The project aims to create a personalized AI-based application to promote sustainable energy use and reduce electricity consumption in households.
The solution intends to personalize the energy management experience by analyzing usage patterns to recommend actionable tasks and gamification for
user engagement. It gives users insights, automations, and rewards to make environmentally conscious decisions while saving themselves money.
The app targets a very wide range of consumers, from eco-conscious families to higher-tech consumers. Major pain points that this app targets include
confusion in electricity bills, inability to realize energy czars, and a realistic pathway to sustainability plans. The app starts with a very simple
onboarding, which collects data on household environment, appliances, modes of energy, and energy behaviors, creating personalized user profiles. Once
set up, a dashboard displaying energy consumption in real time, forecasts costs, and tracks progress is available. It gives timely notifications and
alerts to users on the needs for maintenance of their appliances and/or spikes in energy use for some unpredictable demand response.
Gamified aspects, providing challenges, leaderboards, and rewards, will encourage users to change their behavior-one of the ways long-term habits can be
achieved. It does so while being very conscious of privacy: its design places accountability fully on users for the sharing of their data, hence building
trust. By integrating AI-driven insights with gamification, the app provided an actionable and engaging pathway toward reduced energy costs in boosting
environmental sustainability, adding to the long-term behavior tree that will benefit the environment. This is one step toward a greener future.
How can AI effectively reduce monthly electricity costs and guide users to adopt sustainable habits with their home appliances through personalized,
actionable recommendations and gamified engagement for families living in typical households?"
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Personalized Energy Insights:
Track and analyze individual energy usage.
Provide tailored recommendations based on user behavior and preferences.
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Gamification & Rewards:
Challenges, leaderboards, and point systems to motivate behavior changes.
Incentives such as discounts and redeemable rewards.
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Automation & Alerts:
Notifications for high-energy usage and appliance maintenance.
Customizable automation for smart home devices (e.g., managing thermostats, lights).
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User-Centric Onboarding:
Gather user details, appliance configurations, and home layouts to create personalized profiles.
Use AI chatbots to capture dynamic user preferences.
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Data Visualization:
Real-time dashboards to monitor energy usage, cost savings, and environmental impact.
Historical data with filters (daily, weekly, monthly).
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Privacy & Security:
Emphasize user control over data sharing to build trust.
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Methodology
Define Audience:
Online Survey via Google Forms to gather the users experience with the prototype / 8 participants. Quantitative data was collected through structured
questionnaires between tasks, complementing the qualitative findings.
User Personas:
Crazy 8s:
Usability Testing:
We conducted qualitative analysis by recording participants' interactions with the prototype to gather insights on its design and usability.
Survey
Online Survey via Google Forms to gather the users experience with the prototype / 8 participants. Quantitative data was collected through structured
questionnaires between tasks, complementing the qualitative findings.
Interviews
Interviews had taken via In-person, Google meet, and phone calls for 8 participates.
Prototyping and Iteration:
Designed high-fidelity prototypes with enhancements. Iteratively improved the prototype based on participant feedback.
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Key Findings
Electricity Usage Patterns:
Peak usage times: before and after work.
Users want detailed data on individual appliance usage to identify unnecessary consumption.
Cost Sensitivity:
Electricity costs in Michigan are acceptable, suggesting alternative motivators beyond cost are needed.
Energy Management and Behavior:
Strong interest in tools that prevent wasteful electricity usage.
Users desire actionable insights for efficient energy use.
Attitudes Toward Technology:
Mixed reactions to AI tools: some are enthusiastic, while others are skeptical.
Need for diverse strategies to address these varied perspectives.
Attitudes Toward Sustainability:
Many participants recognize climate change but lack clear action plans.
Accessibility and affordability of green energy are key to adoption.
Incentives and Rewards:
Motivational strategies like rewards (e.g., discounts) can encourage behavior changes.
Incentives could help sustain long-term energy-saving habits.
User Feedback
Interest in AI Tools: Users are curious about AI-driven energy monitoring but need reassurance on accuracy and usability.
Behavioral Challenges: Forgetting to turn off appliances is common; reminders and actionable insights are needed.
Motivators: Cost savings, sustainability, and rewards (e.g., discounts) are strong motivators for change.
Sustainability Awareness: Users value sustainability but need clear, actionable plans to integrate it into daily routines.
