From Mechanized Longlines to Smart Fisheries: Integrating Automation, Electronic Monitoring, and Artificial Intelligence

Longline fisheries harvest high-value pelagic and demersal species but remain labor-intensive and require reliable monitoring of catches, bycatch, and fishing effort. This technology-oriented narrative review synthesizes 71 sources on mechanization, automation, electronic monitoring (EM), artificial intelligence (AI), and prospective smart fisheries. Evidence is distinguished by source type, application setting, and operational maturity. Mechanized hauling, baiting, and integrated autoline systems support fishing operations, whereas EM provides records for catch verification and management. Computer vision studies demonstrate catch-event detection, species classification, and selected compliance-monitoring tasks, but reported performance remains specific to the datasets and validation conditions. Commercial availability, experimental performance, and conceptual feasibility are therefore assessed separately. Edge AI, integrated intelligent reporting, digital twins, and generative AI remain emerging or prospective for longline fisheries in the reviewed evidence. The synthesis identifies camera visibility, cross-vessel generalization, rare-species detection, interoperability, and data governance as key constraints. A practical development pathway combines established equipment and EM with externally validated AI, expert review, and feedback to subsequent vessel operations. Increased fishing efficiency alone does not establish sustainability; environmental and management outcomes require separate evaluation.