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Team Status Report for 12/7/24

Significant Risks + Management

Design Changes

Schedule Changes

There are no major schedule changes, and we are on track to have the project completed by our final demo date. We are going to focus on the testing portion.

Progress

Sharon focused on testing and refining key features of the mobile app this week. She conducted latency testing using tools like the NRF Connect app, achieving consistent command latencies under 100ms with automated scripts. She also implemented unit tests to validate core features such as command handling and GPS integration. Additionally, Sharon improved the frontend UI for GPS data streaming for real-time updates and enhanced the ‘Return to Me’ feature with two-point route planning UI. She expanded the stats tracking functionality to include metrics like top speed and total miles traveled, providing users with valuable performance insights.

Jason focused on stress testing the physical composition of the board. This included many non-quantitative assessments such as verifying integrity of the wheels and enclosure after driving over a variety of different surfaces with different weighted passengers. Jason also assisted with soldering of gps chip antenna attachments and will be working to implement the RTK items along with Tio.

Unit Tests and System Testing

Unit Tests Conducted:

  • Command Execution: Tested the responsiveness of motor control commands sent from the app to the skateboard, ensuring a consistent latency under 100ms. Automated scripts were used to validate performance across 100 iterations.
  • GPS Integration: Verified real-time GPS data streaming from the skateboard to the mobile app. Unit tests simulated GPS updates to ensure seamless transitions and accurate location updates.
  • Stats Reporting: Tested the app’s ability to track and display metrics like top speed and total miles traveled, confirming data integrity and consistency under various usage scenarios.
  • Stress Testing: Tested the boards ability to keep all parts on board and the enclosure attached through different challenging terrains, affirming the boards ability to be used in a variety of different users circumstances.

 

System Tests Conducted:

  • Latency Testing: End-to-end latency was measured for commands sent from the app to the skateboard. The system consistently achieved sub-100ms response times, meeting the project’s use-case requirement.
  • End-to-End Integration: Simulated a 2+ mile trip to validate system stability, focusing on seamless communication between components, including Bluetooth connectivity, GPS data flow, and app functionality.

Findings and Design Changes:

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Sharon’s Status Report for 12/7/24

WORK ACCOMPLISHED:

Latency Testing for Mobile App Commands: This week, I focused on evaluating the latency between the mobile app and skateboard functionality. Using tools like the NRF Connect app and custom testing scripts, I measured execution times for commands sent to the skateboard. Each command consistently achieved a latency of under 100ms, meeting performance goals. I automated this process by running a script that called commands 100 times, ensuring the system’s responsiveness and reliability under continuous use.

Unit Testing for the App: I implemented unit tests for the mobile app to validate individual components and functions. These tests focused on core features such as command handling, GPS data integration, and stats reporting. By simulating app interactions, I ensured that the app behaves as expected under various scenarios. This foundational testing step provides confidence in the stability of the app as we move into more complex integrations and system testing.

Streaming GPS Coordinates: I refined the GPS data streaming functionality, enabling real-time updates of skateboard coordinates. The improved implementation now streams accurate location data seamlessly, even when transitioning to new data sources such as the RTK GPS module. These updates ensure the ‘Return to Me’ feature is well-equipped for precise navigation.

Frontend Refinements for ‘Return to Me’ Feature: I enhanced the flow and UI for the ‘Return to Me’ feature, now utilizing two points for more accurate route planning (current location and return destination). While this update improves clarity and functionality, additional tests are needed to determine the maximum operational range. Collaboration with the team on range testing has begun to collect this critical data.

Enhanced Stats Reporting: I expanded the app’s stats tracking capabilities to include metrics such as top speed and total miles traveled. These additions enhance the user’s ability to monitor and assess skateboard performance over time, providing valuable insights into its usage.

PROGRESS:

The project is progressing well, with significant accomplishments in performance testing, app functionality, and collaborative testing efforts. The addition of unit tests has improved the app’s reliability, while there will be more ongoing tests for the coming week for the end to end system.

NEXT WEEK’S DELIVERABLES:

  • Focus on improving the user interface for the ‘Return to Me’ feature, such as adding visual feedback for range limits and refining the map display for better usability.
  • Extend unit tests to cover error handling and edge cases and stress testing.
  • Finish the other testing parts of our use-case requirements.
  • Integrate RTK GPS data for improved accuracy in location tracking.
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Team Status Report for 11/30/24

Significant Risks + Management

GPS accuracy issues have not been resolved, but we now possess all the components we need for setting up GPS-RTK, and aim to complete this before the final demo.

