Title: Post‑Conflict Technology Residues (PCTR): A Neutral, EO‑Detectable Multi‑Hazard Class for GeoAI and PostSDG Governance
Abstract:
Post Conflict Technology Residues (PCTR) represent a neutral, material‑based class of technological remnants defined exclusively through physical, chemical, and structural properties, persisting in the environment after security‑related incidents, disasters, or conflict events, and remaining hazard‑agnostic, EO‑detectable, and globally relevant for GeoAI, environmental monitoring, and PostSDG governance.
They should include, for example, lithium‑ion energy storage units, carbon‑fiber composites, metallic fragments, electronic assemblies, and partially activated technical components, whose behavior — driven by thermal instability, hydrological mobilization, and the persistence of carbon fibers, metals, and fluorinated polymers — could generate a complex multi‑hazard interaction profile simultaneously affecting fire risk, water quality, soil contamination, infrastructure integrity, and human exposure.
At this point, we require expanded systemic architectures, because existing frameworks may acknowledge multi‑hazards and digital risks, but they do not contain a neutral, material‑based, EO‑detectable object class like PCTR that jointly models, regulates, and monitors physical residues, digital decision spaces, and algorithmic remnants left behind after crises and conflicts.
PCTR constitute an indispensable anchor that could enable us to make the increasingly coupled physical and digital multi‑hazard cascades of modern technologies visible, modelable, and governance‑capable — including those digital, infrastructural, and algorithmic residues that remain within systems after crises and conflicts and may generate new risks.
From an EO perspective, PCTR form an emergent object class, as optical data reveal debris fields, SAR detects metallic structures, thermal sensors locate hotspots, hyperspectral methods capture chemically induced changes in vegetation and sediments, and time‑series analyses track the migration of residues through hydrological or anthropogenic processes — enabling GeoAI‑supported detection, classification, and modeling across spatial and temporal scales.
Pins and GeoIME also play an important role in this context.
In parallel, recent AI event dynamics — in which advanced models were able to break out of isolated environments during security tests, exploit previously unknown vulnerabilities, and reach external systems — demonstrate that digital systems are developing increasingly autonomous operational scopes. These scopes are no longer fully controllable through classical security concepts and could generate relevant digital multi‑hazard cascades that may also trigger physical multi‑hazards, such as malfunctions in energy storage systems, autonomous vehicles, drones, robotics, or critical infrastructure, which in turn could generate PCTR objects.
Conversely, PCTR could potentially destabilize digital systems by impairing sensors, data chains, or GeoAI models, causing physical and digital residues to reinforce one another and form a two‑dimensional multi‑hazard system. This makes the integration of both hazard classes into international resilience architectures — such as the Sendai Framework, the WHO International Health Regulations, the Emergency Response Law of the People’s Republic of China, the Environmental Health Frameworks of CDC China, the National Health Emergency Response System, the Emergency Management Framework for Canada, the PHAC frameworks, ISPRS, and IEEE PAR 4011 — necessary.
It is a balancing act on a razor’s edge, because the razor’s edge represents the extremely narrow zone between digital AI cascades and physical PCTR cascades — a zone that modern technologies can cross at any moment, as there is currently no sufficiently robust architecture capable of making both sides jointly visible, modelable, and governance‑capable.
This also requires building a future Governance Aware Utilization Layer — a comprehensive, globally interoperable architecture that keeps classification neutral, auditable, scientifically grounded, and operationally relevant, while jointly modeling, regulating, and monitoring physical residues, digital decision spaces, and multi‑hazard cascades.
In combination with BioSens, PCTR could enable Human‑in‑the‑Loop Hazard Intelligence, linking community‑based sensing with advanced EO analytics and forming the foundation for a scalable, technology‑supported resilience architecture. Since no international framework currently exists that accounts for the long‑term behavior of modern technological residues across multiple hazard types while simultaneously addressing the autonomous operational scopes of modern AI systems, the convergence of PCTR and digital AI events could provide a neutral, EO‑verifiable, and governance‑capable hazard taxonomy. This aims to strengthen collective resilience, enable interoperable governance, and support a sustainable, technology‑driven future aligned with the SDGs.
Short Biography:
Birgit Bortoluzzi is an architect and author of Systemic Resilience Logic, Resilience Frameworks, and Governance Architectures. She developed the Geo Resilience Compass and the University of Hope prevention platform and contributes to global standards development within the IEEE GRSS Disaster Management & Early Warning Working Group (PAR 4011).
With more than 27 years of experience, Birgit brings an exceptionally broad professional portfolio: as an author and framework architect, as founder of MehrLot Digital (strategic communication and positioning), in public communication and event management within a research institution and as well as in the field of cybersecurity at a government agency. This career path gives her a rare interdisciplinary perspective on modern resilience architectures. She is a certified disaster manager, strategy and scenario planner, marketing manager (Marketing Thesis “Personalized Medicine as a Societal Responsibility” awarded with excellence), and social media PR manager.
Her work focuses on developing closed, multi‑hazard governance architectures, integrating epistemic integrity into hazard governance, and designing globally interoperable resilience frameworks. She specializes in vulnerable groups (Long Covid/ME/CFS, Multiple Chemical Sensitivity, and other chronic conditions), CBRN resilience, governance engineering, robust multi‑hazard architectures, cross‑sector early‑warning ecosystems, hazard intelligence, geospatial and EO‑integrated risk systems, wargaming, civil protection logic, and high‑risk scenario architecture.
Birgit is the creator of the Geo Resilience Framework (GRC). Her work bridges science, governance, geospatial intelligence, and systemic risk architecture — with the aim of building resilient societies and operational architectures for complex global hazard environments.