Spain is well known for its Mediterranean climate, characterized by high temperatures and low precipitation, particularly during summer. These features attract many tourists every year that choose Spain as holiday destination to enjoy its sunny beaches, vibrant cultural experiences and outdoor activities. Unfortunately, this climate is not only perfect for tourism but also fosters conditions that can lead to the outbreak of wildfires. And guess what? The increasing heatwaves and prolonged dry spells, caused by climate change, aggravate the work of the firefighters who need more resources to extinguish the fires.
Spain’s Fiery Stats: Where do we stand?
In 2023, the European Forest Fire Information System (EFFIS) ) estimated that around 91,000 ha of forest area were burnt. That’s like burning through the size of nearly 130,000 soccer fields! By using EFFIS data, it was possible to compare the surface of burnt area in several EU countries. The outcomes of this comparison are that, in 2023, Spain was the third country with most burnt area just after Greece (174,773 ha) and Italy (97984 ha). It is relevant to notice that Greece, Italy and Spain present similar climatic conditions, characterized by high temperatures and low precipitation.
Statistics from burned Spanish areas. Source: EFFIS
And here’s the kicker: in 2024, the flames have already gobbled up 37,000 hectares, putting Spain ahead of other Mediterranean countries. The recent Andújar wildfire in Jaén (Andalusia) alone scorched 835 ha of area that usually hosts an extensive variety of flora and fauna.
Hot zones: Where wildfires hit the hardest in Spain
Not all of Spain is equally flammable, but some regions are definitely more fire-prone. Andalusia frequently experiences wildfires, particularly in areas with dense forests and shrubland. Remember the Sierra Bermeja fire in 2021? It was one of the worst wildfires in years. Cataluña, especially near the Pyrenees, also faces frequent wildfires, like the intense blazes during the scorching summer of 2022. And let’s not forget Galicia in the northwest, where wildfires regularly sweep through rural and forested areas.
Source: Elordenmundial.com
What’s fuelling the flames?
Humans, of course! Whether it’s a careless camper, an arsonist, or a farmer burning fields, we’re often the ones lighting the match. But climate change effects are also major catalysts for wildfires. Rising temperatures, causing increased heat and dryness that make the vegetation more susceptible to ignition by reducing their moisture. Shifting precipitation patterns, which mean more drought frequency, making vegetation more prone to catch fire.
And don’t forget extreme weather events such as wild storms, that can produce lightings and thereby increasing the likelihood of natural ignition, while strong winds fan the flames, compromising the control of the fires, and making them spread.
The aftermath: What’s at stake?
When wildfires rage, the damage is not just environmental, it is economic and social, too. Forests and natural habitats are destroyed with the related loss of biodiversity, soil degradation, and increased carbon emissions is a direct consequence of wildfires on the environment. Economically, the destruction of homes, infrastructure, and agricultural lands hits communities hard. Tourism, a lifeline for many regions, can also be severely affected. And let’s not overlook the health risks. Wildfire smoke can affect vulnerable populations like the elderly and those with respiratory conditions, leading to respiratory illnesses and other health issues after a prolonged exposure.
Fighting fire with strategy and innovation
Battling wildfires is not just about putting out flames; it is about being smart before they even start. That means investing in research to understand fire behavior and the impacts of climate change, developing new firefighting technologies, and educating the civilians to increase public awareness on this matter.
The Spanish government is also stepping up with strategies and solutions to mitigate the risks of wildfires and adapt to the challenges posed by a changing climate that can worsen these risks like better land management practices (e.g. clearing vegetation and creation of firebreaks), reforestation with fire-resistant species, and enhancement of early warning systems. Moreover, the implementation of a well-organized firefighting system including brigades, aerial units and military units is essential to quickly control wildfires. Additionally, the European Union supports Spain through the European Civil Protection Pool, providing further resources to fight extensive wildfire.
CARTIF’s contributions to address fire risks in Spanish regions
RethinkAction, project led by CARTIF comprises the Almería province in Andalusia as one of its case studies. The project collects information on the area (e.g. historical and future values of climate variables), assesses the potential climate-related risks and creates risk maps. These maps provide useful insights on the risk of drought, heatwaves and storm in each municipality of the province and each vulnerable sector that can be exposed to these risks such as agriculture, tourism, water management and biodiversity.
