mardiana, Meidi Wani Lestari, Third

DESIGN AND CONSTRUCTION OF A NATURAL DISASTER DETECTION EQUIPMENT USING THE WATER LEVEL SWITCH SENSOR AND SENSOR SW-420

Introduction

Design and construction of a natural disaster detection equipment using the water level switch sensor and sensor sw-420. Design & build an IoT-based system for early natural disaster detection (floods, earthquakes) with water level & SW-420 sensors. Get Telegram alerts via Arduino/NodeMCU to minimize losses.

Abstract

Disasters such as earthquakes, tsunamis, floods and others always cause losses in the form of material, psychological can also cause casualties. To avoid the occurrence of greater losses, an early disaster warning and information system is needed to provide opportunities for self-rescue so that losses can be minimized. The basic concept of the Internet of Things (IoT) "wherever, whenever and however" and connected to the internet is very suitable when applied to detect and early warning of natural disasters. This tool will monitor the water level using a water level float sensor and detect vibrations with the SW-420 vibration sensor module. when the water exceeds the height of the water level sensor, the data will be processed by the Arduino programmed using the Arduino IDE then the data is sent to the NodeMCU 8266-12E to send data notifications to the user. The reading results can be seen on the Telegram smartphone application.

Review

The submitted abstract outlines the design and construction of a natural disaster detection equipment aiming to provide early warnings and minimize losses, a highly pertinent and critical area of research given the increasing frequency and impact of such events. The fundamental concept of integrating Internet of Things (IoT) principles, leveraging "wherever, whenever and however" connectivity, is well-aligned with modern approaches to remote monitoring and real-time data dissemination. The initiative to develop a low-cost, accessible system for early warning aligns with a significant societal need, promising to offer opportunities for self-rescue and improved disaster preparedness. From a technical standpoint, the proposed system utilizes a water level float sensor (described as a switch) and an SW-420 vibration sensor module, processed by an Arduino and connected to a NodeMCU 8266-12E for sending notifications via the Telegram application. While the integration of these off-the-shelf components for an IoT application is straightforward, the abstract's broad claim of "Natural Disaster Detection Equipment" for disasters like "earthquakes, tsunamis, floods and others" requires significant scrutiny. A water level *switch* sensor provides only binary information (above/below a threshold), which is insufficient for comprehensive flood monitoring or tsunami detection. Similarly, the SW-420 vibration sensor is a very basic component, typically used for simple impact detection rather than precise, nuanced seismic activity or tsunami-induced ground vibrations. The abstract lacks detail on how these limited sensors can effectively differentiate between various disaster types, particularly distinguishing an earthquake from general environmental noise or localized disturbances. To enhance the scientific and practical merit of this work, the authors should consider refining the scope and claims of their equipment, perhaps focusing more specifically on flood detection where the water level sensor might be more directly applicable. For robust detection of earthquakes or tsunamis, significantly more advanced and calibrated sensors, potentially an array of sensors, along with sophisticated signal processing and algorithms would be imperative. The full paper should provide detailed information on the system's calibration, accuracy, response time, and how false positives are mitigated. Crucially, validation through field testing or simulated real-world conditions, accompanied by performance metrics (e.g., detection accuracy, latency, reliability), is essential to substantiate its effectiveness as an "early warning" system. While the current approach demonstrates a basic IoT integration, a more critical assessment of sensor capabilities versus disaster complexity is needed to move beyond a proof-of-concept to a truly reliable disaster detection tool.

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