Harmful algal blooms (HABs) cause harm to human health or hinder sustainable use of the marine environment in Blue Economy sectors. HABs are temporally and spatially variable and hence their mitigation is closely linked to effective early warning. The European Union (EU) Interreg Atlantic Area project βPRIMROSEβ, Predicting Risk and Impact of Harmful Events on the Aquaculture Sector, was focused on the joint development of HAB early warning systems in different regions along the European Atlantic Area. Advancement of the existing HAB forecasting systems requires development of forecasting tools, improvements in data flow and processing, but also additional data inputs to assess the distribution of HAB species, especially in areas away from national monitoring stations, usually located near aquaculture sites. In this contribution, we review different novel technologies for acquiring HAB data and report on the experience gained in several novel local data collection exercises performed during the project. Demonstrations include the deployment of autonomous imaging flow cytometry (IFC) sensors near two aquaculture areas: a mooring in the Daoulas estuary in the Bay of Brest and pumping from a bay in the Shetland Islands to an inland IFC; and several drone deployments, both of Unmanned Aerial Vehicles (UAV) and of Autonomous Surface vehicles (ASVs). Additionally, we have reviewed sampling approaches potentially relevant for HAB early warning including protocols for opportunistic water sampling by coastguard agencies. Experiences in the determination of marine biotoxins in non-traditional vectors and how they could complement standard routine HAB monitoring are also considered.