Furthermore, CARTIF participates to the NEVERMORE project. This project includes the Region Murcia as case study. A climate-related risk assessment is performed also for this region and a map highlighting the most affected municipalities is produced. Such as the RethinkAction project, the NEVERMORE project provides relevant information not only on the most affected municipalities but also on the most vulnerable sectors involved. Knowing the municipalities with high probability to be affected by climate change is incredibly relevant for the prevention of fires, to identifying the missing resources that are necessary to contain possible outbreaks.
Refreshing your memory, in the previous blog “Talking about everything visible and invisible (I)” we briefly told you about the digital technologies and techniques used to inspect, document and analyze Cultural Heritage in the visible range (the one that our eyes capture). It is now time to tell you about the complementary technologies and techniques that work in other ranges where our eye does not see (the invisible), allowing us to know about composition, history and conservation needs. Here they are:
X-ray techniques: X-ray radiography and X-ray fluorescence (XRF) imaging are helpful in examining the internal structures and material composition of cultural heritage objects. These methods aid uncover hidden layers and construction details that are vital for restoration and conservation efforts.
Source: rxpatrimonio.com
Infrared (IR) imaging: near-infrared (NIR) reflectography, infrared thermography, and infrared spectroscopy are used to analyse pigments, identify underdrawings or alterations, and study the degradation of materials. This provides a deeper understanding of the original techniques used by the artists and the changes that the objects have undergone over time.
Ultraviolet (UV) imaging: is utilized to highlight the fluorescent properties and surface details of objects. This technique reveals hidden markings, retouching, and other modifications that are not visible under standard lighting conditions, offering insights into previous restoration efforts and the object’s history.
Microscopic analysis: employing optical and electron microscopy allows for the detailed examination of minute features, such as pigments, fibres, and inclusions. Microscopic analysis is crucial in the study of material structures and degradation processes at a microscale level.
Source: «La microscopía en el estudio del biodeterioro y la conservación del patrimonio histórico y cultural». Ana M. García https://oa.upm.es/20369/
Spectroscopic techniques: methods like Raman spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and X-ray spectroscopy provide detailed information about the molecular and elemental makeup of cultural heritage objects. These techniques are essential for identifying pigments, analysing organic materials, and detecting changes related to aging and degradation.
Chemical analysis techniques: gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) are used to identify and characterize organic compounds present on cultural heritage objects. These techniques allow understanding the material composition and the degradation processes, definitely aiding in developing appropriate conservation strategies.
Non-Destructive Testing (NDT) techniques: computed tomography (CT) scanning, THz imaging, and ultrasound, are crucial for investigating the internal structure and condition of cultural heritage objects without causing any damage. These techniques reveal hidden features, assess structural integrity, and identify potential defects.
Although X-ray imaging can penetrate deeper and through denser materials, and also generally provides higher resolution images than THz imaging, this last is particularly safe for organic materials as it does not involve ionizing radiation (unlike X-rays, which require strict safety protocols to prevent damage to sensitive historical objects). THz imaging provides excellent material contrast for organic and composite materials, leading to a growing demand due to its effectiveness in non-destructive testing.
THz imaging is scarcely widespread throughout the EU but it is primarily found in technologically advanced research institutions, major museums, and specialized conservation labs. CARTIF is fortunate to have a dual-source THz system (100 GHz and 280 GHz) making it the proper partner in supporting museums and any kind of cultural institutions in art conservation and materials science.
THz imaging by CARTIF to provide information about the composition and layering of a parchment: real gold-leaf is clearly differentiated from other materials, such as adhesives, pigments, or underlying substrates.
Additional multimodal analysis methods should be considered to include a temporal dimension, keeping track of the evolution of features and phenomena over time. It implies the integration of data acquisitions from different visible /non-visible technologies into complex data structures that provide new analysis opportunities for scientists, conservators and curators. This requires advanced data processing and visualization tools that act as virtual environments for precise exploration, allowing to fully explore the always complex cultural heritage objects.
Collaborative platforms are essential for sharing and integrating digitized visible and non-visible data in this context, facilitating global cooperation among researchers, conservators and curators and also enhancing the collective understanding and preservation of cultural heritage.
The world is moving towards a future without fossil fuels, and this transformation is already underway. Fossil fuels, which have been the main source of energy for more than a century, are in decline for reasons of both environmental sustainability and limited availability1.
