Senior Movement Alert Kit v6 – AI-Optimized Heating Control for Elderly Care with ESP32

Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.

Create a truly intelligent home system that adapts to the needs of elderly family members. This kit lets you train an ESP32-based Q-learning agent to decide when to turn a heater on or off—using real occupancy data from a PIR sensor and environmental readings from a DHT22. There are no hardcoded rules; the system continuously learns the optimal heating schedule, improving comfort and energy efficiency the more it runs.

What You'll Build

You will assemble an IoT device that monitors motion, temperature, humidity, and exact time of day. The ESP32 runs a reinforcement learning algorithm (Q-learning) that observes patterns and earns rewards for keeping the senior comfortable. The 0.96‑inch OLED displays the current state, while the relay output can control a real heater or a demonstration lamp. With the DS3231 RTC, the system respects time‑based contexts—morning coolness, afternoon warmth, or nighttime vigilance—all automatically learned without a single line of scheduled code.

What You'll Learn

• Deploy a complete Q-learning loop on a low-cost ESP32 microcontroller
• Interface HC-SR501 PIR, DHT22, and DS3231 RTC sensors simultaneously
• Design embedded AI that makes autonomous decisions in elderly care scenarios
• Build adaptive automation that improves its policy through interaction with the environment

Kit Contents

Why Buy This Kit Instead of Sourcing Parts Separately