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Jacob’s Status Report for 9/27/2025

This week, I took the responsibility of developing the final design slides. We changed a lot of our previous use case requirements and mapped design requirements that matched them. We also changed our block diagram, switching out certain systems to better meet our needs.

Some examples include:

  • We swapped out the Grafana software to alert users with just Flask and an HTTP protocol. We realized that Grafana is a full-fledged software that might be overkill to send a signal. Whereas we can strictly just send that alert with Flask.
  • We also decided on using an autoencoder ML algorithm
    • It’s unsupervised learning (looking at unlabeled data), which is great for us since we don’t know what an anomaly looks like
    • It also excels at anomaly detection

Moreover, I extensively practiced the presentation content to ensure the presentation went smoothly.

The project is still on track, and we should be receiving a handful of parts soon. As much as I would like to get started on developing our system, we still have to write our design report, which should occupy us for a while.

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Aidan’s Status Report for 9/27/2025

This week, I acquired the Raspberry Pi Pico and servos for cooling loop valve control. I collaborated with my teammates to flesh out exactly how the control loop will function, finalized specific parts to begin PWM requirements reasearch, and sourced my toolchain to develop the Pico software. Next, I conducted thermal analysis on our system as required for our project to solidify our design requirements and ensure they are accurate to our specific design and system. Additionally, I assisted in finalizing the design proposal slides this weekend to ensure they are cohesive and ready for next week’s presentation.

The thermal analysis research was added to the schedule this week given our feedback from team meetings, but otherwise, we are on schedule for the remaining tasks.

Next week, we are focusing on laser cutting parts for the design, finishing up research for specific PWM requirements for our sensors, begin sensor SW dev, and begin software development on the main Pi board. Additionally, we will also continue development on the design report to ensure it is reflective of our research and system design.

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Team Status Report for 09/27/2025

Accomplishments

  • CAD modeling & assembly: Completed CAD assembly for testbed
  • Block diagram: Finalized block diagram with added power distribution components and software
  • Analysis & Research: Conducted thermal analysis and research to justify use case requirements
    • ML model research to choose specific model and plan inputs/outputs

Significant Risks

  • Dependency on off the shelf parts for fabrication: Same as last week, cannot finalize or fabricate custom mounting plates until we have real parts to verify mounting hole dimensions
    • Cannot start testing of code until fan/pump, SSRs, etc. arrive
    • Plan to start ordering parts on Monday

Design Changes

  • Block diagram finalized with added power components and sensor / control separation. No costs affiliated with this design change.
  • CAD assembly finished to also include power components. No costs affiliated with this design change.

Schedule Changes

  • The schedule was updated this week to account for delays in parts purchasing. Fabrication and code development all depend on receiving components.
  • Adjusted task split for parallel development
Gantt Chart

Public Health, Safety, or Welfare

Kristina

Part A: One consideration of public health could be the system’s effect on the operator’s mental wellbeing. Frequent false alerts may cause stress or alert fatigue while reliable detection can reduce anxiety and improve confidence in system performance.

In terms of welfare, maintaining uptime prevents data loss and disruption for users who rely on the server for work. This could help the public’s mental health if people do not have to worry about losing unsaved work.

Social Factors

Aidan

Part B: Our design and product considers social factors by allowing for versatile configuration and tuning towards a multitude of real life applications. This allows the product to be used in different social and economic settings, given that each group has a different set of computing needs, and our product can be fine tuned and adapted to fit each of these groups. Additionally, our product considers alert fatigue with regards to the user and ensures that false positives are minimized to ensure the product works as intended across social groups. Lastly, the ML models and fine tuning are exposed and customizable to the specific user depending on their setup to encourage transparency in the product and solidify trust in AI-based anomaly detection systems.

Economic Factors

Jacob

Part C: For economic considerations of the project, the first thing that catches my mind is components. Our project is intended to help extend the lifetime of the system. With a longer life, the components no longer need to purchased and replaced as frequently. This in turn should save the user money.

Another consideration is the real time cost of running the system. For our use case in the datacenter or servers, they use masses of energy to power themselves. Running AnomAIy should use extremely marginal amount of power compared to the heavy load of the data centers.

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Kristina’s Status Report for 09/27/2025

Completed CAD Model

  • Completed CAD model with water loop and other component models downloaded from online (e.g. SSRs, DC-DCs, etc.)
  • Adjusted radiator + fan position to reduce board size
  • Planned out and added power planes (24V power supply stepped down to 12V, 5V for fan/pump, servo)
  • Began 3d printing some parts from CAD design
    Full Assembly
    Full Assembly – Bottom View
    Water Loop
    Heater Complex (Power Resistors)
    Servo Valve Assembly (Blockage Fault)

    Power Distribution

Block Diagram

  • Finalized block diagram to add power supply and conversion
  • Adjusted coolant temp sensor connection to separate sensor data collection from controls (fan/pump, valve, heater)
  • Added software

    Block Diagram

BOM Draft

  • Completed BOM, added case components like linear motion rods and connectors
  • Added power components like DC-DC converter, power supply

Schedule & Progress

  • Updated schedule to account for part lead times
  • Need to order parts ASAP since fabrication for laser cut parts depend on dimensions of actual mounting holes

Next Steps

  • Begin ordering off the shelf components from BOM
  • Work on design report
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Jacob’s Status Report for 09/20/2025

For this week, I looked into the different software to actually gather data from our system.