The PNIEC (National Integrated Energy and Climate Plan 2021-2030) stipulates that by 2030, 42% of the final energy consumed must come from renewable sources. To reach this objective, 27% of this final energy must be electricity, mostly generated from renewable sources (with a goal of 74%). This will involve the installation of more than 55GW of additional renewable generation capacity. This increase in the share of renewables in our energy mix raises new technical issues, as renewables, by their nature, are intermittent and less predictable compared to traditional energy sources. This can lead to inestabilities in the electricity grid, manifesting themselves as congestion and voltage variations.
On the demand side, the energy transition will also require an increase in the electrification of energy consumption, especially in the transport and air conditioning sectors, as well as in some industrial demands.
For the electric system, this will result in an increase in electricity demand and a transition from a traditional, flexible and highly predictable centralised generation system, with passive consumers and distribution networks, to predominantly renewable, decentralised and intermittent generation system, with managable demand resources and an increasing need for flexibility to ensure efficient levels of quality and safety..
The flexibility of a power system is defined by its ability to adapt to imbalances between generated and consumed power. Failure to meet this condition can lead to system and, therefore, on the supply. Till today, the flexibility of our system has being mainly proportionated by fossil generation plants, that equilibrates the generation of existent demand, maintaining a controlled growth of the electric demand. However, at the energy transition context, this change for several reasons:
The flexibility of a power system is defined by its ability to adapt to imbalances between generated and consumed power
The main renewable generation sources (solar and wind) do not have the capacity to “keep up” with demand.
When the transmission capacity of power lines is exceeded by demand, congestion arises, leading to overloads and supply failures.
When the quantity of power generated doesn´t match the real-time demand, voltage variations occur, affecting the quality of the power supply and potentially damaging equipment and appliances connected to the grid.
The electrification process entails a significant increase in consumption on transmission and distribution lines, which must be adapted to this increase in demand, especially during consumption peaks. Adapting these infrastructures exclusively through the repowering of lines or the installation of additional lines would have a very high material and economi cost.
The current model of renewable energy integration is associated with more decentralised generation, wich means that flexibility suppliers will also be increasingly distributed across distribution networks.
Although electricity storage offers high system flexibility, its high cost, especially in pre-metered systems, makes it necessary to consider additional sources of demand flexibility.
For all of these reasons, it is considered critical to favour and promote demand flexibility. This can be done implicitly, through incentives for users to change their consumption habits, for example, price signals, and also explicitly, where the activation of flexibility is direct and with a shorter-term response. An example of this second case is balancing services.
On the other hand, grid instability, resulting from the high share of renewables in a decentralised scheme, can be addressed through participation in local flexibility markets, which allow consumers and small generators to offer consumption and generation adjustment services, helping to stabilise the grid.
In the ENFLATE project, CARTIF is developing a flexibility management tool that helps the network operator to manage distribution networks by simulating scenarios representing participation in local flexibility markets. In is also possible to simulate the provision of balancing services for the transmission grid operator. These services are studied on the electricity netowrk of Láchar (Granada), operated by the partner CUERVA.
In Spain there is still no regulatory framework for local flexibility markets, so the European framework is used. The minimum size of flexibility offered in the local flexibility markets considered in the ENFLATE project is of 0.1MWh and the trading period is one hour. The two products offered are: surge management and congestion management.
Balancing services are offered in the balancing markets. There are three possible services: primary regulation, secondary regulation and tertiary regulation. In ENFLATE we simulate the last one, also known as manual actuation reserve for frequency. It allows offering 1MW to be bid and the trading period is from 15 minutes to two hours.
ADAION is another partner providing digitisation services on the demonstrator. Its cloud-based platform uses artificial intelligence to simulate and know the capacity of the network at all times. It provides the necessary inputs to the algorithm developed by CARTIF, so that participation in both markets can be simulated. Renewable generation, flexible demand and electric storage.
Thanks to projects such as ENFLATE, we can study the scope and benefits of using demand flexibility in real demonstrators such as the Láchar grid, simulating flexibility and balancing market conditions. In this way, we prepare for the challenges of the energy transition. At national level, the current regulatory framework for demand-side flexibility is underdeveloped and scatteres in various regulations, which have gradually been modified with the aim of transposing the European Directives. While they are being consolidated, we preparing for change with projects financed by the European Commission, as in the case of ENFLATE2.
The construction industry is undergoing a quiet revolution. While cranes and excavators continue to take centre stage on construction sites, a new type of worker is gaining ground: collaborative robots, or “cobots”. These efficient helpers will transform the way we construct and rehabilitate buildings. But what exactly are they and how can they change the rules of the game?
