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Maya’s Status Report for 2025-03-08

  1. Relay ESP32 Setup:
    • Set up a dedicated ESP32 for relay control.
    • Integrated the relay ESP32 with Home Assistant for centralized automation.
    • Began testing the relay functionality with various devices.
  2. Device Integration:
    • Connected minor devices such as a PWM fan, light, and motor.
    • Explored additional devices for potential integration.
    • Evaluated performance and responsiveness of connected devices.
  3. Wiring and Testing:
    • Started wiring and organizing connections for the relay ESP32.
    • Identified and tested different wiring configurations.
    • Determined which setups work best for our needs.
  4. Power Consumption Monitoring:
    • Set up power consumption monitoring to track energy usage.
    • Integrated sensors to measure power draw from connected devices.
    • Began analyzing data to identify potential energy optimization strategies.

Challenges Encountered:

  • Ensuring stable and reliable relay switching for different devices.
  • Managing power distribution effectively to support multiple components.
  • Troubleshooting intermittent connectivity issues between ESP32 and Home Assistant.
  • Calibrating power monitoring sensors for accurate readings.

Next Steps:

  • Expand testing with additional devices to enhance automation capabilities.
  • Optimize wiring layouts for improved reliability and ease of use.
  • Develop automation rules within Home Assistant for better power management.
  • Continue refining the system based on real-world performance observations.
  • Analyze power consumption data to implement energy-saving measures.
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Anya’s Status Report for 03/08/25

Work Accomplished :

  • This week, I focused on developing components of the system that interact with Home Assistant and Nordpool electricity pricing data. The primary tasks included designing and implementing the ESPHomeClient, HomeAssistantClient, and NordpoolClient while also working on the frontend and backend integration.
  • Completed the design report (System Architecture, Quantitative Design Requirements, System Implementation, Testing Methodology)
  • Started working on the frontend + backend functionality of the web app


Implemented an ESPHomeClient to enable communication between ESPHome-based IoT devices and Home Assistant. This module allows devices to send and receive sensor data while maintaining real-time connectivity with Home Assistant.

    • Designed a HomeAssistantClient to interact with Home Assistant’s API, enabling data retrieval and control over smart home devices.

    3. NordpoolClient

    • Built a NordpoolClient to fetch electricity prices from Nordpool via Home Assistant.
    • Integrated API calls to retrieve real-time electricity prices and structured the data for easy analysis.

    On the frontend side, I developed and integrated an energy flow chart that visually represents energy distribution and load optimization within the system.



    Progress:

  • On track with regards to the schedule and GANT chart
  • Currently waiting for integration with Raspberry Pi and  power sensors via ESPHome.
  • Once hardware integration is complete, live data from the sensors will replace simulated inputs in the ML and forecasting module

Tasks to complete next week

  • Conduct end-to-end testing of energy data collection, processing, and visualization.
  • Compare original vs. optimized energy loads to assess efficiency improvements.
  • Identify any bottlenecks in data flow between ESPHome, Home Assistant, and the dashboard.
  • Start integrating predictive analytics for energy consumption forecasting via some sort of inference API
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Erika’s Status Report for 03/08/2025

1. Accomplishments This Week
This week, I focused on two key tasks:

  • Design Review Report: I collaborated with my team to write and refine the design review report, ensuring we clearly outlined our project scope, system architecture, and implementation plan.
  • CAD Model for Demo House: I continued developing the CAD model for our demo house. Specifically, I designed a two-layer wall structure featuring wood on the exterior and acrylic on the interior. This design allows us to sandwich wires and electronic components between the layers for a cleaner, more organized prototype. I also worked on integrating component placements within the model to facilitate efficient wiring and sensor integration.

2. Progress Status
I am on track with my individual tasks for the week. The design review report was completed on schedule, and progress on the CAD model is aligned with our timeline. However, I will need to start laser cutting soon to ensure I do not run into any issues later on.

3. Next Week’s Deliverables
Next week, I plan to:

  • Finalize the CAD of the demo house and determine kerf to verify fit.
  • Laser cut the wood
  • Order the acrylic sheets

This will ensure we stay on track for upcoming milestones and allow us to refine the system before final integration.

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Team’s Status Report for 03/08/25

  • Risk: Hardware Integration Challenges
    • Issue: Ensuring seamless communication between sensors, microcontrollers, and the backend system is critical. Incompatibility between components or unexpected electrical issues could cause delays.
    • Mitigation: We are testing each hardware module separately before full integration and maintaining thorough documentation for troubleshooting.
  • Risk: Energy Monitoring Accuracy
    • Issue: If the system fails to accurately track and optimize energy consumption, the value of SmartWatt is diminished.
    • Mitigation: We are calibrating sensors early in the process, running validation tests, and comparing data against trusted benchmarks..

