2024 Hampton Roads Datathon

Access4All: A Data Collection and Analysis Tool for Curb Ramp ADA Compliance

SenseLane Team: Junqing Wang, Zizheng Yan, Yang Liu, Hong Yang,

Department of Electrical and Computer Engineering, Old Dominion University

Introduction

Accessible pedestrian infrastructure is a fundamental but critical need for creating equitable and inclusive urban environments that serve all members of our community. In particular, curb ramps play a crucial role in ensuring safety and accessibility for travelers with disabilities, elderly pedestrians, parents with strollers, and other users with mobility challenges. The Americans with Disabilities Act (ADA) creates specific standards 1  for curb ramp design and installation, yet many of our existing roadway infrastructure systems fail to meet these requirements, bringing significant mobility barriers to vulnerable road users. This project aims to develop a web-based tool (i.e., Access4All) that integrates artificial intelligence (AI) technologies and geospatial analytics to facilitate scalable data collection efforts for locating existing curb ramps in the City of Norfolk and evaluate accessibility based on the collected and other associated socioeconomic and infrastructure data at different analysis units. It intends to propose an efficient and streamlined data-driven solution for collecting and analyzing ADA-compliant curb ramp data, which can inform infrastructure improvement decisions and promote equitable access throughout urban areas. 

Access4All: Curb Ramp Data Collection

Access4All is equipped with a systematic multi-step approach combining geospatial processing and analytics, remote sensing, and AI-based object detection technologies. Figure 1 provides a high-level illustration of the developed tool. Initially, the road network shapefile of Norfolk was obtained through the city’s public data source2, and then the geospatial processing was conducted to identify all intersections at the city-wide level. Each identified intersection was then assigned a unique identifier and corresponding coordinates. Using these coordinates, high-resolution aerial imageries were acquired through the Google Maps API for each intersection. Then, a well-trained AI-based detection model was deployed to automatically detect and classify curb ramps within these intersection images. To ensure data quality (e.g., accuracy and completeness), an interactive review and editing component was also incorporated in Access4All.

Harnessing the Power of Access4All to Improve Accessibility

The Access4All also integrates an interactive visualization and analysis component to enable further spatial analysis and applications based on the collected curb ramp data, illustrated in Figure 2. Users can select specific areas of interest within the City of Norfolk, showing dynamic displays of intersection data with color-coded markers indicating the number of curb ramps at each location. For specific applications, a city-scale analysis was conducted at the census tract level, utilizing heatmap visualizations to display curb ramp density. Additionally, the accessibilities of public transit stops and public libraries were also assessed as examples to show the potential of our Access4All.

Practical Applications and Future Efforts

The Access4All data collection and analysis tool developed in this project, while initially focused on the City of Norfolk, demonstrates its scalability potential for analyzing curb ramp accessibility across the entire Hampton Roads region and beyond. It facilitates project prioritization (e.g., populated areas with few curb ramps) of installing/maintaining curb ramps to achieve ADA compliance, and infrastructure asset inventory and management. Looking ahead, the developed tool and datasets will be further enhanced by including additional functionalities and elements, such as modules capturing crosswalks. It will also be extended to develop a dataset covering areas of interest in the Commonwealth of Virginia and the country to support data-driven decision-making and resource allocations for accessibility improvements.

1 https://archive.ada.gov/pcatoolkit/chap6toolkit.htm

2 https://data.norfolk.gov/stories/s/6px2-wzep

For more information, please contact: hyang@odu.edu

Team: Can-Do

Project Title: Waste Management: How to Be a Trendsetter

Summary:

Trendsetting Reimagining Automation Servicing Homes

Trash meets treasure! The City of Norfolk needs to be on the forefront as a trendsetter within our communities.  To our citizens we say, “We hear you, our job is you”.   We as a city are all about involvement, engagement, and collaboration. Part of doing our job involves promoting local businesses that align to citizen services requests.  We feel we can do this by capitalizing on an untapped niche in marketing.   