Cobots: More than simple machines
Unlike traditional industrial robots, cobots are designed to work side by side (or rather, arm in arm) with humans. These robots are equipped with sensors that allow them to detect the presence of people and objects in their environment. In this way, they can adapt their movement and strength to work safely alongside human workers. In the field of construction, these robots can be of great help, especially in the heaviest, most repetitive and dangerous tasks.
Façade rehabilitation: a new approach
Façade rehabilitation is an area where cobots can be of particular value. These tasks are often labour-intensive, dangerous and require high precision. There are several tasks where these devices could be of great use.
Inspection: Equipped with high-resolution cameras and sensors, the cobots can examine every inch of a façade in detail, detecting cracks, dampness or flaws that might go unnoticed by the human eye.
Cleaning: Specialised robots can clean façades efficiently and uniformly, without putting scaffolding workers at risk.
Application of materials: Whether it is paint, sealants or coatings, cobots can apply materials with high precision and consistency. In addition, material waste is significantly reduced, as they would use the exact amount needed in each case.
Repairs: Some advance cobots can perfom minor repairs, such as filling cracks or replacing deteriorated elements.
3D Printing: 3D printing using cobots makes it possible to create intricate shapes and patterns that would be extremely difficult or costly to achieve with traditional methods. In this way, each façade can be unique, perfectly adapted to the aesthetic and functional needs of the building and its surroundings. In addition, it is possible to directly print elements such as thermal or acoustic insulation within the façade structure. In this context, European projects in which CARTIF collaborates, such as INPERSO, are actively working on the integration of cobots for the rehabilitationf and 3D printing of façades.
Profit beyond efficiency
The intorduction of cobots in façade renovation not only improves the efficiency and quality of work, but also brings other benefits. In the area of safety, for example, by performing the most dangerous tasks, cobots significantly reduce the risk of occupational accidents. They also help in sustainability by optimising the application of the requires amount of material and thus reducing waste. Finally, they also facilitate traceability and documentation of the work performed. The data collected during robotic inspections provides a valuable digital record of the building´s condition.
Challenges and considerations
Despite their potential, the use of collaborative robots in construction still faces some challenges. One of them is related to existing regulations. Building regulations need to be adapted to include this new technology. This problem is common in many areas where innovations are ahead of regulations. Research is also needed on the long-term performance of the new materials associated with these techniques and the durability of the structures created. Finally, the initial costs of these robotic systems need to be considered. Although it may be cheaper in the long term, the initial investment in this technology canbe significant and requires a payback time that needs to be assessed.
Human factor
Despite all these advances, it is important to remember that cobots aren´t here to replace human workers, but to complement them. Construction professionals are still essential for planning, decision-making and tasks that require a human touch and creativity. One of the goals of using such robots is to free workers from the heaviest, most repetitive and dangerous tasks.
Looking to the future
As technology advances, we can expect to see even more sophisticated cobots on our construction sites. Imagine robots that can communicate with each other to coordinate complex tasks, or use artificial intelligence to adapt their working methods to the specific conditions of each building. Human-robot collaboration in building construction and renovation is not just a passing trend, but the future of the industry. With every façade rehabilitated and every building constructed, cobots are proving their worth, moving towards a more sustainable and safer future for the construction industry. These technologies can not only change the way we build, but also how we conceive the function and design of buildings. As technology advances, we can expect to see buildings that are not just structures, but truly functional and sustainable works of art.
Over the past decades, hydrogen has been identified as a potential clean fuel, although its mass adoption has been hampered by the abundance of oil and low relative prices of fossil fuels, as well as, in recent years, by the advance of the battery electric vehicle. Today, while technological advances have brought down the costs of hydrogen production and use, it is essential to scale up these technologies and define a roadmap to optimise the necessary investments. The current energy transition points to an era of sustainable energy gases, and the consumption of renewable hydrogen and methane is expected to surpass that of coal and oil in the 21st century. In this context, renewable hydrogen, or hydrogen produced with low CO2 emissions, emerges as a key player in the decarbonisation of the global economy.
Biohydrogen is a specific type of renewable hydrogen defined as hydrogen produced by biological processes or from biomass as feedstock. Biomass, one of the most abundant renewable resources on all continents, is the subject of increasing research into its alternative uses and valorisation. This interest is also focused on the conversation of waste streams into energy, because of the potential to transform large quantities of agricultural, forestry, industrial and municipal waste into biohydrogen and other renewable gases, thus benefiting sustainable development. The efficient use of renewable feedstocks derived from biomass and waste as a fuel source clearly presents a significant opportunity for a more sustainable planet.
