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Ore’s Status Report for 3/14/26

This week I focused on getting the user detection system running on the Raspberry Pi 5 with the Raspberry Pi Camera Module. I ported the vision pipeline to the Raspberry Pi and began testing live camera input while running the pose estimation model. The system uses MoveNet to detect body keypoints and estimate the user’s torso center, which is then used to compute the position error relative to the center of the camera frame. I spent most of my time testing the pipeline on the Raspberry Pi, debugging runtime issues, and verifying that the camera feed and model inference run correctly on the target hardware.

My progress is slightly behind schedule because I am still debugging a few issues related to running the system on the Raspberry Pi.

Next week, I plan to finish debugging the user detection system on the Raspberry Pi and continue testing the tracking pipeline with the camera. As I also help get the physical assembly completed, this will allow me to begin early integration testing of the full system. I will begin connecting the vision output to the motor control system so the umbrella can adjust its position based on the detected user location.

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Team Status Report for 3/14/26

One of the most significant risks to the success of the project is delays in the physical assembly of the system, particularly the integration of the motors, gears, and structural components. Although much of the initial software development has been completed, meaningful system testing depends on the mechanical components being installed and functioning properly. Without the motors and gearing mechanisms in place, we cannot fully validate the motion control, actuation, and overall system responsiveness of the shade system. Mechanical integration also presents challenges such as alignment issues, mounting stability, and ensuring that the motors provide sufficient torque to move the canopy reliably.

To manage this risk, we’re prioritizing the completion of the remaining mechanical tasks so that the hardware and software subsystems can be integrated as soon as possible. The focus for the current phase of the project is completing the mounting brackets, canopy fabrication, and the full physical assembly of the arm, joints, canopy, and motors. These tasks are distributed across the team to ensure steady progress and reduce the likelihood of delays caused by a single point of failure. By accelerating the physical assembly process by having more people helping, we will be able to begin integrated system testing earlier and identify potential issues before the final stages of the project timeline.

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Bonnie’s Status Report for 3/14/26

This week I focused on the development of the iOS application that will control the smart umbrella system. I created the initial Xcode project and implemented the basic app structure using SwiftUI. The app includes separate components for models, services, view models, and views to keep the code organized.

I implemented the networking layer that will allow the app to communicate with the Raspberry Pi using HTTP requests. The app is set up to send commands such as move, stop, and mode changes, and to retrieve status information from the umbrella system.

The user interface currently includes the initial screens for connecting to the device and controlling the umbrella. These screens will eventually allow users to adjust pan and tilt angles, change modes, and monitor system status.

I also committed the initial version of the app to our GitHub repository and pushed it to a new branch (iOS-APP) so the team can review and collaborate on the implementation.

Next steps include connecting the app to the Raspberry Pi API, testing communication between the phone and the umbrella system, and improving the control interface for smoother interaction.

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Nicholas’s Status Report 3/7/26

Most of our work recently was finalizing decisions for the design document which took a big push due to the fact that we were slightly behind on research because of our project pivot. Some of the decisions I worked on are listed. We selected the majority of the BOM and ordered our parts which we should receive by the end of the week after spring break.

We decided on NEMA 17 planetary gear stepper motors because their peak torque at 0 RPM provides the necessary mechanical resistance against coastal wind forces, which was a critical trade-off compared to the lower standstill torque of servo motors. Furthermore, we selected Lithium Iron Phosphate (LiFePO4​) for our power subsystem specifically for its thermal safety and stable voltage discharge, ensuring the system can operate reliably for a full 8-hour day in high-temperature beach environments.

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Ore’s Status Report for 3/7/26

This week, I helped narrow down which parts to buy and started submitting actual purchase orders. I also worked on the user detection implementation, but mainly this week, for me, was drafting, refining, and submitting the design report. I’m currently on track with my scheduled work. Next week and a half, I hope to finish locally testing the user detection and have the full physical assembly of our shade system completed.

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Team Status Report for 3/7/26

At the moment, the most significant risks that could jeopardize the success of the project are falling behind on our individual work, which may cause other team members to not be able to progress within their areas of work in the project. We’re planning to be more strict with following our schedule and staying on top of things to have a working demo in time, and shifting priorities within the project as needed, keeping our TA and designated professor in the loop. We’re currently working on the perception, app development, and the physical assembly of our project

 

A was written by Bonnie, B was written by Ore, and C was written by Nicholas.

Part A: Global Factors

Our smart beach umbrella considers several global factors beyond a local setting. Rising global temperatures and increased UV exposure make sun protection more important worldwide. An automatically adjusting umbrella can help reduce health risks such as heat stroke and sunburn in many regions.

Accessibility is also a global factor. Not all users are physically able or technologically experienced enough to adjust a traditional umbrella frequently. Automating the process makes the product more inclusive.

Cost and scalability were considered by using affordable components such as a Raspberry Pi and standard motors, making the system more practical across different economic environments. Privacy is also important, since the umbrella uses a camera and mobile app, so data processing should remain local to protect users.

 

Part B: Cultural Factors

The design of Shade.ai also considers cultural factors associated with beach recreation and outdoor leisure. In many coastal communities, beach outings are social and family-centered activities where convenience, relaxation, and shared spaces are valued. A system that autonomously maintains shade allows users to focus on spending time with friends and family rather than repeatedly adjusting equipment.

 

Part C: Environmental Factors

Shade.ai prioritizes the protection of living organisms and the responsible use of natural resources through its core functionality and material selection. By utilizing autonomous solar modeling and CV-based tracking, the system provides a reliable barrier against harmful UV radiation, addressing a health risk for beach-goers that is often underestimated due to unreliable cooling sensations.