How to Build a Smart Robot Vacuum Scheduler with Room Mapping

Create an innovative smart robot vacuum scheduler that utilizes advanced room mapping technology. This project combines IoT, AI, and user-friendly interfaces to revolutionize home cleaning routines, offering customizable schedules and intelligent navigation for optimal efficiency.

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Simple Summary

A smart robot vacuum scheduler with room mapping capabilities, offering efficient and customizable cleaning routines for modern homes.

Product Requirements Document (PRD)

Goals:

Develop a smart robot vacuum scheduler with room mapping capabilities
Create an intuitive user interface for easy scheduling and control
Implement efficient cleaning algorithms based on room layouts
Ensure compatibility with popular robot vacuum brands

Target Audience:

Homeowners and renters looking for automated cleaning solutions
Tech-savvy individuals interested in smart home devices
Busy professionals seeking time-saving home maintenance tools

Key Features:

Room Mapping: Utilize sensors and AI to create accurate floor plans
Custom Scheduling: Allow users to set specific cleaning times for different rooms
Remote Control: Enable vacuum control via mobile app or web interface
Cleaning History: Track and display past cleaning sessions and coverage
Multi-floor Support: Manage schedules for homes with multiple levels
Voice Assistant Integration: Compatible with popular smart home ecosystems

User Requirements:

Easy setup process for connecting to robot vacuums
Intuitive interface for creating and modifying cleaning schedules
Real-time notifications for cleaning status and completion
Ability to manually override scheduled cleanings
Option to set no-go zones or areas requiring extra attention

User Flows

Initial Setup:
- User installs app and creates account
- App guides user through connecting to robot vacuum
- User initiates room mapping process
- App generates floor plan and suggests cleaning zones
Creating a Cleaning Schedule:
- User selects "New Schedule" in app
- User chooses rooms, days, and times for cleaning
- User sets any specific preferences (e.g., suction power, no-go zones)
- App confirms and activates the new schedule
Monitoring Cleaning Progress:
- User receives notification that cleaning has started
- User opens app to view real-time cleaning map
- User can pause, resume, or end cleaning session
- App provides summary of cleaning session upon completion

Technical Specifications

Frontend: React Native for cross-platform mobile app
Backend: Node.js with Express.js
Database: MongoDB for user data and cleaning histories
Real-time Communication: WebSockets for live updates
AI/Machine Learning: TensorFlow for room mapping and path optimization
IoT Integration: MQTT protocol for communication with robot vacuums
Authentication: JWT for secure user authentication
Cloud Services: AWS for scalable backend hosting
CI/CD: GitHub Actions for automated testing and deployment

API Endpoints

POST /api/users/register
POST /api/users/login
GET /api/rooms
POST /api/rooms/map
GET /api/schedules
POST /api/schedules
PUT /api/schedules/:id
DELETE /api/schedules/:id
POST /api/vacuum/start
POST /api/vacuum/stop
GET /api/cleaning-history

Database Schema

Users:

id: ObjectId
email: String
password: String (hashed)
name: String
createdAt: Date

Rooms:

id: ObjectId
userId: ObjectId
name: String
floorPlan: Object
area: Number

Schedules:

id: ObjectId
userId: ObjectId
roomIds: [ObjectId]
daysOfWeek: [Number]
startTime: String
duration: Number
createdAt: Date

CleaningHistory:

id: ObjectId
userId: ObjectId
scheduleId: ObjectId
startTime: Date
endTime: Date
roomsCleaned: [ObjectId]
coverage: Number

File Structure

/src
  /components
    /RoomMap
    /ScheduleForm
    /VacuumControl
  /screens
    Home.js
    Rooms.js
    Schedules.js
    History.js
    Settings.js
  /services
    api.js
    vacuumConnector.js
    roomMapper.js
  /utils
    dateHelpers.js
    notifications.js
  /redux
    store.js
    /slices
      userSlice.js
      roomsSlice.js
      schedulesSlice.js
  App.js
/server
  /routes
  /controllers
  /models
  /middleware
  server.js
/tests
package.json
README.md

Implementation Plan

Project Setup (1 week)
- Initialize React Native project
- Set up Node.js backend
- Configure MongoDB database
- Implement basic user authentication
Room Mapping Feature (2 weeks)
- Develop algorithm for processing vacuum sensor data
- Create room mapping visualization component
- Implement room editing and labeling features
Scheduling System (2 weeks)
- Build scheduling interface
- Implement recurring schedule logic
- Create notification system for schedule events
Vacuum Control Integration (2 weeks)
- Develop API for communicating with various vacuum models
- Implement real-time control features
- Create cleaning progress visualization
Cleaning History and Reporting (1 week)
- Design and implement cleaning history database schema
- Create reporting and analytics features
User Interface Refinement (1 week)
- Polish UI/UX across all screens
- Implement animations and transitions
- Ensure responsive design for various device sizes
Testing and Bug Fixing (2 weeks)
- Conduct thorough testing of all features
- Address any bugs or performance issues
- Perform security audit
Deployment and Launch Preparation (1 week)
- Set up production environment
- Prepare app store listings
- Create user documentation and support materials

Deployment Strategy

Backend Deployment:
- Deploy Node.js server to AWS Elastic Beanstalk
- Set up MongoDB Atlas for database hosting
- Configure AWS CloudFront for content delivery
Mobile App Deployment:
- Submit iOS app to Apple App Store
- Submit Android app to Google Play Store
- Implement over-the-air updates for future releases
Continuous Integration/Deployment:
- Set up GitHub Actions for automated testing
- Configure automatic deployment to staging environment
- Implement manual approval for production deployments
Monitoring and Maintenance:
- Set up AWS CloudWatch for server monitoring
- Implement error tracking with Sentry
- Establish regular backup schedule for database
Scalability:
- Configure auto-scaling for backend servers
- Implement caching strategies for frequently accessed data
- Optimize database queries for performance

Design Rationale

The design decisions for this smart robot vacuum scheduler prioritize user experience, efficiency, and scalability. React Native was chosen for the frontend to enable cross-platform development, reducing time-to-market. Node.js and MongoDB provide a flexible and scalable backend solution. The room mapping feature utilizes AI to create accurate floor plans, enhancing the vacuum's efficiency. Real-time communication via WebSockets ensures users can monitor and control their vacuums instantly. The modular file structure and use of Redux for state management promote maintainability and ease of future feature additions. AWS services were selected for deployment due to their reliability and scalability, crucial for a IoT-connected application. Overall, this architecture balances modern technology with practical implementation to deliver a robust and user-friendly smart home solution.