This work proposes a cloud solution to build an Internet of Things (IoT) platform applied in a greenhouse crop production context. Real-time and historical data, as well as prediction models, can be accessed by means of RESTful (Representational State Transfer) web services developed for such a purpose. Forecasting is also provided following a Greenhouse Models as a Service (GMaaS) approach. Currently, our GMaaS tool provides forecasting based on computational models developed for inside climate, crop production and irrigation processes. Traditionally, such models are hardcoded in applications or are embedded in software tools to be used as Decision Support Systems (DSS). However, using a GMaaS approach, models are available as RESTful services to be used as needed. In addition, the proposed platform allows users to register new IoT devices and their greenhouse data in the FIWARE platform, providing a cloud scale solution for the case study. RESTful services of the proposed platform are also used by a web application allowing users to interact easily with the system.