Unidade de Investigação - CIIC - Computer Science and Communication Research Centre
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- IoT in Greenhouse Supported by Climate Conditions Management PlatformPublication . Galvão, João; Neves, Filipe; Vieira, João; Rafael Simões; Ribeiro, Vânia; Costa, PauloThe system called iMeteo4all is a management platform for several physical variables, inherent to the control and management of climatic conditions inside structures, for the intensive production of plants called greenhouses and to be one contribution for agriculture 4.0. The objective of this work was to design and develop software for monitoring and managing the quality of the internal environment, through successive data collection/readings provided by a network of sensors and process automation for more efficient and sustainable agriculture. Different case studies of greenhouses whose production technologies are distinct, such as aquaponics and soil technologies were considered, in these controlled environment structures to produce plants (edible and non-edible). This platform requires an Internet address to perform the interface among a tablet, a cell phone, a computer and communication systems between a net of IoT (Internet of Things) sensors, which collect climatic variables inherent to growth and connected to several MCUs (Micro Controller Unit). Subsequently, managers and employees will be able to view and interact in real time, making more accurate decisions, depending on the climatic variations inside the greenhouse, increasing efficiency in several areas in greenhouses. It is possible to access the history of each sensor and configure automations according to the collected data. Access to data from this solution is secure through an SSL (Secure Sockets Layer) certificate applied to the public https address. If hardware failures exist, the system is prepared to be restored through regular backups in the cloud and internally, providing users with confidence and robustness in the constant use of this platform.
- A stochastic approach to optimize Maritime pine (Pinus pinaster Ait.) stand management scheduling under fire risk. An application in PortugalPublication . Ferreira, L.; Constantino, M.; Borges, J. G.The paper discusses research aiming at the development of a management scheduling model for even-aged stands that may take into consideration fuel treatments to address the risk of wildfires. A Stochastic dynamic programming (SDP) approach is proposed to determine the policy (e.g. the fuel treatment and thinning schedules and the rotation age) that produces the maximum expected discounted net revenue. Fuel treatment activities encompass shrub cleanings. Emphasis was on combining a deterministic stand-level growth and yield model with wildfire occurrence and damage models to design a SDP network. SDP stages are defined by age and state variables include both the stand basal area and the number of years since the last fuel treatment. Fire occurrence and damage scenarios are addressed at each stage. Results from an application to Maritime pine (Pinus pinaster Ait.) stand management scheduling in Leiria National Forest, Portugal, are presented. Results suggest that the modeling strategy may help assess the impact of wildfire risk on the optimal stand management schedule. They confirm that the maximum expected discounted net revenues decreases. Further, albeit some timber may be salvaged after the wildfire, rotation age also decreases when the risk of fire is considered. Finally, they provide interesting insights about the role of thinning and fuel treatment policies in mitigating risk.