Design Changes

We’ve changed the nature of our LiDAR integration, as it seems that the RealSense series is incompatible with Raspberry Pi OS. We have been able to use it in MacOS and Linux environments without issue, so there is the possibility that we demo with a LiDAR mounted on the board and a connected laptop serving as an intermediary between the device and the board.

Schedule Changes

There are no major schedule changes, and we are on track to have the project completed by our final demo date.

Progress

Jason has designed and 3D printed an enclosure for the onboard electronics. The board can easily be assembled and disassembled for reconfiguring and debugging electronic components.

Tio has written the autonomous return and manual control for the board, and is currently refining the RTK accuracy for improving the return.

Sharon has integrated the backend Bluetooth signals from the mobile app with the Raspberry Pi on the skateboard. She addressed challenges with outdated libraries by utilizing a specific fork of Bleno and implemented a socket-based communication flow, which improved responsiveness and reduced latency for motor control commands. Sharon also worked on refining the GPS accuracy for the ‘Return to Me’ feature by testing various filtering techniques, including the Kalman filter, to smooth out location inconsistencies. Additionally, Sharon refined the app interface, introducing an emergency stop button requiring a double-tap to activate for added safety and removing the reverse functionality to simplify user interactions.

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Sharon’s Status Report for 11/30/24

WORK ACCOMPLISHED:

Frontend Enhancements for Remote Control: This week, I finalized several UI elements on the remote control page, focusing on making the interface more interactive and user-friendly. Based on feedback from our demo, where users emphasized the importance of receiving immediate feedback that the board was operational, I modified the app to display the duty cycle instead of just speed. Additionally, I integrated a speed indicator to provide a more intuitive and responsive user experience, ensuring real-time visibility of the board’s performance metrics.

Motor Control Optimization: I finalized the motor control code, focusing on achieving a smooth and reliable speed curve. After iterative adjustments and testing, I optimized the speed rates for better responsiveness and stability. Additionally, I refined the emergency stop functionality to make it more effective and immediate, enhancing overall safety during operation. These changes ensure a more seamless and controlled user experience.

Integration of GPS Location Display: For the ‘Return to Me’ feature, I successfully connected the board’s GPS location to be displayed on the app. Following the pattern established with the socket-based acceleration controller, I set up sockets for GPS data transmission from the Raspberry Pi to the app. This implementation enables real-time location updates, represented by a pin on the app’s map interface. This progress ensures better visualization and understanding of the board’s current position, advancing the reliability of the ‘Return to Me’ feature.

PROGRESS:

Progress is on schedule, with the majority of tasks successfully completed. The remaining work involves final refinements to polish the features and ensure they function as intended. Extensive testing is underway to validate performance, usability, and reliability, addressing any minor adjustments needed to meet the project’s goals. These final steps will ensure a seamless and fully functional system.

NEXT WEEK’S DELIVERABLES:

  • Link animations to the return sequence and ensure synchronized movement of the board with the app.
  • Collaborate with teammates to finalize metrics and visualizations.
  • Implement a centralized Bluetooth context to streamline connections and improve efficiency.
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Sharon’s Status Report for 11/16/24

WORK ACCOMPLISHED:

Bluetooth Integration and Motor Control Setup:
This week, I focused on connecting the Raspberry Pi to the mobile app via Bluetooth to control the skateboard’s motors. One challenge was that many Bluetooth packages for Node.js were outdated and lacked community support. After extensive troubleshooting, I found a specific fork of the Bleno library that supported my requirements, allowing me to set up a functional BLE server on the Pi.

Initially, I attempted to call my teammates’ Python motor control scripts directly from the JavaScript BLE server. However, this approach was not seamless and introduced unnecessary delays. To optimize the workflow, I restructured the system by implementing sockets for motor control. The BLE server now forwards commands from the mobile app to the socket server, which listens on the same port and directly communicates with the motors. This solution reduced network overhead and significantly improved latency, creating a smoother and more responsive control experience.

Frontend Refinements:
I refined the app’s interface to enhance usability and safety. The emergency stop button now requires users to press it twice to prevent accidental activation, providing a crucial safety measure during operation. Additionally, I removed the reverse function from the control UI to simplify interactions, based on user feedback and testing insights.

