The First IEEE/International Conference on Artificial Intelligence and Cyber Physical Systems
AICPS'25

Environmental Digital Twins and Edge AI for the Intelligent Management of Vulnerable Ecosystems

The increasing environmental and climatic pressures on fragile ecosystems—such as coastal lagoons, wetlands, and protected areas—demand innovative strategies for monitoring, analysis, and decision-making. This keynote will present insights and results from two research projects—SMARTLAGOON and CHAN-TWIN—that have developed pioneering solutions based on Environmental Digital Twins, Edge Artificial Intelligence (Edge AI), and Participatory Data Science to support the sustainable management of the Mar Menor lagoon and the Torrevieja and La Mata lagoons (Alicante, Spain). The talk will demonstrate how to integrate physical data (GNSS-IR sensors, intelligent cameras, meteorological stations), social data (social sensing from online platforms and citizen participation), and predictive models (AI, time-series forecasting, environmental simulation) into a unified digital twin that empowers both citizens and public authorities to make informed and adaptive decisions. Finally, the keynote will reflect on the current challenges in building sustainable, interoperable, and scalable digital infrastructures for environmental management, and discuss how these methodologies can be transferred and replicated in other ecologically and socially valuable contexts.

Exploring the Frontiers of Artificial Intelligence: Innovations, Applications, and Ethical Considerations

In recent years, AI advances have accelerated dramatically, thanks to progress in deep learning, generative models, and the availability of vast amounts of data. These systems can now generate text, create realistic images, compose music, contribute to medical diagnosis, and even aid in scientific research. However, this rapid evolution raises crucial ethical and regulatory questions. How can we ensure that AI remains safe, transparent, and respectful of human values? Policymakers worldwide are still striving to find the right balance: insufficient regulation could lead to abuses, while excessive control could stifle innovation and limit the benefits AI can bring to society, such as improving healthcare or addressing global challenges. This presentation reviews the fundamentals of AI and deep learning, explores practical applications such as facial recognition and medical imaging, and addresses the ethical considerations that must guide the responsible development and deployment of intelligent systems.

Title of the abstract of Pr. Mohamed Nadhir Djekidel

Secure, Sustainable and Efficient: Designing the Digital Infrastructure of Tomorrow

As digital systems become the backbone of global innovation, the challenge before us is clear: how do we design infrastructure that is not only technologically advanced, but also secure, sustainable, and efficient—across borders, sectors, and scales. This keynote addresses the urgent need for a new paradigm in digital infrastructure design. We begin with security, exploring global strategies for resilience against cyber threats and the future of trust in a hyperconnected world. We then turn to sustainability, examining how data centers, cloud platforms, and hardware ecosystems can align with climate goals through energy optimization, carbon-aware computing, and responsible sourcing. Finally, we explore efficiency, highlighting innovations in AI-driven automation, edge computing, and intelligent orchestration that enable scalable, low-latency systems. Through real-world examples and forward-looking strategies, this talk challenges technologists, policymakers, and industry leaders to rethink infrastructure as a dynamic ecosystem—one that must be secure by design, sustainable by necessity/commitment, and efficient by innovation.

Smart Oilfields: AI-Driven Edge Computing and Response Prioritization for Sustainable Production

In the evolving landscape of digital oilfield operations, Sensia introduces a transformative approach to artificial lift optimization through its Hyperconverged Edge Controller (HCC2) and AI Response Prioritization (AiRP) system. The HCC2 serves as a robust, scalable edge computing platform designed to unify sensing, intelligence, and control at the wellsite, enabling real-time data processing and decision-making closer to the source. Complementing this, AiRP leverages advanced artificial intelligence and machine learning algorithms to automate incident detection and prioritization for ESPs. By distinguishing critical events from routine alerts, AiRP significantly reduces response times—from hours to minutes—enhancing operational efficiency, minimizing downtime, and improving asset performance. Together, these technologies exemplify Sensia’s commitment to digitalization, offering oil and gas operators a pathway to smarter, safer, and more sustainable production.

Neuro-symbolic AI: The Third Wave of AI

There are three waves of Artificial Intelligence. The first Wave of AI is Crafted Knowledge, which includes rule-based AI systems. The second wave of AI is Statistical Learning, which includes machine becoming intelligent by using statistical methods. The third wave of AI is contextual adaptation. In the third wave, instead of learning from data, intelligent machines will understand and perceive the world on its own, and learn by understanding the world and reason with it. Neuro-symbolic AI, which combines neural networks with symbolic representations, has emerged as a promising solution of the third wave of AI. In this talk, first I will share my journey from counter-unmanned aircraft systems to explainable AI to neuro-symbolic AI. Then I will present the past, present, and future of neuro-symbolic AI. I will also share my perspective on the emerging area of neuro-symbolic AI.