Skip to content

Latest commit

 

History

History
43 lines (28 loc) · 1.77 KB

README.md

File metadata and controls

43 lines (28 loc) · 1.77 KB

Overview

image

The Smart HomeGuard Project offers a cutting-edge home security solution integrating an Android app with cloud-based machine learning for real-time surveillance and intruder detection.

Key Components

  • Android App: User interface for surveillance, alerts, and control.
  • Machine Learning Models: Intruder and object classification.
  • Cloud-Based API: Hosting and communication of machine learning models.
  • Tech Integration: Utilizes Jetpack Compose, Coroutines, Room, Retrofit, and Work Manager.

Animated Overview

Smart HomeGuard Animation

Core Features

  1. Real-Time Surveillance: Live feed and immediate alerts on potential threats.
  2. User Authentication: Secure login to access app features.
  3. Data Communication: Seamless cloud interaction for data analysis and storage.
  4. Scheduled Updates: Regular checks and updates through background task scheduling.

Development Milestones

  • UI Development: Designing an intuitive interface with Jetpack Compose.
  • Machine Learning Integration: Implementing accurate detection models.
  • Cloud Infrastructure: Establishing robust cloud connectivity for model hosting.
  • Comprehensive Testing: Ensuring reliability and efficiency across systems.

Future Goals

  • Revolutionize home security with advanced technology.
  • Achieve seamless integration for real-time monitoring and detection.

Demo

Coming Soon!


For more information on deployment and usage, please refer to our comprehensive user documentation. Stay tuned for updates on this innovative security solution!