Data Fusion and Visualization Approaches to Achieving a Common Operating Picture During Offshore Wind Construction and Operation Works

Abstract

Abstract The offshore wind industry is promoting developments in environmental sensing, machine learning, and artificial intelligence, to better detect the presence of marine and avian species. Environmental sensing technologies (e.g., radar, video and infra-red imagery, passive acoustics, and radio telemetry) have advanced where wildlife are reliably detected and tracked, aiding their protection by minimizing conflicts with ships, other users of the ocean space, and other stressors. Significant marine ecosystem data is collected daily offshore from a wide range of reputable sources. These disconnected sources represent, in aggregate, a trove of Domain Awareness (DA) data and if cohesively viewed, provide opportunity to better de-risk operations, protect wildlife, and avoid delays in real time. Taking care and effort to assimilate these (often disparate) data sources into common visualization platform(s) provides both more granular and macro-scale situational awareness, while advancing opportunities to apply predictive Artificial Intelligence (AI) to the data. This can result in the application of regional (or broad scale) predictions and understandings of species activities. As this data base of predictions and observations grow, additional decision making and management mitigations can be applied, such as alerting specific vessels to the presence of protected species or initiating tailored dynamic management areas (DMAs) at appropriate temporal or spatial scales. Deployment of sensors on technically advanced host platforms, including autonomous underwater vehicles, uncrewed surface vehicles, and metocean buoys, is occurring regularly. Equally prolific are strategies to collect, analyze, and display data from each sensor, resulting in myriad data dashboards, digital twins, and immersive visualization environments offered to offshore wind developers and regulators. While accelerating technological innovation, these numerous, and often single-focus approaches can hinder the delivery of a unified picture of the worksite or regional environment, limiting conservation value of these efforts and increasing environmental and scheduling project risks. This paper reviews some of the extant initiatives to deliver environmental data and provides a suite of best practices and recommendations for developing a DA capability or a common operating picture (COP) of developer's projects, as well as a regional view that covers multiple worksites. This work will assist developers and regulators to understand a realistic state of technical readiness and how to appropriately scope data products that support data fusion consistently across visualization platforms.