We Can-Do more, tooting our own horns figuratively and literally.  Daily we touch lives at unprecedented levels. Nearly every day, refuse collection trucks drive through neighborhoods and city streets. Why not use the trucks as a form of passive advertising? As businesses thrive, the city thrives.   As the city has grown, we have grown with it.  Our trucks slow down and empty containers to over 66,000 locations a week which equates to 792,000 collections yearly- our market reach is massive!  Unlike so many marketing mediums that are nearly extinct (like newspaper and local radio), let’s capitalize on the advertising space that will not disappear- the City of Norfolk refuse collection trucks.  

Authored By: Ayngaran Krishnamurthy & Roshni Gannoju 

INTRODUCTION

Urban green spaces like parks and recreational areas play a crucial role in improving mental health by reducing stress, anxiety, and depression. In Hampton Roads, where urbanization continues to expand, access to these spaces is uneven, particularly in densely populated or low-income neighborhoods. Our study seeks to analyze the correlation between exposure to green spaces and mental health outcomes, focusing on how limited access to parks can elevate the risk of depression and other mental health issues. 

OBJECTIVE

Our study explores the impact of green space accessibility on mental health, aiming to shed light on how access to parks influences mental health outcomes such as depression and anxiety. Research consistently shows that individuals who live near parks experience better mental health, while those in areas with limited access face increased mental distress. In particular, our study emphasizes the underexplored relationship between urban green spaces and mental health, providing valuable insights for urban planners and public health officials. By demonstrating the tangible benefits of green space exposure, we hope to raise awareness about the necessity of integrating parks into future urban development strategies, especially in regions with low access to green spaces. 

APPROACH

We used four datasets to analyze the impact of green space accessibility on mental health in Hampton Roads:

1. Hampton Roads 2020 Census Tracts (Redistricting): This dataset provides insights into the demographic distribution of the Hampton Roads population, helping us identify areas with high population density and limited green space access.
2. Hampton Roads Public Parks (2024): This dataset catalogs public parks across the region. By overlaying the park locations with census data, we identified communities with inadequate access to green spaces.

3. Percent of Adults with Frequent Mental Distress (County Health Rankings, 2022): This dataset offers insights into the mental health of residents, focusing on areas where people report experiencing frequent mental distress (defined as 14 or more days of poor mental health per month). These areas were compared to their access to parks.

4. Why We Need More Nature at Work: This study examines the effects of natural elements and sunlight exposure on employee mental health. It highlights how nature in professional settings (e.g., sunlight, greenery) can reduce stress and improve mood, further supporting the idea that exposure to green spaces—whether in residential or workplace settings—is essential for mental well-being.

SELF-STUDY: THE IMPACT OF PARK EXPOSURE ON OUR DAILY ROUTINE 

Objective: To experience firsthand the effects of park exposure versus no exposure, helping us better understand the benefits we advocate for in our green space research. 

Number of Subjects: 2 

Daily Routine: 

• Work: 4 hours (9:00 AM to 1:00 PM)
• Classes: 1:15 PM to 4:00 PM
• Gym: 1 hour
• Study/Assignments: 2-3 hours

Study Design:

1.    Park Exposure (First 3 Days):

For three days, we integrated breaks at ODU Turtle Pond. This led to noticeable improvements in:

o    Mood: Increased focus and productivity during work.

o    Stamina: Improved gym performance (e.g., running 5.8 km versus 5 km without a break).

2.    Non-Exposure (Following Days):

Without park exposure, mood levels dropped, work motivation declined, and gym stamina decreased. These results further validated the positive mental health impact of green space exposure.

CONCLUSION

This study underscores the importance of urban green spaces for fostering better mental health outcomes. Whether at home or in the workplace, access to natural elements like parks, greenery, and sunlight is critical for reducing anxiety, depression, and stress. Hampton Roads must prioritize the incorporation of green spaces into urban planning strategies to ensure that all communities have equal access to nature’s benefits. Green spaces should be regarded as integral to both public health infrastructure and urban development plans, creating a healthier and more resilient community. 

In our analysis, we investigate how infrastructure-related factors influence traffic crashes within the City of Norfolk’s jurisdiction. Specifically, we explore types of intersections, road types, and road defects in these events. This focus on these road-related factors allows us to identify problems in transportation infrastructure to identify effective preventative measures the area can take to reduce roadway risk. Reduced roadway risk most importantly saves lives, but it also reduces material costs associated with crash damage and cleanup.