Contingency Plans:

  • If hardware integration delays occur, we will simulate system behavior in software to continue progress.
  • If energy monitoring accuracy issues arise, we will refine our algorithms and conduct more extensive testing.

2. Design Changes and Their Impact

This week, we made the following adjustments to our system design:

  • Change: Updated Physical Model Design
    • Reason: To improve wiring organization and ease of sensor placement, we modified the demo house’s wall structure to include a layered design (wood exterior, acrylic interior).
    • Costs: This change requires additional material procurement and minor CAD redesign work.
    • Mitigation: We are sourcing materials efficiently and ensuring that fabrication remains within our timeline.

By proactively managing these risks and changes, we aim to keep SmartWatt on track for a successful completion.

ARIMA models from sklearn have been added to the load forecasting module as they have better accuracy on testing data.

Progress

  • Frontend of webapp scoped out
  • ML models working with simulated data
  • API and communication requests between backend and ESPHome and Home Assistant established

Additional Weekly Questions

3. Considerations of Global Factors:

SmartWatt addresses the growing global need for energy efficiency and sustainability by optimizing household energy consumption. As the world transitions to renewable energy, challenges such as grid instability, peak demand management, and high electricity costs are becoming more pressing. SmartWatt provides a data-driven solution by integrating smart meters, IoT-enabled devices, and AI-driven analytics to monitor and optimize energy use in real time. This system empowers homeowners to reduce their carbon footprint, lower electricity bills, and contribute to overall grid stability—an issue that affects both developed and developing regions as energy demands rise.

Beyond local energy concerns, SmartWatt aligns with broader global initiatives such as the United Nations Sustainable Development Goals (SDGs), particularly Goal 7: Affordable and Clean Energy. By enabling users to shift energy consumption to off-peak hours and integrate renewable sources like solar, SmartWatt helps reduce reliance on fossil fuels and supports cleaner energy adoption worldwide. Additionally, in regions where energy access is limited or expensive, SmartWatt’s optimization algorithms can help households maximize their use of available power, ensuring more efficient distribution of resources. As energy prices fluctuate due to geopolitical and economic factors, SmartWatt provides a scalable, intelligent approach to energy management that benefits users across diverse global contexts.

Part B (written by anyab)

Cultural differences influence energy consumption behaviors, regulations, and sustainability priorities. In Europe, where time-of-use tariffs are common, the system automates energy usage during off-peak hours (we use Nordpool API which provides spot electricity prices in Europe) . In regions with flat-rate pricing, it prioritizes renewable energy and battery storage. These region-specific energy insights make the system adaptable to diverse communities, ensuring relevance and effectiveness. Beyond energy consumption habits, cultural attitudes toward technology and automation play a significant role in system adoption. In regions where smart home technology is widely embraced, users may prefer fully automated energy management, while in areas with privacy concerns or skepticism toward automation, the system can offer manual control options to align with user preferences.

Part C (written by sdoshi2)

Environmental factors play a crucial role in the development of SmartWatt.
It is expressly designed to reduce household energy consumption. By optimizing energy usage and promoting demand-side management, SmartWatt helps lower reliance on fossil fuel-based power generation, which remains a major contributor to greenhouse gas emissions. Additionally, by integrating renewable energy sources such as solar panels, the system encourages sustainable energy practices and reduces strain on non-renewable resources.

We also take into account the fact that the users environment will discate the renewable power production and the power consumption based on climate/weather

Beyond energy reduction, SmartWatt also considers energy efficiency in hardware selection. The sensors and microcontrollers used in the system are also chosen to lower power consumption to ensure that the monitoring and optimization processes do not inadvertently contribute to excessive energy use.

Furthermore, SmartWatt aids in environmental conservation by mitigating energy wastage. By identifying inefficiencies such as poorly insulated spaces, users can make informed decisions to enhance their home’s energy efficiency. This proactive approach not only saves money but also reduces unnecessary energy demand, contributing to a broader reduction in environmental degradation. In regions where power generation relies heavily on coal or other environmentally harmful methods, SmartWatt’s ability to shift energy consumption to cleaner energy sources can make a significant difference in reducing ecological impact.

By addressing these environmental factors, SmartWatt aligns with sustainability goals and contributes to a more energy-efficient future, making it an essential tool for environmentally conscious consumers and policymakers alike.

 

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Team’s Status Report for 02/22/25

Risks

  • Running ML models on Raspberry Pi could cause performance limitations due to limited computing power. To address this, I will optimize models for efficiency and consider offloading computations to an external server.
  • Additionally, compatibility between ML frameworks and Home Assistant might pose challenges.I will validate API integrations using Postman to address this.

Changes

No major changes in implementation/design yet. After trying to deploy the ML model on RPi, if the RPi has limited storage/processing power, will deploy the ML forecasting on a computer.

