Spatiotemporal modelling and monitoring of harmful algal blooms using IoT in Lake Victoria Basin Kenya.

ABSTRACT: The escalating global concern of harmful algal blooms (HABs) in aquatic environments, poses significant challenges in the context of sustainable development goals (SDGs). The impacts of HABs extend beyond increased waterborne diseases, causing high aquaculture mortality, diminished aesthetic appeal, elevated drinking water treatment costs, and negative effects on tourism and gross domestic product (GDP). Traditional HAB assessment methods involving field sampling and laboratory analysis are inefficient due to their labor intensiveness and cost. This study introduces a novel approach, combining near real-time satellite remote sensing with a low-cost in-situ internet of things (IoT) system that adds a layer of real-time data collection and timely reporting. The method utilizes the ocean colo

SUBMITTER: Okomo JO 

PROVIDER: S-EPMC12575628 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature