This week, I focused on designing the computer vision pipeline and refining the overall system architecture, with particular emphasis on adapting the solution to real-world constraints. Based on power considerations, I redefined the hardware requirements by transitioning the edge platform from an NVIDIA Jetson to a Raspberry Pi, ensuring better alignment with system limitations while maintaining functional goals. I also spent time finalizing key details of the project proposal, including design rationale and implementation considerations. Overall, my progress remains on schedule, and this hardware adjustment helps reduce risk moving forward. In the coming week, I plan to begin validating the CV pipeline on the updated hardware platform and support the team in completing remaining proposal deliverables.
Giovanni Maddalozzo Status Report for 2/21/2026
This week I worked on looking at the Firebase/Firestore solution. I will have to upgrade our plan to the non-basic plan to get access to the cloud functions. This is fine though because I would only be charged if we go over the “free” quota, which will probably won’t happen for capstone. Also, I figured out how to simplify our backend a bit. We can send the image to Firebase Storage with metadata attached. Then on upload, we can have a cloud function run and insert everything into our database. So we only need 1 cloud function instead of 2 and this will ensure we never go over our limits as well. I created the backend database in Google Firebase. I also ordered more parts, specifically the raspberry Pi. I am still on track and then next week I hope to show a prototype of of the working code and finish ordering all parts.
Giovanni’s Status Report for 2/14/2026
This week I decided on the database and the backend format. The structure of our database will be one table which will hold the pothole id, the location, the severity, validity, and a link to the image which will be stored in Firebase Storage. I also learned that we can host our website via Firebase Hosting, which will simplify our website creation. I also learned how to test our database via the Firebase emulator. I also worked with the team to figure out the parts list and this is where we realized that the Jetson might not be a viable microcontroller. This is because of its power usage and how that poses an issue if we want a backup battery. Next week I hope to actually start coding and creating the backend
Kevin’s Status Report for 2/14/2026
This week I have proposed our website solution for PotSpot and also have a plan for implementing our map API functionality. This plan was made from continued research of map APIs. Additionally, I helped flesh out our design proposal outlining concrete solution flows for PotSpot on the backend. As of right now, this aligns with the schedule outlined in our proposal. In the next week, I intend on starting the actual design of the website portion of our project and work on the GPS transponder implementation.
Team Status Report for 2/14/2026
Overall Project Status
This week, the team made solid progress across hardware, software, and documentation by ordering key components (Jetson, gps transponder, power supply, and cellular note carrier) for the dash cam solution, prototyping the overall dash cam design, and establishing an initial backend architecture along with a well-organized codebase. We also defined several core design proposal components, including the design requirements, system specification and block diagram, implementation plan, and the test, verification, and validation plan, while aligning on project management responsibilities for the immediate next steps. At this stage, no major design changes were made, as the current system architecture meets the project requirements; the primary risks identified involve hardware integration and on-device performance, which are being mitigated through early prototyping and staged testing. The project remains on schedule. In the coming week, the team plans to finalize and order the remaining parts, set up the Jetson SDK, finalize the database schema, establish the Firebase backend, and configure a consistent developer workflow to support coordinated development moving forward.
Attribution:
Part A was written by Dylan.
Part B was written by Giovanni.
Part C was written by Kevin.
Part A: Public Health, Safety, and Welfare Considerations
PotSpot directly addresses public safety and welfare by improving the efficiency and reliability of pothole detection and reporting. Poor road conditions pose safety hazards to drivers, cyclists, and pedestrians, and manual reporting methods are often infrequent and delayed. By automatically detecting potholes with high accuracy and uploading precise location metadata, the system enables faster identification and repair of hazardous road conditions, reducing the likelihood of accidents and vehicle damage.
The system is designed for fully hands-free operation after initial setup, ensuring that drivers are not distracted while operating their vehicles. This design choice prioritizes both physical safety and driver well-being while maintaining continuous data collection in the background.
