THE DIGITAL SENTINEL: REVIEW ON FO, RS AND AI FOR PROACTIVE FOOD-WATER NEXUS RISK

The necessity for sustainable food systems dictates a critical move towards proactive, evidence-based Food Safety and Risk Assessment, particularly in the face of escalating environmental threats. The global proliferation of Harmful Algal Blooms (HABs) poses a major, dynamic risk to water security, which rapidly translates into food contamination. Traditional, reactive testing methods are inadequate for managing this emerging hazard. This Perspective article proposes a unified "Digital Sentinel" framework that transforms environmental surveillance into predictive supply chain alerts. The Sentinel operates by fusing two complementary data streams. First, macro-scale environmental monitoring, accomplished through Remote Sensing platforms, provides continuous geospatial tracking and predictive modeling of bloom intensity. Second, this information is validated by micro-scale molecular insights, utilizing Algal Omics technologies (Genomics, Transcriptomics) for high-throughput identification of toxic species and quantification of toxin-producing genes. Hence, the integration of this heterogeneous data is achieved using advanced Big Data analytics and Explainable Artificial Intelligence (XAI). This intelligent layer generates a verifiable, proactive risk score that informs evidence-based regulatory decisions. Thus, the Digital Sentinel strengthens Food Safety, certifies product origin for Food Authenticity, and fully embodies the principles of Foodomics, Digitalization, and the indispensable One Health Model. Hence, the approach is promising and aligns with the direction of digital transformation in food safety and environmental health.