Ocean of Things System on Local Tidal Flow Analysis

Abstract

Local tidal flow analysis is achieved with Internet‐of‐Things systems that combine distributed sensor networks and portable devices. An ultrasonic sensor system that measures tidal height with a ±1.3175 cm margin of error and 99.554% accuracy was described in previous studies, and an average error of 1.263% in similar measurements was also reported. Other studies detail systems that use Arduino, NodeMCU ESP8266, or combined sensor platforms to offer real‐time updates, high-resolution current (0.02 cm/s) and temperature (0.0625°C) data, and cloud‐based analytics. Distributed networks, demonstrate scalability up to thousands of floats, and portable arrangements support localized tidal monitoring and data validation through statistical methods and machine learning models.

The lack of comprehensive monitoring systems to analyze local tidal flow in oceanic environments presents a significant challenge. Without real-time data collection and analysis, coastal communities and marine ecosystems are vulnerable to various risks such as coastal erosion, flooding, navigation hazards, and ecological disruptions. Therefore, there is a pressing need to design and implement an Ocean of Things system that can effectively gather and analyze data on local tidal flow, enabling informed decision-making for sustainable coastal management and protection. The expressions are detailed in equation 1, discussed on how the temperature and pressure can be determined when duly analyzed in a statistical tool. However, equation 2 makes a further elaboration in determining the depth of any ocean and determine the tide as at when due. Other equations further elaborate different aspects of the work. In determining the depth, the device designed when set on motion to float in any tide will determine all those parameters as mentioned such as; depth, temperature and pressure.