To develop and operate an IoT-based Smart Greenhouse Monitoring and Control System, first install environmental sensors such as DHT22 for temperature and humidity, soil moisture probes, and LDRs for light intensity inside the greenhouse to continuously collect data on growing conditions. Connect these sensors to a microcontroller like Arduino Uno and integrate a WiFi module such as ESP8266 or NodeMCU to enable real-time wireless data transmission to an IoT cloud platform for remote monitoring and storage. Once data is available online, analyze it through dashboards or mobile apps to observe trends and make informed decisions. When environmental parameters deviate from optimal levels, the system should automatically trigger actuators—such as fans, sprinklers, or grow lights—to maintain ideal conditions. Throughout the cultivation cycle, data logging and analysis help identify patterns for predictive control and resource optimization, reducing manual intervention and improving crop yield and quality. The system should be operated continuously to maintain stability and can be enhanced over time by adding AI algorithms for predictive adjustments, renewable power sources for sustainability, and scalability to hydroponic or commercial setups, ensuring consistent productivity and energy-efficient farming year-round.
Kamble et al. (Thu,) studied this question.
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