Suppress that algae: Mitigating the effects of harmful algal blooms through preemptive detection & suppression

Recently, Harmful Algal Blooms (HABs), e.g., toxic red tide and blue-green algae, have suffocated and plagued coastlines and inland water bodies leading to economic losses. Currently, batch data collection in many areas is inadequate and reactionary following regional fish kills. Therefore, there is an inherent need for a “smart” solution aimed at preemptive detection and mitigation of the impending super bloom through combination of concurrent measurements, modeling, and mitigation using suppression agents. Our hypothesis is if a Seek and Destroy Algal Mitigation System (SDAMS) is engineered with a multitude of capabilities, including remote algal parameter sensing, wireless data transmission, and mitigation using suppression agents, then it will preemptively detect and mitigate HABs. The SDAMS includes (i) a floatation device with a Wi-Fi microcontroller and five sensors for concurrent measurements, (ii) real-time data transmission to the cloud, (iii) data visualization; diagnostic and predictive analysis, and (iv) an algae suppression component. During laboratory testing, physical and chemical agents used for mitigation noticeably suppressed the algae in various ways. Algal suppression occurred by either reducing pH, increasing Dissolved Oxygen (DO), or exerting high mechanical properties. We conducted predictive analytics to quantify the influence of the suppression agent on algae and compared the green spectrum strength (indicating algal intensity) to the DO concentration. Using machine learning, a 4th order polynomial equation with 94% accuracy provided the best curve-fit to explain the green spectrum-to-DO relationship. This cost-effective solution can be applied to instantaneously suppress, or preemptively mitigate, HABs to minimize environmental impacts.