Progress

  • Automation setup with Home Assistant.
  • Initial implementation of optimization models.
  • Model training and prediction framework.
  • CSV data storage and Docker integration.
  • Nordpool grid price retrieval setup.
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Anya’s Status Report for 02/22/25

Accomplishments this week

Home Assistant Automation Implementation [Integration Platform]

Defined shell commands and set up tasks in config yaml files for data publishing via the HA API

Grid Price Integration from Nordpool

  • Configured retrieval of real-time electricity prices from Nordpool.
  • Integrated Nordpool API into the optimization workflow to factor dynamic pricing.
  • Implemented logic to optimize energy consumption based on real-time grid prices.
  • Instantiated the grid price optimization problem using plp.LP
Challenges & Next Steps
  • Sensor Deployment: I am awaiting final integration of sensors to obtain real-time load consumption data
  • Performance Optimization:  I need to fine-tune the grid pricing model for higher accuracy.
  • Scalability: Need to expand the system to support multiple optimization strategies dynamically.
  • Progress and Schedule
  • Completed foundational tasks and progressing into real-time data collection and optimization refinements.
  • Minor delays in sensor delivery [due to snow storm] could impact the timeline for model training.
  • Action Items for Next Week
    • Deploy sensors and verify real-time data collection.
    • Train models using load consumption data
    • Conduct further tests on the dayahead optimization strategy.
    • Optimize automation workflows in Home Assistant.
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Erika’s Status Report for 2/22/2025

This week, I completed the design of the model house, ensuring it is manufacturable and fulfills all the requirements of our project design, including a variety of loads and a solar panel energy input suitable for energy optimization analysis. I also made significant progress on the user dashboard web app, setting up the basic framework and integrating initial features for visualizing household energy consumption.

I am on schedule with the project timeline. Completing the model house and starting the user dashboard are tasks planned for upcoming weeks, but it is great to get a head start.

Next week, I plan to integrate real-time energy consumption data into the user dashboard. I also aim to enhance the dashboard’s UI to improve user interaction and clarity. Furthermore, I plan to determine additional materials for the model house such as acrylics for walling and small decorations or toys to simulate a real home with active appliances.

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Maya’s Status Report for 2025-02-15

# Progress This Week:
1. **ESP32 Setup and Expansion:**
– Continued setting up the ESP32, refining its configuration and stability.
– Started wiring components to the ESP32 on a breadboard for initial testing.
– Ensured reliable communication between ESP32 and Home Assistant.

2. **Model House Component Selection:**
– Researched and decided on key parts for the model house.
– Selected sensors and actuators for power monitoring and automation.
– Planned the integration of these components into the broader system.

3. **Testing and Initial Wiring:**
– Connected and tested multiple components with the ESP32.
– Began initial wiring to verify sensor functionality and data transmission.
– Identified preliminary wiring challenges and planned solutions.

# Challenges Encountered:
– Verifying compatibility between selected components and the ESP32.
– Managing power distribution effectively to prevent overloading circuits.

# Next Steps:
– Finalize the wiring layout and begin soldering for a more permanent setup.
– Expand testing with additional sensors and actuators for comprehensive data collection.
– Develop automation rules within Home Assistant based on sensor inputs.
– Continue refining power optimization strategies through real-time analysis.

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Erika’s Status Report for 2/15/2025

1. Accomplishments:
This week, I worked on:

  • Design Review Presentation: I created the slides for the following sections:

    • Testing and Verification Methodology: Outlined our approach to validating system accuracy, including sensor calibration tests and data integrity checks.
    • Implementation: I included a visual of what our user dashboard will look like.
    • Project Management: Developed the Gantt chart, task assignments, and bill of materials for the team.
      [Include a screenshot of your slides or the presentation document]

  • User Dashboard Web App: I started building the front end of the user dashboard using Next.js. I implemented the homepage layout and began integrating basic components such as energy usage graphs and a real-time energy savings counter.

This image is serving as the inspiration for my own dashboard.

  • Model House Demo: I designed the layout for our model house, which will be used to showcase SmartWatt’s real-time monitoring capabilities during the demo. I determined the dimensions of each rooms and the placement of each load.

  • Materials Planning: I determined the quantity of wood and acrylic needed to build the model house. I have ordered the wood so I can start laser cutting as needed. However, I plan to wait until later in the semester to assemble the model house since we don’t currently have a large enough storage space.

2. Progress Status:

  • I am currently on schedule with my tasks. The design review slides are complete, and I made significant progress on both the web app and model house design.

3. Goals for Next Week:

  • Web App: Complete the first iteration of the front-end visualizations and user input interface.
  • Model House: Receive the balsa wood and cut each piece to size. I will also order wood glue to assemble the pieces in the future.
  • Design Review Submission: My teammate will present our design review on M/W.