ITISE 2026 - 20 articles
Canaria, Spain | 15–17 July 2026
Volume Editors:
Olga Valenzuela, University of Granada, Granada, Spain
Fernando Rojas, University of Granada, Granada, Spain
Luis Javier Herrera, University of Granada, Granada, Spain
Hector Pomares, University of Granada, Granada, Spain
Ignacio Rojas, University of Granada, Granada, Spain
Regional climate variability arises from the interaction between long-term anthropogenic warming and large-scale atmospheric circulation processes. In particular, the coupling between the Stratospheric Polar Vortex (SPV), jet stream dynamics, and sur...
This work presents a data-driven approach for state-of-charge estimation of rechargeable zinc-air batteries based on electrochemical impedance spectroscopy. Due to the nonlinear electrochemical behavior and flat discharge voltage profile of zinc-air...
This paper reassesses the role of transport logistics and infrastructure in shaping sustainable territorial development in mainland Portugal using an integrated quantitative and spatial approach. In this regard, the work is based on an Absolute Acces...
Fisheries are central to global food security, marine conservation, and the livelihoods of millions worldwide, yet a comprehensive understanding of fishing behavior and effort remains lacking due to the scale of oceanic systems and constraints of tra...
This study develops a machine learning-based spatiotemporal forecasting framework for predicting crash occurrence risk across Alaska transportation systems using integrated weather, roadway, temporal, and spatial datasets. The methodology combines Ge...
The increasing integration of decentralised photovoltaic (PV) systems and electric vehicles into low-voltage (LV) distribution networks introduces significant variability in net-load patterns, exemplified by the “duck curve” (daytime over...
Wastewater treatment plants (WWTPs) are crucial infrastructure. Continuous monitoring of plant conditions using sensor technology has enabled real-time monitoring, forecasting and control. WWTP processes, namely, those occurring in biological reactor...
This work develops and validates machine learning models for short-term electricity demand forecasting under a disaggregated demand setting. The study uses high-resolution historical consumption data, calendar descriptors, and meteorological variable...
This study analyzes nitrogen dioxide (NO2) concentrations in several European capital cities with the aim of assessing the risk of population exposure and comparing pollution levels across urban environments. NO2 is a major air pollutant in Europe, l...
The running-in phase of hermetic reciprocating compressors is characterized by slow, nonstationary changes in operational signals and is commonly assessed using empirically defined test durations or manually defined indicators. From a data-analysis p...
This work evaluates a hybrid harmonic and data-driven approach for short-term sea-level forecasting in the Venice lagoon. The observed sea level is decomposed into an astronomical component, estimated through harmonic analysis, and a non-astronomical...
Continuous glucose monitoring enables Blood Glucose Level (BGL) forecasting, yet current deep learning models face a critical trade-off: general models lack individual accuracy, while personalized models suffer from a severe “cold-start”...
Accurate day-ahead electricity price forecasting is essential for market participants to optimize bidding strategies and manage financial risks in increasingly volatile energy markets. This paper presents a comprehensive web-based system designed for...
This paper investigates the prediction of magnetic fields using an all-optical NV diamond sensing setup combined with neural network models. In contrast to previous work, the focus is placed on the generalization capability of the models across indep...
This work presents a conceptual design and preliminary analysis of a resource-efficient measurement device using nitrogen vacancy centers to measure magnetic fields. The electric current is derived by using the Biot–Savart law. Laboratory instr...
Building thermal performance has become a major concern as global warming intensifies and building energy demand is expected to rise by 30% by 2030. Bio-based construction materials offer a promising solution by improving thermal comfort and reducing...
The building sector accounts for 34% of global energy demand, making accurate short-term load forecasting essential. Small commercial buildings remain challenging due to high-frequency noise and data sparsity. This study proposes a hybrid machine lea...
This paper presents a hybrid ARX-LSTM forecasting framework for the Spanish Continuous Intraday Market (MIC), targeting the hourly volume-weighted average price two hours ahead. A correlation analysis over 2024 data identifies Day-Ahead Market and In...
The power demand of High-Performance Computing (HPC) infrastructures exhibits both stable weekly regularities and rapid workload-driven fluctuations, which are difficult to capture reliably with a single modeling paradigm. Achieving more sustainable...
This paper applies the von Mises family of circular distributions to model seasonal timing of heavy rainfall extremes in Kimberley, South Africa. Unlike conventional modelling approaches that emphasize the modelling of mean rainfall, circular modelli...
