Abstract
In the recent past home automation has been expanding its objectives towards new solutions both inside the smart home and in its outdoor spaces, where several new technologies are available. This work has developed an approach to integrate intelligent microclimatic greenhouse control into integrated home automation. Microclimatic control of greenhouses is a critical issue in agricultural practices, due to often common sudden daily variation of climatic conditions, and to its potentially detrimental effect on plant growth. A greenhouse is a complex thermodynamic system where indoor temperature and relative humidity have to be closely monitored to facilitate plant growth and production. This work shows an adaptive control system tailored to regulate microclimatic conditions in a greenhouse, by using an innovative combination of soft computing applications. In particular, a neural network solution has been proposed in order to forecast the climatic behavior of greenhouse, while a parallel fuzzy scheme approach is carried out in order to adjust the air speed of fan-coil and its temperature. The proposed combined approach provides a better control of greenhouse climatic conditions due to the system’s capability to base instantaneous solutions both on real measured variables and on forecasted climatic change. Several simulation campaigns were carried out to perform accurate neural network and fuzzy schemes, aimed at obtaining respectively a minimum forecasted error value and a more appropriate fuzzification and de-fuzzification process. A Matlab/Simulink solution implemented with a combined approach and its relevant obtained performance is also shown in present study, demonstrating that through controlled parameters it will be possible to maintain a better level of indoor climatic conditions. In the present work we prove how with a forecast of outside temperature at the next time-instant and rule-based controller monitoring of cooling or heating air temperatures and air velocities of devices that regulate the indoor micro-climate inside, a better adjustment of the conditions of comfort for crops is achievable.
Highlights
A home control system (HCS) is a tool to monitor and manage the main features of a residential home to improve its general efficiency and reduce its environmental impact
The NNARX models have been created by varying both the number of input parameters and the number of hidden layer neurons, through a sensitivity analysis it was chosen the network with the best performance
The approach shows a couple of fuzzy logic controller (FLC) fed by a climatic temperature predictor
Summary
A home control system (HCS) is a tool to monitor and manage the main features of a residential home to improve its general efficiency and reduce its environmental impact. HCS serves three main functions: security and safety monitoring; efficiency of space heating/cooling, water heating and lighting; and monitoring external environment and weather. An important aspect is represented by the control of outdoor environment in terms of home security, garden or sunroom management, external lighting, etc. A significant amount of literature has been produced in the field of architectural design of gardens. In cases of limited outdoor space, vertical gardens and home-grown for-food cultures have recently attracted significant attention. The use of greenhouses for Energies 2017, 10, 722; doi:10.3390/en10050722 www.mdpi.com/journal/energies
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