- ElectroAuraML is a personal project I am working on currently in its early stages, solely to leverage machine learning to enable human presence detection, ambient condition monitoring, and intelligent environmental control. The goal is to create an adaptable system/systems that enhances comfort, efficiency, and sustainability in various settings using machine learning models.
-
Human Presence Detection: Use machine learning to identify human presence and activities.
-
Real-Time Environmental Monitoring: Measure and analyze ambient conditions such as temperature, humidity, light intensity and other unique sensing mechanisms to acquire useful data for real-time control and analysis.
-
Adaptive Environmental Control: Dynamically adjust environmental settings based on sensed data.
-
Flexible Implementation: Open to various hardware platforms and software tools to suit different use cases.
Develop a modular and scalable architecture for integrating machine learning with environmental control systems.
Ensure systems integration with a wide range of sensors and devices required for implementation.
Provide a framework that supports real-time decision-making and adaptability.
Smart Homes: Automate lighting and HVAC systems based on occupancy and ambient conditions.
Workspaces: Enhance energy efficiency and comfort in office environments.
Agritech: Monitor and optimize environmental conditions for plants or livestock.
This project is in the early stages of its development, and contributions are welcome!
Suggest ideas or improvements via Email.
Share insights or examples for hardware and software integration.
This project is inspired by the potential of combining machine learning with embedded systems to create smarter, more responsive environments. Thanks to the open-source community and researchers within the field for tools and inspiration.