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Vision-Guided Smart Home Control

Project Overview

Vision-Guided Smart Home Control is an innovative project that combines the power of computer vision with the connectivity of IoT to create a seamless human activity recognition system. Using OpenCV for accurate motion detection and pySerial for IoT integration, ActionSense transforms how environments respond to human actions, enhancing automation and interaction.

Key Features

  • Advanced Human Activity Recognition: Employs OpenCV to detect and classify various human activities in real-time with high precision.
  • IoT Connectivity: Links recognized human activities to IoT devices using pySerial, enabling automated actions and smart responses.
  • Real-Time Performance: Provides instant detection and response, ensuring a dynamic and interactive user experience.
  • Customizable Action-Response Mapping: Allows users to define specific activities and corresponding IoT device responses, offering personalized automation.
  • User-Friendly Interface: Features an intuitive setup and management interface for easy configuration and monitoring.

Technologies Used

  • OpenCV: For robust and efficient human activity recognition.
  • pySerial: For seamless communication and integration with IoT devices.
  • Python: As the primary programming language for developing the system.
  • IoT Devices: Various connected devices to demonstrate the system’s capabilities.

Applications

  • Smart Homes: Automate home devices based on detected human activities, such as turning on lights when someone enters a room.
  • Healthcare Monitoring: Monitor patient movements and trigger alerts or actions in response to specific activities.
  • Security Systems: Enhance security by detecting unusual activities and triggering alarms or notifications.
  • Fitness and Sports: Track and analyze movements for training purposes or interactive fitness applications.

Project Goals

  • Enhance Automation: Improve the responsiveness and intelligence of automated systems through accurate activity recognition.
  • Promote Interaction: Create more interactive environments by connecting human actions to IoT devices.
  • Demonstrate Innovation: Showcase the integration of advanced computer vision with IoT technology in a practical, user-friendly application.

Output

Recognition of action by Model

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IOT Connection to the Recognition Model

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  • Only Fan is working while Sleeping Action is sensed and Lights were off image
  • Light is off for better Vibe and Fan, AC, Tv are on While watching Tv
  • Note: Due to Inavalibility of Ac,Tv for project we replced them with few other lights for use

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Vision-Guided Smart Home Control is an innovative project that combines the power of computer vision with the connectivity of IoT to create a seamless human activity recognition system. Using OpenCV for accurate motion detection and pySerial for IoT integration, ActionSense transforms how environments respond to human actions, enhancing automation.

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