GPS Accuracy Testing and Improvements:
Continuing work on the ‘Return to Me’ feature, I tested the phone’s GPS capabilities alongside the purchased GPS module. Outdoor testing showed an accuracy of up to 4 meters under favorable conditions. To improve results, I applied aggressive filtering techniques and implemented a Kalman filter to smooth out inconsistent data points. While this approach showed promise, testing was limited due to inclement weather, leaving room for further optimization. These efforts move us closer to reliable location tracking for the return feature.

Dependency Updates and Maintenance:
Maintaining the app involved updating several dependencies to ensure compatibility and stability. This task was critical to resolving issues introduced by outdated packages and improving the overall development environment.

PROGRESS:

The integration of the BLE server with socket-based motor controls marks a significant improvement in responsiveness and system efficiency. The updated frontend design prioritizes user safety while maintaining functionality, and the progress in GPS accuracy ensures we are on track for reliable navigation. These accomplishments strengthen the foundation for real-time control and navigation, aligning with our project timeline and goals.

NEXT WEEK’S DELIVERABLES:

  • Finalize motor control testing to ensure seamless and reliable operation under various conditions and define acceleration/deceleration curve with teammates.
  • Continue testing the Kalman filter and experiment with additional methods to enhance GPS precision, prioritizing outdoor trials when weather permits.
  • Begin setting up WebSocket connections to allow continuous data streaming from the Pi to the app, enabling real-time monitoring and control.
  • Connecting the GPS functionality and return to me feature from teammates.
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Sharon’s Status Report for 11/9/24

WORK ACCOMPLISHED:

GPS Location Testing for ‘Return to Me’ Feature:
This week, I focused on refining the GPS location tracking for the ‘Return to Me’ feature, specifically testing the React Native geolocation library to assess its accuracy when integrated into the app. To establish a benchmark, I set the skateboard’s GPS as the ground truth. Through testing, I found that indoor accuracy was less reliable, especially when compared to the hardware data. Using the Apple longitude and latitude APIs revealed limitations in precision, even though they provided more digits in the coordinates. Outdoor testing yielded better results, with an accuracy of approximately 5 meters, and we are considering snapshotting the user’s location for the return feature. I will continue exploring methods to enhance GPS precision and conduct additional tests to ensure reliable navigation.

Bluetooth Backend Server Setup on Raspberry Pi:
In parallel, I worked on establishing a Bluetooth backend server on the Raspberry Pi to enable control from the mobile app. This process encountered several challenges, as many Bluetooth libraries were outdated, and only specific older Node.js versions supported Bluetooth socket functionality effectively. After troubleshooting compatibility issues, I successfully set up the server on the Pi. I also initiated connection testing between the app and Pi, allowing initial button presses on the app to trigger responses from the Pi. This setup aims to facilitate seamless control of the Raspberry Pi via the mobile app, enabling my teammates to shift from terminal-based commands to app-based control as they complete testing on individual components.

PROGRESS:

With enhanced GPS testing and a functional Bluetooth server setup, the app is progressively prepared for full control and navigation capabilities. Testing the React Native geolocation library provided valuable insights into the strengths and limitations of GPS tracking across different environments. The Bluetooth backend setup on the Raspberry Pi also establishes a foundational control link between the mobile app and hardware, simplifying interactions for further integration with the skateboard. These developments create a stable base for expanded real-time functionality and keep us aligned with the project timeline.

NEXT WEEK’S DELIVERABLES:

  • Continue refining the GPS accuracy for the ‘Return to Me’ feature by implementing additional testing strategies to optimize location tracking, including snapshotting techniques.
  • Collaborate with teammates to finalize control mechanisms over Bluetooth, refining button responses and commands on the app to ensure seamless interaction with the skateboard’s components.
  • Begin exploring WebSocket integration for continuous data streaming from the Pi, allowing real-time feedback and control.
  • Test the Bluetooth setup further by connecting more app functionality with Pi feedback, working closely with teammates as they conclude individual testing, aiming for complete app-based control by the end of the week.
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Sharon’s Status Report for 11/2/24

WORK ACCOMPLISHED:

Backend Setup and API Integration: This week, my primary focus was on establishing a complete backend server setup that enables the mobile app to connect and communicate with the Raspberry Pi seamlessly. I developed API endpoints for essential commands and data exchanges, connecting these endpoints to the frontend to provide a responsive and cohesive interface. So basically defining more of the flow of the web app and how the commands to the skateboard will work. So now when you hit the button, it’ll send a HTTP request using Axios to the defined API endpoint which will also be on the Raspberry Pi server. Additionally, I set up a dedicated server on the Pi, allowing it to handle requests from the app efficiently. This backend foundation is a key milestone, as it allows for real-time control functionality and prepares the app for more complex interactions with the skateboard’s hardware. Once my teammates are ready and finished with their individual testing of the parts, we can connect the two systems so that when an action occurs on the frontend, it will go through the backend and function in real life. Also, defined that using Bluetooth the highest latency will be 100ms around so that’s good.