To analyze the data, we used a Python script utilizing Pandas for data parsing and Matplotlib for plotting. To avoid spending most of our project time searching documentation and so that we could focus on the data analysis itself, we used ChatGPT4o to help construct pandas queries to structure the data and to come up with quick plotting skeletons.

Since crash frequency is correlated with road use, we instead decided to examine the ratio of serious and fatal crashes to the overall total crashes as our dependent factor. Severe crashes, as defined by the KABCO injury scale, mean that the individuals involved needed help from the scene. The injuries often include severe lacerations, broken or distorted limbs, abdominal injuries, or unconsciousness. By using a ratio rather than a total count, we could account for data unbalance, such as the high number of conventional intersections compared to roundabouts.

Within the dataset, a positive correlation was seen regarding severe crashes and intersection types. Specifically, intersections with five or more points show the highest ratio of severe crashes, while roundabouts, designed to improve traffic congestion, have none. This suggests that roundabouts play a critical role in road safety and accident severity, especially if they are implemented on a wider scale.

Two-way intersections with unprotected medians also show a high ratio of severe/fatal crashes to the total amount of crashes. This data suggests that while medians help cars stay on the road and avoid objects around the interstate, the downside is that without them, the likelihood of severe crashes occurs. This finding highlights the importance of median protection for infrastructure, which can help control traffic flow and reduce human risk.

Road defects also played a significant role in the data regarding severe crashes. Loose materials, such as gravel or debris, are common contributing factors that can cause drivers to lose control, particularly at high speeds. This hazard leads to infrastructure strain due to accidents blocking and slowing down traffic.

Our data suggests that some specific direct structural changes may work towards lowering crash severity and infrastructure strain. Constructing more roundabouts and adding more median barriers may lower the severity of crashes in the areas they are built. Road debris is a more challenging issue, but one suggestion is implementing hazard detection. Some roadways have installed traffic monitoring cameras, allowing to detect traffic, speed, and accidents, and we posit that these cameras might be used to detect objects in the roadway.

By taking preventative action, we can reduce both the risk of accidents and the strain on infrastructure from crashes and disruptions. By identifying the causes of major accidents, we can pinpoint factors they share and create a solution to reduce the number of total accidents that occur. These measures will reduce injury and save lives, as well as reduce taxpayer dollars spent on accident cleanup and EMS services.

The City of Virginia Beach Team is analyzing the Traffic Congestion on Ferrell Parkway (Westbound) and focusing on reducing congestion and improving the flow of traffic on Ferrell Parkway towards Indian River Road. Over the span of the past few years, drivers have experienced significant traffic delays during peak hours. This causes an increase in travel time in drivers’ commutes, as travel time during peak hours triple. 

To address this issue, the project aims to expand the westbound section of Ferrell Parkway by adding a lane, which will aid in reduced congestion and improve travel time and fuel efficiency for drivers. The additional lane will not only benefit drivers, but the environment as well because of the reduction in emissions. 

During our data analysis, we analyzed data of the traffic count on the westbound and eastbound lanes on Ferrell Parkway to discover the trends in time and vehicles. We were able to successfully identify the increase in traffic at peak hours of 7 A.M. and 4 P.M. during weekdays and 1:00 P.M on weekends. It was also noted that the westbound lanes on Ferrell Parkway experience significantly more traffic than eastbound lanes. 

By implementing this lane, the City of Virginia Beach can begin to relieve that traffic congestion that leads to increased travel times, fuel consumption and emissions. Ultimately, this proposal highlights an area for infrastructure improvements within the City of Virginia Beach. 

"Third spaces are for us to see and explore; low or no cost to get in the door.  So many things to see and do; the only thing Norfolk is missing is you!"

What is the problem?

Third spaces are closing, becoming inaccessible or uninviting at an alarming rate, and people are becoming increasingly isolated. In a post-COVID world, consumers are more budget conscious. As we transition to a more digital society, we ironically struggle to stay connected.  

What is a third space?  

