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@article{200040,
        author = {Badiginchala Chandrika and Boggarapu Navya and Sanchi Chandana and Dr.L.Lakshmi prasanna kumar},
        title = {Smart AI Air Conditioner Controller System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {1317-1319},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200040},
        abstract = {This paper presents a Smart AI Air Conditioner Controller System, an IoT-based solution that transforms any existing split air conditioner into an intelligent, sensor-aware, and remotely managed climate control system. The system employs an ESP32 microcontroller as the edge computing node to collect real-time data from DHT22 (temperature/humidity), INA219 (power monitoring), and PIR (occupancy) sensors. A Python Flask server implements a rule-based decision engine to determine optimal AC operating parameters—on/off state, temperature setpoint, and fan speed—returning control commands via HTTP/REST. Physical actuators include a relay for compressor control and an L293D-driven fan motor with proportional PWM speed control. Telemetry data is logged to CSV for future machine learning model training. Testing over 24 hours demonstrated reliable operation with 8,638/8,640 rows logged successfully, mean HTTP round-trip latency of 8.7 ms, and estimated monthly energy savings of 81 kWh compared to conventional AC systems. The architecture is designed for seamless upgrade from rule-based control to machine learning without hardware or protocol changes.},
        keywords = {IoT; ESP32; Air Conditioner Control; PIR Sensor; Flask Server; Energy Efficiency; PWM; Embedded Systems.},
        month = {May},
        }