Microchip’s EnviroSense AI reference design combines edge AI, multi-sensor monitoring and real-time classification to enable intelligent environmental monitoring without cloud dependence.
Microchip Technology has introduced EnviroSense AI, a reference design that demonstrates how edge artificial intelligence (AI) can enable real-time environmental monitoring using an embedded microcontroller. Built around the PIC32CZ CA90 microcontroller, the solution integrates temperature, humidity and ambient light sensors with on-device machine learning to classify environmental conditions without relying on cloud computing.
The reference design showcases how edge-deployed machine learning models can analyze sensor data locally, reducing latency while improving response times and data privacy. Developed using the MPLAB Machine Learning Development Suite, the system classifies environmental conditions into intuitive categories such as Sunny, Cloudy, Humid, Rainy and Cool Indoor, based on measured temperature, humidity and light intensity. It also identifies time-of-day lighting conditions, including morning, noon, evening and night.
A dual-screen graphical user interface displays both raw sensor readings and classified environmental states, allowing users to compare measured values with AI-generated insights in real time. The design supports smart automation applications such as HVAC optimization, safety alerts and appliance control, where immediate environmental classification can improve operational efficiency and user comfort.
According to the reference design, the platform is intended for rapid prototyping across consumer, industrial and smart infrastructure applications. It demonstrates scalable machine learning integration on standard microcontrollers without requiring a dedicated neural processing unit, making edge AI more accessible for embedded system developers.
The hardware platform is based on the PIC32CZ CA90 Curiosity Ultra Development Board, which features a Cortex-M7 microcontroller with integrated security capabilities and multiple connectivity options. By combining embedded AI, multi-sensor data acquisition and real-time environmental classification in a single solution, EnviroSense AI provides developers with a practical framework for building intelligent, low-latency monitoring systems for next-generation IoT and automation applications.
Click here to review full reference design.