Part B: Social Factors
Social considerations for PotSpot center on trust, privacy, and equitable access to infrastructure improvement tools. While the system collects road imagery, it is designed to focus on pothole detection rather than individuals, and access to pothole status updates and management features is restricted to authorized city administrators through authentication and audit logging. This helps mitigate concerns related to surveillance and misuse of data.
Additionally, PotSpot supports collaboration between drivers, local governments, and communities by aggregating crowdsourced data into a centralized, easy-to-understand interface. This encourages civic engagement and improves communication between residents and municipalities regarding road maintenance priorities.
Part C: Economic Factors
Economically, PotSpot is designed to balance system performance with cost efficiency. Hardware components were selected to meet strict accuracy and latency requirements while maintaining reasonable weight and power constraints, keeping the overall device affordable and scalable. The use of cloud-based infrastructure enables the system to support up to 1,000 active users without requiring costly on-premise server deployments.
By enabling faster pothole detection and repair, the system has the potential to reduce long-term infrastructure maintenance costs and vehicle repair expenses for drivers. Clear, data-driven prioritization of road repairs allows municipalities to allocate resources more efficiently, resulting in economic benefits for both local governments and the broader community.
Dylan’s Status Report for 2/14/2026
This week, I personally made progress on several core technical and planning tasks, including prototyping the computer vision pipeline, developing an initial dash-cam–based system concept, and researching suitable computer vision datasets to support model training and evaluation. In parallel, I contributed to the design proposal by working on the proposal slides to clearly communicate system goals, constraints, and architecture. Overall, my progress is on schedule relative to the project timeline, with no major blockers identified this week. In the coming week, I plan to focus on on-device testing and iterative tinkering with the prototype CV pipeline to evaluate real-world performance, as well as finalize the remaining components of the parts list to prepare for hardware integration.
Team Status Report 2/7/2026
Hi, this is team B4’s weekly status report! This week we have done a great job meeting and making sure everyone was doing what we needed to do. I think right now one of the risks is getting the wrong part/proposing the wrong part. We are managing this by making sure we put in ample time researching each part before adding it to the parts list and thinking about potential backups. For example for our camera we are thinking about ordering two different ones so we have one as a backup. So far we haven’t made any changes to the existing design, but that might change next week when we really start to finalize parts. No changes have happened to our schedule, but we do think we are somewhat ahead in progress!
– Gio, Kevin, Dylan
Giovanni Maddalozzo Status Report for 2/7/2026
Hi, this is my status report for the week of 2/7/2026. This week I took time to research microcontrollers, how we would connect to the internet, and potential database services. I think we have narrowed down our microcontroller to be the NVIDIA Jetson Nano Orin. We have already put in a request for that piece, which is good. I also looked into the notecarrier which we can use for internet and was previously suggested by Tamal. I put these in our shared folder for the parts. I also think that for our database service we can use Firebase because it is easy to use and Kevin has previous experience with it. I think our progress is on schedule and potentially even ahead since we have somewhat finalized some parts. Next week I want to fully talk about what I have discovered with the team and nail down all the parts so that we can request it that week.
Dylan’s Status Report for 2/7/2026
I focused on building the foundation for the computer vision portion of the project by researching different YOLO versions and computer vision algorithms relevant to pothole detection, as well as exploring CV pipelining strategies for edge deployment. I also began assembling the parts list and submitted order forms for the Jetson Orin Nano, while ensuring steady progress against the project schedule. Next, I plan to finalize and complete the parts list, place the remaining orders, and start experimenting with training and testing computer vision models for pothole detection on the target hardware.
Kevin’s Status Report for 2/7/2026
Earlier this week I presented our project proposal so I prepared my presentation/speaking on PotSpot. Additionally, I also worked on helping make the parts list needed for our project. I helped research on what GPS module that we want to use for our system. I also started brainstorming the style that we want our webapp to look like. On top that, I researched on an initial implementation for the APIs needed to complete the map functionality. This is on schedule and aligns with what I outlined in our project proposal for what I need to get completed this week. In the next week, I intend to propose a more finalized approach to implementing our initial prototype of the webapp of PotSpot.