Pablo David Campillo (Answare S.A.)
Tutorial on Intelligent Agriculture Environments thanks to Serverless and Cloud Object Storage Technologies using GeoSpatial Data Processing in Python. In this tutorial we will explain how comparing water use estimates obtained from two different databases over extended regions of irrigated crop fields, we will map differences in the water use footprint of irrigated arable lands in representative large areas of Peninsular Spain. On the one side, with high-resolution NDVI index, derived from multi-temporal imagery from Sentinel 2 MSI sensor, we will identify actual irrigated crop areas and will estimate water consumption using multi-date imagery data along the growing season. Mapping these variations along a certain period of time with frequent updates will be only possible due to the continuous update of open-access databases and the utilization of computing continuum capabilities. On the other side, we will estimate and map water consumption indicators considering the officially declared and georeferenced irrigated arable land area which is available from SIGPAC, the Agricultural Common Policy open access database and specific correction factors (irrigated land area and crop water consumption volume). The comparison of both results will identify non-coincident areas which would help to monitor water use efficiency and funding resource allocation.
Assoc. Prof. Sofia Ouhbi (United Arab Emirates University, UAE)
Towards Value co-Creation in Intelligent Environments. In this tutorial will cover how to consider end-users’ perspective in early stages of co-design with a special emphasis on Service-Dominant (S-D) logic and the value co-creation process.
PhD candidate Mario Quinde (Universidad de Piura, Peru)
ADAPTing context-aware solutions for personalised asthma management. This tutorial aims to show the lessons learned from a research project that studied the use of mobile technology to support people with asthma in the management of their condition. The topic is studied from an Intelligent Environments perspective, with a special focus on context-aware reasoning leading to the creation of the Approach to Develop context-Aware solutions for Personalised asthma managemenT (ADAPT).
Assoc. Prof. Georgios Dafoulas and Assoc. Lecturer. Ariadni Tsiakara (Middlesex University, UK)
Learning analytics – Using visual analytics with data from smart. This tutorial will briefly describe aspects of the Tableau platform and how visual analytics can be used in the education sector. Emphasis will be given on sharing good practice of how learning analytics were used to produce dashboards representing emerging patterns of behaviour, and activity. The tutorial will be based on data collected using an intelligent learning environment utilising augmented reality tools, biometric sensors, emotion detection mechanisms and collaborative technologies.
Assist. Prof. Pedro Moura (University of Coimbra, Portugal) and Assist. Prof. Gregorio López (Comillas Pontifical University ICAI-ICADE, Spain)
Energy Management in Intelligent Buildings. This tutorial provides the main guidelines for the optimization of energy management in smart buildings. The main goals and requirements from the energy perspective will be analysed, and the role that ICT plays to achieve such goals and meet such requirements will be discussed. Buildings are the foundation and endpoint of the electric delivery system. Nowadays, buildings are no longer just a passive component of the system, but are a crucial active component ensuring local generation (mainly with solar photovoltaics) and demand flexibility. The matching between the demand and generation in buildings should be high in order to avoid the technical and economic disadvantages of injecting a large share of the local generation into the grid. Therefore, the use of new resources such as energy storage or load management technologies is fundamental to ensure the required flexibility levels. Particularly, in large commercial and public buildings, there is a high potential to control thermal loads (such as the HVAC system) or the charging of electric vehicles (EVs) to provide flexibility to ensure the building optimization. However, in such buildings, not all resources belong to the building (e.g. the parked EVs) and the load control may affect users’ comfort levels. Therefore, energy management must take into account the objectives and preferences of different stakeholders, being fundamental the implementation of innovative optimization methods. The availability of new options of sensors and actuators, as well as Machine-to-Machine communication technologies ensure the required information to implement optimized energy management while taking into account cybersecurity and privacy restrictions. Simultaneously, artificial intelligence techniques allow the design of smart buildings capable of proactively ensure intelligent environments in complex systems such as large buildings.