Monitoring and Prediction of Water Levels in Telkom University Techno Lake Based on the Internet of Things using the Linear Regression Approach

Unpredictable fluctuations in lake water levels can have severe consequences, leading to droughts or overwhelming water overflow, causing damage to the delicate ecosystem both within and around the lake. To address this pressing issue, the Internet of Things (IoT) emerges as a transformative technological solution. IoT enables the interconnection of electronic devices to the internet, granting accessibility from anywhere and at any time. In response to this problem, an innovative IoT-based prototype has been developed to monitor and predict lake water levels. This prototype utilizes a linear regression approach as a reliable method for water level prediction. Furthermore, it leverages the LoRa network to ensure data accessibility even in areas without internet connectivity, and it operates sustainably by harnessing solar panels as an energy source. These unique features make the prototype a groundbreaking solution, revolutionizing the way we manage and safeguard our lakes. The efficacy of the prototype is proven by the remarkable accuracy of error testing (error) on the predicted linear regression values using Mean Absolute Percentage Error (MAPE), yielding an impressively low error rate of below 10%. Such high accuracy validates the reliability and effectiveness of the system, giving stakeholders the confidence to adopt and implement this solution on a broader scale. By implementing this IoT-based lake water monitoring system, we can proactively address water level fluctuations, minimize ecological harm, and foster sustainable water management practices.