SMART PARKING SPACE

[Audio] Smart Parking Space App – Data-Driven Recommendation Ronald Sweatman University of Phoenix FIN/571 John Delenger 09/16/2025.

[Audio] Project Rationale and Goals Now that we've established the project's goals, let's turn to the data. We'll start by examining occupancy patterns across different days of the week to see how demand fluctuates..

[Audio] Rationale for Smart Parking Initiative Parking Congestion Issues Urban parking congestion causes increased driving time, higher emissions, and driver frustration during peak hours. Smart Parking Benefits Smart parking apps provide real-time space availability, guiding drivers to underutilized lots efficiently. Dynamic Pricing and Efficiency Dynamic pricing helps manage demand, improving operational efficiency and reducing traffic congestion. Alignment with Smart City Goals The initiative supports sustainability and data-driven decisions, enhancing urban quality of life. Urban areas face significant challenges related to parking congestion, which leads to increased circulation time, higher emissions, and driver frustration. Data from the week of November 20–26, 2022, shows that certain lots, particularly Lots 7 and 9, frequently operate near or at full capacity during peak hours. This creates inefficiencies and environmental impacts as drivers spend additional time searching for available spaces. A smart parking application can mitigate these issues by providing real-time availability, guiding drivers to underutilized lots, and enabling dynamic pricing to manage demand. The rationale for this project is grounded in improving operational efficiency, reducing traffic congestion, and enhancing the overall user experience for residents and visitors. Implementing such technology aligns with smart city principles, which emphasize sustainability, data-driven decision-making, and improved quality of life through innovative solutions..

[Audio] Goals of the Smart Parking Project Analyze Occupancy Patterns Analyze parking occupancy rates by day and lot to understand demand variability and trends clearly. Identify Peak Congestion Times Examine time-specific parking patterns for Lots 7 and 9 to pinpoint periods of severe congestion. Phased App Rollout Implement a smart parking app with real-time guidance, dynamic pricing, and enforcement integration in stages. Establish KPIs for Success Define KPIs like reduced curb-to-space time and shifts in demand to measure project effectiveness. The primary goals of the smart parking initiative are to visualize current occupancy patterns, identify peak usage periods, and recommend actionable strategies for implementation. Specifically, the project aims to: (1) analyze occupancy rates by day and by lot to understand variability and demand trends; (2) examine time-dependent patterns for Lots 7 and 9 to determine when congestion is most severe; (3) propose a phased rollout of a smart parking application that includes real-time guidance, dynamic pricing, and enforcement integration; and (4) establish key performance indicators (KPIs) to measure success, such as reductions in curb-to-space time and shifts in demand from saturated lots to underutilized ones. These goals support a data-driven approach to urban mobility, ensuring that resources are allocated effectively and that the city can achieve measurable improvements in traffic flow and environmental impact..

[Audio] Data Analysis and Visualization Now that we've established the project's goals, let's turn to the data. We'll start by examining occupancy patterns across different days of the week to see how demand fluctuates..

[Audio] Box Plot Analysis by Day of Week Day Median Occupancy (%) Variability Sunday Low Narrow spread Monday Moderate Consistent Tuesday High Upper quartile near saturation Wednesday High Similar to Tuesday Thursday High Stable Friday High Widest spread Saturday Moderate Variable, late-morning peak The box plot analysis of occupancy rates by day of the week reveals clear patterns in parking demand. Weekdays, particularly Tuesday through Thursday, exhibit higher median occupancy rates compared to weekends, with upper quartiles approaching saturation levels. Friday shows the widest spread, indicating variability in demand, possibly due to mixed work and leisure activities. Saturday demonstrates a late-morning increase with significant variability toward mid-afternoon, suggesting fluctuating usage patterns. These insights confirm that parking demand is strongly time-dependent and influenced by day-specific behaviors. Understanding these trends is critical for designing interventions such as dynamic pricing or targeted notifications during peak periods. By leveraging this data, the city can anticipate congestion and proactively manage resources to optimize parking availability and reduce circulation time..

[Audio] Box Plot Analysis by Parking Lot Lot Median Occupancy (%) Peak Occupancy (%) Lot07 High >90% Lot09 High >90% Lot03–06 Moderate Below 70% The box plot analysis by parking lot highlights significant disparities in usage across the city's facilities. Lots 7 and 9 consistently operate near capacity during peak hours, with upper quartiles exceeding 90% occupancy. This indicates that these lots are critical pressure points in the system and require targeted interventions. Conversely, other lots, such as Lots 3 through 6, show lower median occupancy rates and greater availability, suggesting opportunities to redistribute demand through real-time guidance and wayfinding. The variability observed across lots underscores the potential benefits of a smart parking solution that dynamically directs drivers to underutilized spaces, thereby reducing congestion and improving overall efficiency. These findings provide a strong foundation for prioritizing Lots 7 and 9 in the initial phase of the smart parking app rollout..

[Audio] Data Analysis and Visualization After looking at overall occupancy trends, it's important to zoom in on specific lots. The next slide focuses on Lot 7, where time-dependent patterns reveal critical insights about congestion..