Third spaces are typically low or no cost locations in a community (like a church, park, community center, library, the mall, bars and restaurants, ice cream parlor, or a coffee shop) Norfolk has many community centers and public resources that are expensive (utilities & staffing) to maintain and are underutilized (as we see based on the usage statistics). 

Norfolk public spaces also have a poor reputation, bad operating hours, and are often not providing the programming or facility elements that their communities need  

(based on resident survey) - Especially for those from underserved communities: 

(low or no transportation, low to moderate income, difficult schedules, language barriers, etc) 

What is our proposed solution?

Introducing "Dive-In HR"  

Dive-in HR is a comprehensive mobile application or browser-based community engagement tool which aims to showcase hyperlocal (up to 1 mile) upcoming events (7-30 days) based on the location the user selects, and their interests. In the first edition, users will be able to see events at libraries and community centers, green spaces and waterfront areas. 

Future versions of this application will allow community members to submit their own third spaces. Applications for new third spaces must meet and display particular information such as proximity to a transportation route, language access options, ADA compliance, costs associated, and descriptive features about who this space serves and what audiences they want to capture. 

Digital access or print versions will be available at participating community centers or libraries for those without internet or smartphones. To further engage the community that this aims to serve, “challenges” will be launched based on the location type to encourage users to visit specific locations. As users participate in challenges, they will also have the opportunity to provide critical feedback regarding the location they are in. For those who complete challenges, prizes will be awarded to celebrate users for their engagement. Example prizes include stickers or pins, virtual badges or engagement tiers, and participating location incentives like half-off products, or other free items. 

This application’s purpose is to improve space utility, increase access / visibility to service areas of need, engage the community, build trust, and improve hyper local community well-being.  

Ensuring Fair Access to Emergency Infrastructure Amid Growing Climate Vulnerabilities

Members:  Wai Yan Siu (ODU), Trang Le (ODU), Audrey Douglas-Cooke (NSU), Abdul Mustafazade (ODU), Deepta Tejasa Vuppalapaty (ODU), and Priscilla Cook (ODU)

Link to project

Background:

Timely access to emergency services is vital for Hampton Roads. Expedient care, at Level 1 trauma centers, can reduce mortality by 25%. Norfolk, VA, has two acute care hospitals: Sentara Leigh Hospital (SLH) and Sentara Norfolk General Hospital (SNGH) - the region’s only Level 1 Trauma Center. It is important to evaluate Norfolk’s infrastructure to ensure Emergency Medical Services (EMS) have ease in accessibility, preventing any unnecessary delays. Infrastructure planning is challenging because future needs and actual usage are difficult to predict before implementation. In Hampton Roads, climate change has heightened risks, as evidenced by severe flooding due to rising sea levels and sinking land. The impact of climate change on the infrastructure in Hampton Roads makes access to emergency facilities more critical and exacerbates disparities among communities.

Data:

To determine if Norfolk’s infrastructure impedes timely access to its acute care hospitals, we used publicly available data and collected travel time and distance across Norfolk that factored in distance, speed limit, real-time, and historical traffic data, generated using Graph Neural Networks. We also evaluated access during flood events using geospatial analysis and Space Syntax to identify impacted roads and communities. We provided a travel cost estimate based on actual travel times and emergency department visit rates from the CDC to offer budgetary guidance for improving Norfolk’s Road infrastructure and creating equal access to emergency services. 

Policy Implications:

We found that travel time can vary significantly --- by as much as 350% --- from 6 minutes in the nearest community to 27 minutes in the furthest. This raises the question of how the original planning decision was made relative to the reality of what is occurring now. Unsurprisingly, we found that discrepancy is as large as 83%. During flooding events, our analysis showed travel routes to Norfolk’s only Level 1 Trauma Center, SNGH, were disrupted. This caused increased travel time for the northern and northwestern communities. We identified the vulnerable communities in terms of access to emergency services were Zip codes 23502, 23503, and 23513. This was due to longer travel times and larger populations, highlighting the need for improved road infrastructure in these areas.  