“Biohydrogen. Specific type of renewable hydrogen defined as hydrogen produced by biological processes or from biomass as feedstock”
Biohydrogen has characteristics that make it a renewable element capable of providing safe, economically competitive and 100% carbone dioxide-free energy in its production and use. Despite this, the penetration of this low-carbon hydrogen remains limited. It is crucial to understand the reasons for this situation, the emerging trends and the technological route that will enable its consolidation as an energy vector.
Biohydrogen production
Biohydrogen production has gained worldwide attention due to its potential to become an inexhaustible, low-cost, renewable source of clean energy. Feedstocks for its production include lignocellulosic products, agricultural residues, food processing residues, aquatic plants and algae, and human effluents such as sewage sludge. Under proper control, these resources will become a major source of energy in the future. Biomass has the potential to be an important source of renewable hydrogen, complementing other processes that produce biomaterials.
The main methode of obtaining biohydrogen is from biomethane generated in anaerobic digestion, through a process known as reforming. Gasification, on the other hand, converts organic matter into hydrogen-rich synthesis gas. Alongside these thermochemical technologies, biological hydrogen production, such as dark fermentation and the use of microalgae, offer additional promising methods. Dark fermentation uses anaerobic bacteria to break down organic matter and produce hydrogen. Microalgae, on the other hand, can generate hydrogen through biophotolysis, a process that converts sunlight and water into hydrogen and oxygen. This set of technologies presents a wide range of possibilities for biohydrogen production.
Storage and distribution
The storage and distribution of hydrogen in general, and biohydrogen in particular, represent crucial aspects of its large-scale adoption. Storage in high-pressure tanks is currently the preferred option, although other methods exist, such as injection into existing gas infrastructure of storage in chemical materials. Hydrogen can be stored in a gaseous or liquid state, either on the surface or in solids, or in hydrogen-bearing chemical compounds. These storage options aim to overcome current limitations and facilitate the uptake of hydrogen as an energy carrier.
Applications and uses
The current interest in the hydrogen economy is due to its enormous opportunities for penetration in the energy sector, especially in mobility and chemicalstorage of renewable energy. In the case of biohydrogen, it is also an efficient method of managing organic waste streams. The production of renewable hydrogen has increased in recent years, mainly used in the manufactureof ammonia. Renewable ammonia can also be used as an energy storage medium, energy carrier or fuel. Hydrogen production therefore not only has industrial applications, but also offers innovative energy solutions.
In metallurgy, hydrogen is used in the direct reduction of iron for steel production, and in transport, it can generate clean energy in vehicles. These diversified applications demonstrate the potential of biohydrogen to transform key sectors of the economy. However, its large-scale adoption requires overcoming technological, logistical and market barriers, as well as establishing appropriate policies for its regulation and development.
Biohydrogen perspectives
Biohydrogen, like other energy carriers, has advantages and disadvantages. While other forms of energy already have an established position, hydrogen, and in particular biohydrogen, is progressively advancing in trying to replace options such as coal or natural gas in sectors such as energy, industry and transport. The main driver for this is the need to reduce pollutant emissions, which has generated considerable interest in this energy vector. However, low energy density, infrastructure and installation costs, and factors associated with security are the main barriers slowing down its implementation. While some of these barriers can be removed by cost reductions resulting from research breakthroughs, others, such as energy density, cannot be changed. Here, the use of derivatives mainly from the chemical industry can play a key role in the energy system or in the transport sector.
Barriers can be addressed or adapted, but this will not be achieved without a joint effort by both the private and public sectors. There must be joint objectives and policies on aspects such as the homogenisation of standards that affect, above all, storage limits. Currently, there is no robust global market due to low demand, which is partly a consequence of low generation and direct consumption at generation sites. As biohydrogen progressively breaks through, demand will increase and generation will have to be done on a large scale. This increase in generation and demand will make material transport routes, which are cost-effective especially over long distances, viable. Hydrogen-specific pipelines, trucks and shipping routes will emerge to meet this demand. With this opening and development of adapted means for hydrogen and biohydrogen, a progressive increase in the areas of potential use will be observed, where transport, especially by heavy vehicles and ships, and energy storage in liquid ammonia tanks will play a key role.
