IoT-based green house system with splunk data analysis

Abstract

Greenhouse agriculture has the advantage of protecting the plants from outside harsh conditions and providing suitable conditions for plant growth; it can effectively improve the crop yield and quality. But the traditional monitoring/control system of greenhouse construction costs a lot and the traditional control interface is not friendly (some are just manual setting); it is, therefore, not very cost-effective, friendly and high-productive. With the advent of the cloud computing and low-cost Internet-of-Things (IoT) systems, we can apply these low-cost and effective technologies to monitor environment conditions/plant growth and control the facilities. In addition to conveniently monitor/control greenhouse facilities, a real-time platform to dynamically analyzing the collected data can greatly improve the efficiency of greenhouse cultivation, maintenance costs and decision making. In this study, a low-cost greenhouse monitoring system is developed for small-sized and medium-sized greenhouse installations with real-time data analysis. With RethinkDB, raspyberry pi, tornado, and Splunk, we develop an efficient-and-effective greenhouse system to achieve the above goals. This system design acts as a promising solution/bridge toward the final precise agriculture.