<![CDATA[The advancement of Internet of Things (IoT) technology has opened new opportunities for automated monitoring systems, especially for children with Autism Spectrum Disorder (ASD). These children require intensive supervision due to communication limitations and unpredictable behavior. This study aims to design and implement a smart room system integrated with multi-modal sensors to monitor autistic children's activities in real time.Using a Research and Development (R&D) approach with the ADDIE model, the system was developed with an ESP32 microcontroller and sensors including PIR (motion), DHT22 (temperature), microphone (sound), and LDR (light). The Mamdani fuzzy logic algorithm processes sensor data to classify safety levels. Data is visualized and notified via the Blynk platform.Test results show the system effectively detects "safe," "needs attention," and "critical" conditions with high accuracy, providing timely alerts for parents. This solution enhances home-based supervision and offers a practical, IoT-based approach to child safety and care.]]>
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