Integrated Sensing and Communications (ISAC) will become a service in future mobile communication networks. It enables the detection and recognition of passive objects and environments using radar-like sensing. The ultimate advantage is the reuse of the mobile network and radio access resources for scene illumination, sensing, data transportation, computation, and fusion. It enables building a distributed, ubiquitous sensing network that can be adapted for a variety of radio sensing tasks and services. In this article, we develop the principles of multi-sensor ISAC (MS-ISAC). MS-ISAC corresponds to multi-user MIMO communication, which in radar terminology is known as distributed MIMO radar. First, we develop basic architectural principles for MS-ISAC and link them to example use cases. We then propose a generic MS-ISAC architecture. After a brief reference to multipath propagation and multistatic target reflectivity issues, we outline multilink access, coordination, precoding and link adaptation schemes for MS-ISAC. Moreover, we review model-based estimation and tracking of delay/Doppler from sparse OFDMA/TDMA frames. We emphasize Cooperative Passive Coherent Location (CPCL) for bistatic correlation and synchronization. Finally, issues of multisensor node synchronization and distributed data fusion are addressed. Keywords: Integrated Sensing and Communication, distributed MIMO radar, Cooperative Passive Coherent Location, multidimensional target state vector estimation, distributed MS-ISAC radio access, ISAC precoding, resource allocation, link adaptation, and data fusion.
Power systems are undergoing a transition from centralised generation to distributed renewable generation. That calls for more flexibility in balancing generation and consumption because distributed energy resources in most cases rely on weather-dependent resources and can, therefore, only be controlled to a certain degree. The necessary flexibility can be achieved by introducing digitalisation. However, digitalisation also leads to new vulnerabilities of the power system and increases its complexity. Additionally, the often rapid and unforeseeable development of information and communication technology introduces a new level of uncertainty in the system design. These circumstances make it necessary to shift from a classical design of robust to the design of resilient power systems that are able to anticipate, react to, and recover from them. In this paper, these real-time attributes of a resilient digitalised power system are analysed with respect to potential measures: an enhanced situational awareness, virtualisation, flexibilisation, and a distributed black start. The measures tackle different challenges for resilient digitalised power systems and cover different phases of the resilience process, visualised in the so-called resilience bathtub curve. The implementation of these measures can increase the resilience of a digitalised power system and are meant to be combined with further, also non-real-time measures.
The FAIR principles (Findable, Accessible, Interoperable, Reusable) have transformed research data management, but they do not address the environmental impact of creating and using research software and data, such as energy consumption, carbon emissions, and life-cycle impacts that become central to computer science and engineering-related domains. To bridge this gap FAIR+Sustainability or FAIR+S, an extension of the FAIR framework that embeds environmental accountability as a core element, was introduced. Because FAIR principles already structure how digital research artefacts are described, shared, and reused, they offer an effective entry point for embedding sustainability considerations at scale. FAIR+S weaves carbon-footprint and energy-use considerations directly into FAIR-aligned metadata schemas, workflows and development specifications. In doing so, it enables research infrastructures to report, compare, and audit the environmental implications of data and software in a measurable, interoperable, and transparent manner. This creates a foundation for reproducible research that simultaneously advances open science goals and decarbonisation objectives. However, integrating environmental accountability into established research workflows raises questions of feasibility, relevance, and acceptance across stakeholders and disciplines. In this work we validated the framework through a cross-disciplinary expert survey. The evaluation confirms its importance and practical relevance, but also reveals current gaps in researchers' awareness of green software practices.
