IoT-based Recommender Engine for Yielding Better Crops

Background: Artificial Intelligence (AI) operations have evolved over the last two decades in improvising for an agriculture-based economy. The this area face many challenges maximizing their crop yield while facing like deficient soil treatment, problems from pests and crop-based diseases. Technical requirements of real-time data which can be further transformed to big data. Its impact is fetching low yield, because knowledge gap between farmers technology. These points are key motivators introducing ecosystem with artificial intelligence agriculture research work. IoT devices capable generate large amounts that could into information about environmental parameters temperature field, acts as engine provide All shall collected, stored analyzed better decision-making. One way business uses collected by nourishing it AI systems, grasp use make predictions. Methods: This work enables cater solution supporting IT enabler using analytics on information. It a web application would help monitor fertility suggest producers select best crop(s) grown geographical region. Result: result our recommender successfully predicted we choose grow gardens or farm fields. An extensive study along meteorological models helped us launch smart agricultural system much smarter way. has bridge production quantity yield.