[Audio] Scatter Plot Analysis for Lot 7 Time-Dependent Occupancy Pattern Occupancy rates sharply increase in the morning, peaking around 11:00 AM at approximately 95%. Peak Occupancy and Congestion Maximum occupancy reached 100%, and 95th percentile near saturation confirms frequent congestion. Smart Parking Strategies Real-time updates, dynamic pricing, and driver notifications can reduce congestion effectively. The scatter plot for Lot 7 demonstrates a clear time-dependent pattern in occupancy rates. Data indicates a rapid increase in occupancy during the morning hours, with the average peak occurring around 11:00 AM, reaching approximately 95% occupancy. The maximum observed occupancy was 100% during mid-morning on a weekday, and the 95th percentile occupancy was near saturation, confirming frequent congestion. These findings suggest that Lot 7 experiences sustained high demand during core business hours, making it a prime candidate for smart parking interventions. Strategies such as real-time availability updates, dynamic pricing during peak hours, and notifications to redirect drivers to less congested lots can significantly alleviate pressure on this facility..

[Audio] Scatter Plot Analysis for Lot 9 Occupancy Trends Parking occupancy in Lot 9 rises sharply in the morning and stays near full capacity throughout the day, peaking at 10:00 AM. Peak Usage and Saturation Maximum occupancy reaches 100%, with the 95th percentile indicating frequent congestion and a high risk of saturation during peak hours. Targeted Solutions Implementing real-time guidance and demand-based pricing can reduce circulation time, improve satisfaction, and optimize resources effectively. The scatter plot for Lot 7 demonstrates a clear time-dependent pattern in occupancy rates. Data indicates a rapid increase in occupancy during the morning hours, with the average peak occurring around 11:00 AM, reaching approximately 95% occupancy. The maximum observed occupancy was 100% during mid-morning on a weekday, and the 95th percentile occupancy was near saturation, confirming frequent congestion. These findings suggest that Lot 7 experiences sustained high demand during core business hours, making it a prime candidate for smart parking interventions. Strategies such as real-time availability updates, dynamic pricing during peak hours, and notifications to redirect drivers to less congested lots can significantly alleviate pressure on this facility..

[Audio] Recommendation and Implementation Plan Our recommendation is to begin with a phased rollout, starting with Lots 7 and 9 since they experience the highest congestion. The app will provide live availability data and navigation to underutilized lots, helping drivers save time. Dynamic pricing will manage demand, while enforcement integration ensures compliance and turnover. Accessibility features, such as visibility of ADA and EV spaces, will further improve user experience. This approach balances efficiency, fairness, and inclusivity..

[Audio] Recommendation for Smart Parking App Phased Implementation Start the smart parking app rollout with Lots 7 and 9 to manage demand effectively. Real-Time Availability & Navigation App provides live parking space data and turn-by-turn directions to underutilized lots. Dynamic Pricing & Enforcement Dynamic pricing helps manage peak demand while enforcement integration ensures turnover compliance. Accessibility Features Visibility of ADA and EV parking spaces improves accessibility and user experience. Based on the analysis, it is recommended that the city proceed with a phased implementation of a smart parking application, starting with Lots 7 and 9. The app should provide real-time availability, turn-by-turn navigation to underutilized lots, and dynamic pricing to manage peak demand. Additional features should include enforcement integration for turnover compliance and visibility of ADA and EV spaces to enhance accessibility. These measures will help redistribute parking demand, reduce congestion, and improve the overall efficiency of the parking system. The recommendation aligns with smart city objectives, leveraging technology to deliver sustainable and user-centric solutions..

[Audio] KPIs and 90-Day Roadmap Key Performance Indicators Pilot KPIs include reducing curb-to-space time by 15% and shifting 10% arrivals to adjacent lots. Phase 1: Setup and Configuration Weeks 1–4 focus on configuring sensors, data feeds, app interface, and signage for the pilot. Phase 2: Soft Launch and Testing Weeks 5–8 include a soft launch with A/B testing of messaging and pricing strategies to optimize results. Phase 3: Evaluation and Scale-up Weeks 9–12 involve evaluating KPIs, refining the system, and planning for broader implementation. To ensure the success of the pilot program, clear KPIs should be established. These include a 15% reduction in curb-to-space time during peak hours, a 10% shift of arrivals from saturated lots to adjacent facilities, and a 5% decrease in circulation vehicle miles traveled (VMT) and associated emissions. The 90-day roadmap consists of three phases: (1) Weeks 1–4: Configure sensors, data feeds, app interface, and signage; (2) Weeks 5–8: Conduct a soft launch with A/B testing of messaging and pricing strategies; and (3) Weeks 9–12: Evaluate KPIs, refine the system, and plan for scale-up. This structured approach ensures that the pilot is data-driven, measurable, and adaptable to evolving needs..

[Audio] References Rocco, G., Pipino, C., & Pagano, C. (2023). An overview of urban mobility: Revolutionizing with innovative smart parking systems. Sustainability, 15(17), 13174. https://doi.org/10.3390/su151713174. Raj, A., & Shetty, S. D. (2024). Smart parking systems technologies, tools, and challenges for implementing in a smart city environment: A survey based on IoT & ML perspective. International Journal of Machine Learning and Cybernetics, 15, 2673–2694. https://doi.org/10.1007/s13042-023-02056-5 Bayih, S. H., & Tilahun, S. L. (2024). Dynamic vehicle parking pricing: A review. Operations Research and Decisions, 34(1), 27–45. https://doi.org/10.37190/ord240103. Razack, N. A., Bansal, P., & Khalakc, A. A. (2024). Evaluation of smart parking systems in the context of smart mobility. International Journal of Research Publication and Reviews, 5(3), 2296–2299. https://ijrpr.com/uploads/V5ISSUE3/IJRPR23630.pdf.