Maximizing the yield in crop production using AI and internet of things

The rapid development of systems using Internet of Things (IoT) for monitoring the parameters are in huge demand and are redesigning the agriculture which is moving the traditional agriculture farming into smart agriculture by reducing the crop wastage and making it cost effective for farmers. IoT dependent monitoring systems are used for monitoring the plant growth which depends on physical conditions such as moisture of, soil, humidity and temperature. Different sensors such as DHT11, DS18B20, LDR, microcontrollers and APIs are used to obtain the data which are essential for plant growth. Further to obtain the detailed analysis of extracted parameters, Machine Learning (ML) algorithms are used. The algorithms such as Logistic regression and Linear Support Vector Classifier (LSVC) are determined to be most suitable for analyzing the physical parameters which are important for growth of plant.