GPS Integration and Testing: I am currently testing GPS functionality using a React Native library, focusing on enhancing location accuracy for a smoother navigation experience. Configuring and testing various settings within the library allowed me to assess its performance under different conditions, aiming for precise location tracking. Permissions were set up on the frontend to streamline user access to GPS features, creating a user-friendly experience. Testing different configurations gave insights into optimal settings, which will improve the app’s navigation responsiveness. Also, looking into more of algorithms or signal smoother I can do to make it more accurate and seeing if I can get a longer and consistent stream of data in order to get a more accurate location on the phone.

Volume and Ringer Control Functionality: To enhance control options within the app, I also added functionality for the phone’s volume buttons and ringer, allowing users to control specific skateboard actions using these hardware features. I set up listener functions within the app to detect volume button presses, mapping these to skateboard controls, and adjusted the ringer settings to allow control sound feedback as needed. This additional control layer provides users with an intuitive way to manage interactions without relying solely on touchscreen inputs, especially useful in active scenarios where quick adjustments may be necessary.

PROGRESS:

With the backend server, GPS functionality, and volume control setup complete, the app is well-prepared for expanded interactions with the Raspberry Pi. The API endpoints and server setup on the Pi allow for smooth data and control flow, and the GPS implementation provides accurate location tracking. Testing the React Native GPS library was insightful, allowing me to fine-tune settings for maximum precision, while the volume and ringer control adds a valuable layer of user interaction. These accomplishments set up a stable platform for further real-time control developments, keeping us on track with the project timeline and hopefully allowing us more time to test when finish assembling the skateboard. I have set up this foundation so it would be easier and allow a smooth transition of integrating with the actual hardware in preparation for the completion of my teammate’s work.

NEXT WEEK’S DELIVERABLES:

Next week, I aim to complete the following:

  • Finalize the testing of API endpoints for button controls, working with teammates to fine-tune parameters like acceleration and deceleration when they complete their individual testing.
  • Once my teammates have been able to control their specific parts, I need to set up WebSockets and the backend on the Raspberry Pi to get the streamed data onto the app. I am waiting for them to see if they can get data from the hall sensors.
  • Something we will work on is how the control of the remote will work on the volume buttons so will it be levels or more like a traditional remote controller where you can long hold the buttons.
  • Continue working on the GPS coordinates of the phone and then be able to integrate with the LIDAR so we can start path planning.
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Sharon’s Status Report for 10/26/24

WORK ACCOMPLISHED:

Bluetooth Functionality and Raspberry Pi Integration: This week, I focused on integrating Bluetooth functionality with the Raspberry Pi, which involved several setup challenges. Without an HDMI cable to connect the Pi to a monitor, I had to set it up headlessly, reimaging it with a specific network to enable SSH access. Once connected, I configured the Pi’s Bluetooth by enabling and testing it, then moved to set up Bluetooth on the mobile app. This required installing specific libraries and creating a BLE manager, which allowed the app to discover and connect to the Pi. Since Expo Go doesn’t support BLE, I had to split the native code for both Android and iOS, setting permissions accordingly.

On the Pi, I established a systemd service to automatically enable Bluetooth at boot, ensuring the Pi is always discoverable. After extensive testing, I successfully confirmed the app could reliably connect to the Pi. This milestone establishes a solid Bluetooth connection foundation, preparing us for future functionalities, including real-time controls.

Backend Preparation and Testing Setup: To prepare for backend integration, I continued organizing code for modularity and responsiveness, particularly for features that will connect to backend functionality. While full backend development remains pending, I focused on structuring the app’s Bluetooth connections and streamlined code for compatibility with the upcoming Raspberry Pi and mobile app control interfaces. I also started to make the API endpoints so that when my teammates are ready to connect everything system wise, they have an app to test with and connecting these two systems.

Raspberry Pi Setup: I worked on setting up the Raspberry Pi and making sure that the Github repository was on the Pi so that all my teammates can work on it without disrupting each other’s work and also be able to commit their work to Github from the Pi and so that there wouldn’t be any lost work and we are all able to see each other’s work on the Pi as well. I think something we could possibly setup is remote ssh on the Pi since only some team members need physical access to the Pi and others like me only need the remote capabilities of using the Pi to test software wise.

