areas. Tools like zoom in/out, pan, and reset view options to navigate the map easily. Heatmap layer is used for visual representation of traffic collision data, with areas of higher collision frequencies shown in warmer colors (e.g., red) and lower frequencies in cooler colors (e.g., blue). Semantic layers are used for toggleable layers that overlay additional information on the map, such as street speed limits and average daily traffic counts, possibly using icons or color-coded lines. The dashboard also includes real-time data, indicators or markers for recent collisions or traffic flow status could be present. We allow users to provide feedback on the dashboard's functionality, report errors, or suggest improvements. Users can also customize options to adjust map views, data layers displayed, and notification preferences.
 
 ![Visualzing Analytics](https://github.com/noah-rarick/seattle-collisions-v2/blob/main/img/Map3.png)
+
 In Analytics bar, we can see the details of number of collisions and number of injuries of each area we chose. The statistics and analytics will change when we choose different areas and will also keep updating with updating datasets.