Virginia Zamponi, Kevin O’Brien, Jessica O’Brien, Erik Jensen, Christopher Lynch, and Ross Gore

OERI / VMASC @ ODU

BACKGROUND

Resilient hurricane evacuation routes are crucial for protecting lives and ensuring public safety. They must withstand challenges such as flooding from fast-moving storms, cyber-attacks that could compromise bridge accessibility, and traffic disruptions due to collisions. We offer an interactive online platform for decision-makers to evaluate the resilience of the Hampton Roads Hurricane Evacuation Routes against these scenarios. Our project utilizes local data on FEMA evacuation zones, potential cyber threats to bridges, and traffic patterns from accidents to create a Bayesian network representation of the evacuation routes. This allows us to simulate and quantify how well the routes can remain operational under different hazards. The insights gained from this analysis are actionable; they enable emergency responders to strategically position resources based on identified vulnerabilities and direct funding towards strengthening critical infrastructure, ultimately enhancing the overall evacuation strategy. 

DATA AND DEFINITIONS

The evacuation route system's resilience is defined as the percentage of simulations where all four Hampton Roads areas maintain at least one completely unobstructed evacuation route. Key data sources include: (1) Hampton Roads Evacuation Zones and Routes GIS files; (2) CVE and CVSS data on cyber exploit probabilities; (3) MITRE ATT&CK data on known threat group capabilities; (3) ChatGPT-generated conditional probabilities of traffic disruptions within the route system. This method enables comparison of three hurricane evacuation scenarios against a baseline, quantifying changes in route resilience. 

METHODS

Using the VDEM Hampton Roads Hurricane Evacuation Route Map (left) we constructed a Bayesian Network. The network is built on a web accessible platform we created to enable decision makers in the area to rapidly modify and review changes to the evacuation routes. Next, we simulated a baseline scenario for the resilience of the routes (center). Then, using the collected data we simulated three different scenarios: (1) possible flooding, (2) a cyber-attack on draw, swing and lift bridges (center), and (3) possible traffic break during the evacuation due to automobile collisions. 

RESULTS

The figure demonstrates how evacuation route resilience can be drastically reduced when considering cyber threats, particularly those targeting draw, swing, and lift bridges. Our model examines a potential attack by Russian state-sponsored Sandworm exploiting CVE-2022-1161, a vulnerability in bridge control system PLCs. This scenario is plausible given Sandworm's history of targeting industrial control systems and the overlap between their techniques and the technical expertise required to exploit CVE-2022-1161. Combining the cyber data sources, we estimate an 83% chance of success on a given bridge. The figure shows the attack decreases evacuation system resilience from 100 (extremely resilient) to 30.30 (significantly compromised resilience) due to increased likelihood of impassable bridges in Norfolk/VA Beach and Peninsula routes. To mitigate risks, alternative routes or nearby shelters should be identified and publicized. 

Team- Twin Sparks from ODU

Project title- Turning the Tide: Leveraging Green Infrastructure Solutions to Address

Coastal Flooding in the Hampton Roads

Hampton Roads is increasingly threatened by climate change, resulting in coastal flooding and wetland loss. These issues endanger local ecosystems, infrastructure, and public health, necessitating innovative green infrastructure solutions.

Our project focuses on raising awareness of these challenges, promoting eco-friendly rain gardens, engaging the community, and providing an interactive planning tool. Rain gardens absorb excess stormwater, reducing runoff by up to 50% and removing up to 90% of pollutants. They enhance water quality and restore wetland functions while being cost-effective, space-efficient, and low-maintenance, with targeted support for vulnerable populations.

GardenMe HRGP is our key initiative—an interactive online tool designed as a rain garden planner and impact simulator. It allows residents to visualize their properties, design rain gardens, and simulate their effects on flooding, all through a user-friendly, mobile-compatible platform.

Using a variety of data sources, we are able to gain both informative and actionable insights for residents and policymakers. Additionally, we will analyze data by overlaying flooding scenarios with land use data to identify optimal rain garden locations and garden features, and calculate their potential impact on runoff reduction.

Through real-time data visualizations and community involvement, "Turning the Tide" aims to empower Hampton Roads residents to adopt sustainable practices and build resilience against climate change challenges.