Biohydrogen has the potential to solve today’s pollution problems, but its widespread use is not immediate. The change starts now and the willingness to change must be evident. The next steps include research into all biohydrogen production processes to increase their efficiency and thus their competitiveness; integration of distribution and demand interfaces; management of global policies and technologies; coordination in the face of multilateral sectoral initiatives; and the creation of a knowledge base to serve as a model for the establishment of initiatives.
More information about this theme:
Hidalgo, D., Martín-Marroquín, J. M., & Díez, D. (2022). Biohydrogen: future energy source for the society. In Organic Waste to Biohydrogen (pp. 271-288). Singapore: Springer Nature Singapore.
Artificial intelligence (AI) is contributing to the transformation of a large number of sectors, from suggesting a song to analyzing our health status via a watch, along with manufacturing industry. One hindrance on this transformation relates to the overall complexity of AI systems, which often poses challenges in terms of transparency and comprehensions of the results delivered. In this context, the AI’s explanatory capability (or “explainability”) is referred as the ability to make their decisions and actions understandable to users – which is known as eXplainable AI (XAI); this is something crucial to generate trust and ensure a responsible adoption of these technologies.
Explainable AI (XAI); the ability to make their decisions and actions understandable to users
A wide range of technological solutions are currently being investigated in order to improve the explainability of AI algorithms. One of the main strategies includes the creation of intrinsically explainable models (ante hoc explanations). This type of models, such as decision trees and association rules, are designed to be transparent and comprehensible by their own nature. Their logical structure allows users to seamlessly follow the reasoning behind the AI-based decisions. Tools for visualization of AI explanations are key, since they represent graphically the decision-making process performed by the model, thus facilitating user comprehension. These tools might take different forms, such as dedicated dashboards, augmented reality glasses, or natural language explanations (as speech or as text).
Intrinsically explainable system: decision tree. The intermediary nodes are conditions that are progressively verified until reaching the final result
Natural Language explanations for a recommender system of new routes for exercising. Extracted from Xu et al. (2023). XAIR: framework of XAI in augmented reality.
Another commonly used family of explanation techniques is called post hocmethods: these consist in, once the AI model has been created and trained, a posteriori processing and analyzing this resulting model to provide explanations of the results. For example, some of these techniques evaluate how much is contributed by each input variable in the final result of the system (sensibility analysis). Among post hoc explainability techniques, SHAP (Shapley Additive exPlanations), a method based on cooperative game theory, allows to extract coefficients that determine the importance of each input variable on the final result of an AI algorithm.
Other XAI techniques include decomposition, which divides the AI model into simpler and more easily explainable components, and knowledge distillation into surrogate models, which approximate the function of the original system while being more easily comprehensible. On the other hand, the so-called “local explanations” consist in methods that explain individual examples (input-output), not the entire AI model. An example are the explanations provided by tools such as LIME (Local Interpretable Model-agnostic Explanations). As an illustration of LIME, the example in the following figure shows a specific inference in text classification task, in which a text is classified as “sincere” (with 84% of likelihood), and the most relevant words for that decision are highlighted, as an explanation of this individual classification [Linardatos et al. (2020)].
An additional approach for XAI relates to the integration of input by users in the process of AI model construction, which is known in general as “Human-in-the-Loop” (HITL). This approach allows users to interact (e.g. by labelling new data) and to supervise the AI algorithm building process, adjusting its decisions in real time and thus improving the overall system transparency.
At CARTIF, we are actively working in different projects related with AI, such as s-X-AIPI to help advance in the explainability of AI systems used in industrial applications. A significant example in our work are dashboards (visualization or control panels) designed for the supervision and analysis of the performance of fabrication processes studied in the project. These dashboards allow plant operators to visualize and understand in real time the actual status of the industrial process.
Predictive and anomaly detection models have been created in the context of asphalt industrial processes which not only anticipate future values, but also detect unusual situations in the asphalt process and explain the factors that have an influence on these predictions and detections. Thus, this helps operators make adequate informed decisions and better understand the results generated by the AI systems and how to take proper actions.
Explainability in AI methods is essential for the safe and effective AI adoption in all types of sectors: industry, retail, logistics, pharma, construction… In CARTIF, we are committed with the development of technologies to create AI-based applications that do not only improve processes and services, but also are transparent and comprehensible for users; in short, that are explainable.
Co-author
Iñaki Fernández.PhD in Artificial Intelligence. Researcher at the Health and Wellbeing Area of CARTIF.
