Room comfort is critical for enhancing productivity, particularly in classrooms. Two key factors are temperature and lighting, governed by ASHRAE 55 for thermal comfort (PMV range of –0.5 to 0.5) and SNI 6197:2020 for classroom lighting (350 lux). This study develops an intelligent system that coordinates occupant detection with temperature and lighting control. Occupant detection was implemented using the Single Shot MultiBox Detector (SSD) with MobileNetV2, a camera as the sensor, and image processing on an NVIDIA Jetson Nano. The detected occupant coordinates were used to control lighting patterns, while temperature was measured with a DHT22 sensor and regulated through PMV-based calculations. The recommended temperature setpoints were transmitted to an air conditioner via an IR blaster controlled by an ESP8266. Experimental results show that the detection system achieved 95% accuracy, 99% precision, 95% recall, and a 97% F1-score at a threshold of 0.3. The lighting control system achieved a MAPE of 14.49%, while the temperature control system achieved a MAPE of 4.53% with an average MAE of 1.1 °C. These findings demonstrate that the proposed system effectively integrates occupant detection with automated temperature and lighting control, ensuring improved classroom comfort.