Code Refactoring: With this setup complete, the app is functionally ready for initial Bluetooth control testing, even though backend development is ongoing. I refined various elements across the app, particularly responsiveness and UI adjustments to enhance cross-device consistency. A systemd service ensures Bluetooth functionality on the Pi is seamless, and connection flows on the app are now stable. I also spent time refactoring code for future maintainability and responsiveness improvements.

PROGRESS:

Overall, I’m on track with Bluetooth integration, and the core Bluetooth connection functionality is operational. I overcame challenges with the headless Pi setup, expanding skills in network-based configurations and system services. While backend work has been delayed and I have been working on it still, foundational steps for future app and Pi interaction are complete, including BLE manager setup and systemd service automation. This enables us to move forward with Bluetooth-based features as scheduled in our Gantt chart. My next steps focus on backend setup and enhanced functionality for a polished user experience.

NEXT WEEK’S DELIVERABLES:

Next week, I aim to complete the following:

  • Finish setting up the API endpoints for button control and defining the acceleration curve as well by speaking with my teammates.
  • Once my teammates have been able to control their specific parts, I need to set up WebSockets and the backend on the Raspberry Pi to get the streamed data onto the app.
  • There’s some things that still look a tiny bit off on different screen sizes so need to make more dynamic.
  • Continue improving the visuals and animations for a more polished user experience.
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Team Status Report for 10/19/24

SIGNIFICANT RISKS + MANAGEMENT:

One significant risk currently facing the project is the delay in GPS testing due to missing components, such as the antenna and Qwiic connectors. Without these parts, there is a risk that potential integration issues with the GPS module might not be identified early, which could impact the timeline for autonomous features. Another key risk is the delay in Bluetooth integration between the mobile app and the Raspberry Pi. This was caused by limited access to the Raspberry Pi earlier in the week. To mitigate this, mock data is being used to test the BLE functionality, ensuring that once hardware is accessible, the final integration can proceed smoothly.

There is also a risk with backend development—the team is still debating its necessity. If backend services are deemed essential later, it could introduce delays. To manage this, we are exploring lightweight solutions to avoid additional complexity.

DESIGN CHANGES:

So far, there have been no major design changes this week. However, discussions are ongoing about whether to implement a backend server for managing user data and skateboard status. If backend functionality is introduced, it may require modifications to both the web app and data management strategies. Additionally, the fall break adjustment in our Gantt chart has led us to focus more heavily on setting up hardware and testing BLE connections, slightly shifting the weight of certain tasks in the schedule.

SCHEDULE CHANGES:

The project schedule has been adjusted to account for fall break, with the understanding that fewer tasks were planned for completion during that week. This adjustment allows us to reallocate efforts toward critical tasks in the upcoming week, including sensor integration and motor control development. Additionally, the delay in Bluetooth testing pushed some BLE-related milestones into next week. These adjustments ensure that the project can continue progressing without disruptions, and all key deliverables are still aligned with the final deadlines.

PROGRESS:

This week, the team made significant progress in both hardware setup and software development. Parts from the course inventory, including the Raspberry Pi 4, Intel RealSense LiDAR Camera L515, and SparkFun GPS-RTK Dead Reckoning Breakout (ZED-F9R), were retrieved, and initial setup tasks were initiated. The Raspberry Pi environment was configured, and preliminary testing of the LiDAR sensor was successfully performed on desktop and Windows devices. This involved installing the RealSense software and exploring the Intel SDK’s integration with Linux. We also reviewed Python code samples to streamline sensor integration efforts.

In parallel, the mobile app development progressed significantly. The entire UI/UX, with animations, real-time feedback, and responsive design, was completed, and the core layout for the remote control is now ready. Foundations for Bluetooth Low Energy (BLE) integration have been established by refining connection flows. However, Bluetooth testing has been delayed as access to the Raspberry Pi was limited this week. In the meantime, mock data is being used to simulate the BLE functionality. The team is also considering the need for backend coding, which is still under discussion.

Testing of the GPS module remains pending as essential components, such as the antenna and connectors, are still on order. The design report has been finalized and will guide system integration moving forward. Additionally, we adjusted our timeline to account for fall break, acknowledging that fewer tasks were expected to be completed during this period unless necessary.

