IoTelligence

• 

  Home Network Health!

Inspiration

We wanted to empower users to truly understand their home network — not just see which devices are connected, but also how much bandwidth and power each device is using. The idea came from realizing how many people today use multiple IoT devices without knowing which ones may be draining bandwidth, slowing performance, or even posing security risks.

Our goal was to make something that felt like “network intelligence” — IoTelligence — giving users clear, actionable insights about their connected ecosystem

What it does

IoTelligence is a smart home network management interface that:

• Displays all connected devices on your T-Mobile 5G or Wi-Fi network
• Monitors bandwidth and power usage for each device
• Alerts users when devices consume excessive bandwidth
• Lets users prioritize important devices or disconnect unfamiliar ones
• Provides an easy-to-read dashboard with real-time visualizations

In short, IoTelligence gives users control, transparency, and security over their home networks.

How we built it

We built IoTelligence using both software and hardware integration for real-time network monitoring.

Backend: Built with Flask in Python to handle data processing and serve the web interface.

Frontend: Created with HTML, CSS, and Bootstrap for a clean, responsive UI.

Visualization: Used Chart.js to display live bandwidth and usage statistics.

API: Integrated Gemini API for intelligent analysis and user recommendations.

Hardware: Deployed on a Raspberry Pi, configured to scan connected devices and measure activity on the network.

Data Handling: Used JSON for real-time data exchange between backend and frontend.

Tech Stack: Python, JavaScript, HTML, CSS | Flask, Bootstrap | Gemini API | Raspberry Pi | Flask + local network integration | Chart.js, JSON for data visualization and parsing

Project Challenges

• Setting up reliable real-time device recognition through Raspberry Pi required fine-tuning network packet capture.
• Balancing the accuracy of bandwidth readings with performance was tricky — polling too frequently slowed down the system.
• Integrating the Gemini API for smart analysis while maintaining local privacy required careful API request handling.
• Designing a clean dashboard that communicates complex data simply was more challenging than we expected!

Accomplishments!

• Built a fully functional, locally hosted IoT dashboard in under 24 hours.
• Successfully integrated AI-driven recommendations into network data visualization.
• Designed an interface that’s both technical and intuitive, empowering users of all experience levels.
• Combined hardware and software to create a seamless smart-home solution.

Takeaways

• We learned how to combine IoT hardware with AI analysis to provide real-world insights.

We also deepened our understanding of:

• Flask app deployment and routing
• Network protocols and packet monitoring
• Frontend responsiveness and UX/UI balance
• Using AI APIs like Gemini effectively in lightweight applications
• One key takeaway: bridging AI with real-time IoT data can make technology more accessible, personal, and empowering.

What's next for IoTelligence

• Expanding device recognition with machine learning classification
• Adding energy-saving recommendations based on usage trends
• Integrating cloud syncing so users can monitor their network remotely
• Developing a mobile-friendly version for on-the-go access

We believe IoTelligence can become a go-to solution for smarter, safer, and more efficient home network management

Built With

• and
• bootstrap-|-gemini-api-|-raspberry-pi-|-flask-+-local-network-integration-|-chart.js
• css-|-flask
• data
• for
• html
• javascript
• json
• parsing
• tech-stack:-python
• visualization