Technological development of a forecasting model production for greenhouse tomato crop production, based on climatic, environmental and greenhouse variables of the area. Validation of the solution and creation of a software prototype as support tool to support for the construction of production agronomic forecasting model. Development of a support system for decision making (DSS) on the climate management, production and cost applied to a polygon greenhouses. It will be used as a simulator to assess climate, agronomically and economically different scenarios.

The aim of the project is the implementation of RFID readers in greenhouses of vegetables. The system shows the works, time and place of each action of each employee. Costs of each action of each crop can be known with this system, so it allows to grant each employee according to the work. This system does not need wiring or complex facilities in greenhouses which are hostile environments for electronic devices, so it makes it cheaper than other solutions and easy to use.

Objectives The goal of this project is to develop protocols for using intelligently-controlled (both intensity and quality), multi-spectrum horticultural LED lighting systems for greenhouse ornamental crop production. There are two main objectives: 1. to reduce supplemental lighting energy consumption in greenhouse production, by optimizing LED supplemental lighting control protocols 2. to improve crop quality by using spectrum modification capabilities of LED technology to manipulate the light quality within the greenhouse environment.

FUL FAISABILITE project propose a model of indoor hydroponically plant growing combining news technologies optimized around concepts of vertical conveying, artificial climate, fluid management, inputs, plant breeding, control of energy and LED lighting to produce an abundance of quality products on non-agricultural soils environmentally responsible way.

MAGESTAN project aims to develop new decision support tools for tomatoes greenhouse to optimize production cycles. Development of these tools will build on the new capabilities offered in modeling the high-performance computing and big data.

In the IMPRESS project partners will realize two (synergistic) products: 1) the FI-sense platform, an open sensor platform that can be used by any sensor producer to receive and transmit data of wireless sensors in greenhouses to FIspace. The platform uses frequencies and protocols that are suitable for greenhouse conditions. 2) The AquaTagRemote soil moisture sensor. The low cost wireless soil moisture sensor will make it possible to control the irrigation based on the real soil moisture conditions.

Abstract The project will deliver the prototype of a new in-line sensing technology for smart real-time management of the nutrient composition within intensive hydroponic, aeroponic and aquaponic farming. The emergence of new growing protocols and batch production techniques, from the process sector, have positioned this approach at the forefront of UK horticultural and exotic fruits production, both reducing the UK's requirement to import such produce and offering category managers a flexible production facility to meet changing consumer preferences.