Part A: Global Factors

(Written by Tioluwani Ajani)

SkateBack addresses the growing global need for sustainable, accessible urban transportation solutions by providing a personal mobility option that is electric, compact, and adaptable to various environments. With increased urbanization worldwide, many cities face challenges related to traffic congestion, air pollution, and accessibility. SkateBack offers a zero-emission alternative that encourages individuals to reduce their dependence on fossil-fuel-powered vehicles, contributing to a cleaner environment. As governments and organizations worldwide push for carbon neutrality and improved air quality, personal electric transportation options like SkateBack align with these goals by promoting environmentally friendly travel options. This solution not only benefits cities but also applies to smaller communities where public transportation options may be limited or unreliable, bridging the mobility gap sustainably.

Part B: Cultural Factors

(Written by Jason Hoang)

a

Part C: Environmental Factors

(Written by Sharon Li)

SkateBack is designed to address environmental challenges, particularly in urban transportation and air pollution. By offering a zero-emission alternative for short-distance travel, it contributes to reducing the carbon footprint. As cities and governments push for carbon neutrality with stricter emissions regulations, electric skateboards like SkateBack enable individuals to actively participate in these global environmental efforts. With its rechargeable batteries, SkateBack minimizes the need for fossil fuels, and its compact size reduces the strain on urban infrastructure. SkateBack is designed to reduce dependency on cars and other gas-powered vehicles, thus playing a role in the mitigation of environmental impacts from transportation.

Beyond providing sustainable mobility, SkateBack encourages users to adopt greener habits. Its CO2 savings feature allows users to track how much they’ve reduced their emissions by choosing the skateboard over traditional vehicles. This raises awareness about carbon footprints and empowers users to make more eco-friendly transportation choices. As cities adopt greener transportation solutions to combat climate change, SkateBack aligns with initiatives to reduce fossil fuel dependence and enhance sustainable urban mobility.

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Sharon’s Status Report for 10/19/24

WORK ACCOMPLISHED:

UI Layout Finalization and Enhanced User Experience:  

This week, I finalized the UI layout for all the key pages in the app, with a particular focus on setting up the connection flow. Now, users can seamlessly navigate through the process of pairing their skateboard, selecting devices, and managing connection success or failure.  The connection pages are fully designed and functional, including the welcome screen, device list, search, and both success and failure outcomes. For this, I just used mock data for now. I also added animations to enhance user interaction, making the overall experience smoother and more intuitive. With these components in place, the frontend is now in a solid state, ready for backend integration. The UI is responsive and visually polished, laying a strong foundation for future development. 

Additionally, I implemented a progress bar animation for the “Return to Me” feature, providing real-time feedback as the skateboard gets closer to the user. I also added a warning visual to alert the user if the skateboard is more than 5 meters away, enhancing the safety and usability of the feature.

Stats Page and Calculations: On the stats page, I calculated the equation for CO2 saved to provide users with meaningful feedback on the environmental impact of using the skateboard (the average passenger vehicle emits about 400 grams of CO2 per mile). This data is visually represented to engage users in tracking their sustainability contributions.

Remote Control Enhancements: The remote control page was improved with the addition of battery calculations and a corresponding visual to show real-time battery levels. I adjusted the battery percentage visuals to ensure accuracy and readability, which is critical for the user experience.

Responsive Design: To ensure the app looks good across different devices, I adjusted styles to be more responsive to various phone sizes. I also refined the tab bar styles, making navigation more user-friendly.

PROGRESS:

I’m on track with the progress made this week, particularly in finishing the entire UI/UX with animations, real-time feedback, and responsive design. The core layout for the remote control is complete, and I’ve laid the groundwork for future BLE integrations by refining the connection flows. Since I haven’t had the chance to work with the Raspberry Pi yet, it has pushed back my schedule for Bluetooth connectivity and integrating it with the mobile app. However, I have set up the proper libraries and will try testing it with mock data for now. Also, backend coding is still pushed but still debating the necessity for that. Also, for our gantt chart, we didn’t take into consideration that we had fall break and we were only going to complete additional tasks during that week if necessary. The schedule is below for my progress (my tasks are colored in orange and my shared tasks in yellow):

NEXT WEEK’S DELIVERABLES:

Next week, I aim to complete the following:

  • Finish integrating BLE functionality and begin testing with the Raspberry Pi.
  • Start coding the backend for the skateboard control interface.
  • Continue improving the visuals and animations on the control and stats pages for a more polished user experience.
  • Refactor code as needed to prepare for backend integration. Also, refactor the code to make it more reusable and responsive. There’s some things that still look a tiny bit off on different screen sizes.
  • Test the GPS module on react native.