IoT and Machine Learning based approach for Fully Automated Greenhouse

With the rapid evolution of technology, automation has taken over almost all fields of operation. The change in human-computer interaction has accelerated over the years. Greenhouses have come a long way in terms of technological advances. For 100% yields, it is essential to constantly monitor the optimal parameters for plant growth. Here in this work, different parameters that impact the yield of crops like humidity, CO <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf> levels, light intensity, soil moisture, temperature are being monitored, controlled and coordinated using Raspberry Pi and Arduino. Internet of Things has enabled real-time data collection from the Smart Greenhouse and visualization on ThingSpeak platform. This paper proposes a fully automated greenhouse embedded with hydroponics and vertical farming and with excellent security provisions and surveillance to become a highly advanced and diverse version of currently prevailing models.