Abstract
A fuzzy identification model and fuzzy logic controller was developed aiming the environmental control of an agriculture greenhouse. The fuzzy identification of the process was performed by the analysis of the data collected either during normal operation, as well in reaction to random generated actuating signals on the heating, ventilation and CO2 injection systems. A comparative study has been realized between fuzzy and physical models. Using the fuzzy model it was possible to implement an accurate Generalized Predictive Control (GPC) strategy in order to regulate the environment and to minimize energy consumption. The optimal setpoints were computed by means of balancing the benefits associated with the marketable produce against the costs associated with its production. The calculations use growth, photosynthesis and climate models. This work describes the practical development of an fuzzy controller that memorize the optimal strategy, executed by the GPC, to regulate the temperature and the CO2 concentration of the greenhouse inside air.

Abstract
The recent new developments in hardware and software tools, and in particular of the microprocessors and microcontrollers, are leading to more complex control and management potentialities in the agriculture applications. For the quality and productivity improvement of greenhouse crops it is necessary to measure and control several interacting physical variables. Also, to achieve competitiveness in the market, the production costs must be kept as low as possible. These tasks can only be accomplished using control and management systems with adequate built in software. At the University of Tras-os-Montes and Alto Douro, Vila Real, a data acquisition and control network was implemented with the aim of being applied to agricultural processes. This network has three main operating levels. At the lower level, a set of remote microcontroller stations performs the data acquisition and transmission by radio frequency to a collecting and control station. The control station generates the actuating signals for the agricultural process and communicates with a higher level network, based on PC's. This higher level network is responsible for the system management and supervision. In this paper it will be described the implemented network and the results achieved in its application to the greenhouse environmental and control.

Abstract
For a greenhouse located at UTAD-University, the methods used to estimate in real-time the parameters of the inside air temperature model will be described. The structure and the parameters of the climate discrete-time dynamic model were previously identified using data acquired during two different periods of the year. Several experiments showed that the second-order models identified achieve a close agreement between simulated and experimental data. Afterwards it has been found that parameters change with varying operational conditions. Thus, for a efficient use of these models in real-time control a recursive identification technique for the estimation of the parameters was implemented.

Abstract
This paper describes the implementation of a distributed data acquisition network based on the 80C592 microcontroller from Intel. Each Station is connected in a hierarchical way to form a tree topology. The lower level network stations, designated by Slaves, are dedicate to the data acquisition and the generation of control signals. The upper level, Masters, are responsible for the communications control. Both networks uses a CAN - Controller Area Network - Bus, for Data Transferring, and the global Network is also connected to a PC, via CAN. A device router, NetManager, was implemented to support total intrinsic requirements at the communication level. This type of connection allows total configuration from a personal computer, PC, in which runs a software application developed for Windows(TM) environments. The tests performed at the laboratory, with transmission rates varying from 40Kbits/s to 1Mbits/s, showed that the communications were performed without errors for cable lengths of 1100m to 40m, respectively. This system is now being installed in a set of environmental chambers and greenhouses located on UTAD, where it will be monitored and controlled the air temperatures and humidities, the CO2 and ammonia concentrations and the radiation level.

Abstract
A soil moisture sensor (SMS) was built around RISC-like microcontroller and common peripherals to perform data acquisition, signal processing, configuration, fault-detection and data communication with a control/management system. The SMS employs capacitance and heat-pulse techniques to determine the soil water content. The sensor uses the capacitance technique as the main method while the heat-pulse readings, acquired at a lower rate, are used for calibration and fault detection purposes. The temperature sensors and the heater were assembled in a four-needle probe. Several experiments were conducted for different types of soil. The results showed that this sensor could be applied in an effective way to measure the soil water content. Several tests are being performed to conclude about the sensor dependence with soil temperature and chemical composition as well about its long-term stability.

Abstract
This work presents an on-chip silicon bulk-micromachined Soil Moisture Sensor (SMS) suited for irrigation control and management applications. The same basic fabrication concepts and materials, which made microelectronics successful, are now being adapted to making low-cost, small, high-performance sensor systems with integrated electronics on the same chip. As a result, this system-on-a-chip includes the SMS, readout electronics, self-test, calibration facilities and a digital bus interface for external data transmission, Moreover, since this sensor has low-cost, it could be employed several sensors networked together with the 1-wire bus, to achieve an accurate measure of the soil moisture at the plant root level. A heat-pulse technique is used (for measuring the maximum temperature on a distant point) to determine the volumetric heat capacity and hence the water content of a porous media, such as soil. This method is based on the Joule effect (heater probe shank) and in Seebeck effect (thermopile - temperature probe shank). The heater and the thermopile are suspended on a dielectric window to reduce undesired heat conduction to the substrate (silicon is a good heat conductor). Thermal simulations of the bulk-micromachined SMS are performed to test sensor performance. In order to validate the method, simulations are made and experimental results were achieved with a macrosensor based on this technique. The results were compared with the measurements performed by the conventional thermo-gravimetric method.