Three components: a dashboard and UI layer, a database to hold the data, and (optionally) containers

For UI to make an optimal dashboard for all sensors, I found Grafana to be optimal. Grafana is optimized to display data from sensors with speed and temperature, and has built-in user-friendly features to help users implement dashboards. It has an easy setup and is very lightweight in terms of storage and processing power required, making it optimal for a Raspberry Pi.

Alternatives include:

  • Kibana- Which is better when you need to search for things, which is a feature we don’t really need
  • Redash- Which is optimized to display only SQL databases
  • MetaBase- Which is very user-friendly, but meant to display business analytics rather than temperature, fan speed, etc.

InfluxDB will be the database platform we plan to use. It can easily pull and push sensor data with Python and does so very efficiently. Furthermore, all data is time-stamped and optimized for sensors. InfluxDB is also very lightweight and fast, which makes it easy to use on the Pi.

Alternatives include:

  • QuestDB- high-performance, fast-speed DB, but uses SQL interface, and I don’t know SQL
  • Prometheus- This requires exports to transfer data, which is heavier and bulky

Lastly, Docker is a container system used to work across different systems. The code will exist within a sandbox so that it’s not run locally. This prevents the “works on one machine but not another” problem. I’ve used Docker before in a software engineering class and have a good understanding of it, and I believe it will make our project better

Another thing to note is that there already exists a bunch of software that links Grafana to InfluxDB to Docker, so if I get stuck, I have a handful of other repositories to reference.

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Aidan’s Status Report for 09/20/2025

This week, I took charge in developing the design proposal slides and presented for the team. This required coordinating with my teammates to finalize user requirements, testing and verification, and division of labor. Additionally, I extensively rehersed and iterated the proposal presentation content to ensure all project information would be conveyed cohesively and accurately upon presenting.

Additionally, I spent time researching our ML technical requirements to determine viability of both supervised classification and supervised regression to further understand how implementing anomaly detection will apply to our system. I also communicated with my teammates to review our BOM and finalize where we want to source our parts to ensure smooth transition from planning to implementation.

The project is currently on track and are expecting a smooth transition to implementation as begin sourcing parts and finalizing high level design plans.

Our goals for next week include to continue iterating the block diagram as needed, research for linear motion rod and connectors to purchase, and flesh out the system design as we acquire concrete parts and ensure compatibility for all aspects of our system.

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Team Status Report for 09/20/2025

Significant Risks

  • Dependency on off the shelf parts for fabrication: Cannot finalize or fabricate custom mounting plates (3D printed or laser cut) until we have real parts to verify mounting hole dimensions
    • Planning to finalize component choices at the next team meeting to mitigate finalization and order all required parts to resolve mounting dependency
  • Software development blocked by missing hardware: SW arch design, data collection code, and PWM control code development require sensors and Pi to begin implementation
    • Select and order temperature sensors at the next team meeting to ensure schedule depencies are met towards sensor SW design and development
    • Brainstorm and finanlize high level code skeleton to ensure smooth development and implementation once parts arrive

Design Changes

  • Initial block diagram created with Raspberry Pi 5, Pico, servo, and sensor connections to aid in the development of the system once parts are ordered and design finalized. No costs affiliated with this design change.
  • CAD assembly revised to accommodate sensor placements and control system mounts to aid in the development of the liquid cooling loop and ensure anticipated parts will function well with the current system design. No costs affiliated with this design change.

Schedule Changes

  • No changes to the schedule were made this week
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Kristina’s Status Report for 09/20/2025

Block Diagram Draft

  • Made first draft of block diagram showing connections between sensors, Raspberry Pi 5, Pi Pico, SSRs, power resistors, servo valves, and cooling components
Block Diagram v1

BOM Draft

  • Made first draft of BOM listing major components based on block diagram and physical assembly, to be updated

CAD Models of Liquid Cooling Components

  • Found online CAD models of radiator, fan, and water block
  • Altered radiator model to better match actual part
  • Created CAD models for pump and reservoir based on product photos and references
Pump CAD Model – Side View
Pump CAD Model – Bottom View
Pump CAD Model – Top View
Reservoir CAD Model

Initial CAD Assembly of Cooling Loop

  • Built an initial CAD assembly of liquid cooling loop with component models
  • Used linear motion rods and connector system for structural frame
Case Assembly v1 – Left View
Case Assembly v1 – Top View
Case Assembly v1 – Right View

Revised CAD Assembly of Cooling Loop

  • Updated initial assembly to accommodate sensor placements, including radiator intake/exhaust temperature sensors and mounting space for Raspberry Pi 5 and supporting components
Case Assembly v2 – Front View
Case Assembly v2 – Side View
Case Assembly v2 – Back View

Schedule & Progress

  • Currently on schedule
  • CAD modeling, assembly, block diagram, and BOM align with Gantt chart

Next Steps

  • Iterate on block diagram
  • Expand BOM to include linear motion rod and connectors
  • Start purchasing off the shelf parts in order to update CAD assembly with corrected dimensions and order 3D print/laser cut parts