A Low-Cost AI Buoy System for Monitoring Water Quality at Offshore Aquaculture Cages.

The ocean resources have been rapidly depleted in the recent decade, and the complementary role of aquaculture to food security has become more critical than ever before. Water quality is one of the key factors in determining the success of aquaculture and real-time water quality monitoring is an important process for aquaculture. This paper proposes a low-cost and easy-to-build artificial intelligence (AI) buoy system that autonomously measures the related water quality data and instantly forwards them via wireless channels to the shore server. Furthermore, the data provide aquaculture staff with real-time water quality information and also assists server-side AI programs in implementing machine learning techniques to further provide short-term water quality predictions. In particular, we aim to provide a low-cost design by combining simple electronic devices and server-side AI programs for the proposed buoy system to measure water velocity. As a result, the cost for the practical implementation is approximately USD 2015 only to facilitate the proposed AI buoy system to measure the real-time data of dissolved oxygen, salinity, water temperature, and velocity. In addition, the AI buoy system also offers short-term estimations of water temperature and velocity, with mean square errors of 0.021 °C and 0.92 cm/s, respectively. Furthermore, we replaced the use of expensive current meters with a flow sensor tube of only USD 100 to measure water velocity.

Direct patterning of zinc oxide with control of reflected color through nano-oxidation using an atomic force microscope.

Atomic force microscope oxidation on Zn creating amorphous ZnO (a-ZnO) with the a-ZnO showing multiple colors under white light at different oxidation voltages was successfully demonstrated. Simulation of reflected colors at different thicknesses of a-ZnO was also conducted. The presented technique can not only be applied to near diffraction limit multilevel optical data storage, but also makes it possible to represent the color spectra observed in nature at near diffraction limits. It can also be used for device fabrication in situations exploiting the semiconductor nature of ZnO.