SMARTFLOODGUARD: IoT- INTEGRATED FLOOD

DETECTION AND ALERT SYSTEM

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A Research Project

Presented to the Faculty of

Western Cagayan School of Arts and Trades

Lasam, Cagayan

___________________________________

In Partial Fulfillment

of the Requirements for the Subject

Research II

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By:

RHEAIANE LEIGH C. SAGISI

SHANELLA KRISTEZA B. COLOMA

JON RICK ALFRED CACHOLA

S.Y. 2024-2025

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 ABSTRACT

This investigatory research aimed to design and developed FLOODGUARD: An IoT-Based

Flood Water Level Monitoring System, which enables real-time flood detection. The
objectives included the development of a water level monitoring device, evaluation of its
accuracy in detecting normal, warning, and alert states, and assessment of its cost-
effectiveness. The experiment was conducted in three phases: normal, warning, and alert
conditions, with each phase consisting of three trials. In the Normal Condition, the water
level ranged from 0.92 m to 1.20 m. The Warning Condition covered levels between 1.21 m
and 2.40 m, with measured values of 1.21 m, 1.50 m, and 1.88 m. In the Alert Condition, the
water level exceeded 2.41 m, with measurements of 2.41 m, 2.57 m, and 2.81 m, signaling an
immediate flood risk. The FLOODGUARD system demonstrated reliable performance across
all conditions, consistently providing accurate water level readings. Its ability to transition
seamlessly between warning and alert phases allowed for timely flood detection, enabling
proactive measures to prevent damage. The cost analysis revealed that the total expenditure
for developing the device was ₱2,781, highlighting the system’s affordability. The results
show that FLOODGUARD is an effective and low-cost solution for flood preparedness,
offering early warning capabilities that can significantly enhance community safety by
providing real-time alerts. This study demonstrates the potential of IoT-based solutions in
addressing flood risks and ensuring timely responses during emergencies.

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 Chapter 1

INTRODUCTION

Background of the Study

The Philippines is highly vulnerable to flooding, which is one of the most destructive natural
disasters, causing millions of pesos in damage each year to property, infrastructure, and
agriculture. These floods often result from heavy rainfall, or storm surges and can be fatal
when swift currents sweep people away. Even slow-moving floods pose significant dangers,
especially when contaminated waters spread disease. The destruction of homes, businesses,
and critical infrastructure—such as roads and bridges—disrupts daily life and economic
activity. Additionally, floodwaters devastate agriculture by destroying crops and livestock,
potentially leading to food shortages. In response, there is an increasing need for advanced
flood monitoring and early warning systems to reduce these impacts.

Region 02 in the the Philippines, encompassing Cagayan, Isabela, Nueva Vizcaya,

Quirino, and Batanes, is particularly prone to severe flooding due to its geographical and
climatic conditions. The region's vulnerability is starkly evident from historical flood events.
For example, Typhoon Ulysses (Vamco) in November 2020 caused catastrophic flooding in
Cagayan and Isabela, with the Cagayan River and its tributaries overflowing and inundating
vast areas. This disaster led to significant property damage, extensive agricultural losses, and
severe disruptions to daily life. Another significant event was the flooding caused by
Typhoon Lawin (Haima) in October 2016, which similarly devastated agricultural lands and
residential areas, highlighting the region's susceptibility to typhoon-induced floods.

SMARTFLOODGUARD significantly advances SDG 11, "Sustainable Cities and

Communities," by enhancing safety in flood-prone areas through continuous monitoring and
early alerts. This proactive system helps communities prepare for sudden flooding and
reduces risks associated with unexpected water level rises. It also supports urban planning by
identifying high-risk zones to guide land use decisions. By providing real-time insights to city
planners, FLOODGUARD encourages more thoughtful infrastructure development.
Furthermore, the technology contributes to SDG 3, "Good Health and Well-being," by
mitigating health risks linked to flooding, such as waterborne diseases. With

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SMARTFLOODGUARD in place, communities are better protected, leading to improved
public health outcomes.

Aligned with SDG 13, "Climate Action," SMARTFLOODGUARD provides crucial

real-time data for prompt responses to rising water levels. The system’s early warnings
facilitate timely evacuations and efficient resource distribution, saving lives and minimizing
damage. The system also aligns with SDG 15, "Life on Land," by protecting ecosystems that
can be adversely affected by flooding, thereby supporting biodiversity. Finally,
FLOODGUARD fosters partnerships under SDG 17, encouraging collaboration among local
governments, NGOs, and communities to achieve sustainable development in the Philippines.
FLOODGUARD not only enhances flood management and community safety but also
contributes significantly to the broader objectives of sustainable development in the
Philippines. By aligning with multiple SDGs, it demonstrates the potential of innovative
technologies to foster resilience and promote well-being in vulnerable communities.

The absence of effective warning and alert systems for flooding poses significant risks
and disadvantages, particularly in vulnerable regions such as Region 2 of the Philippines.
Without timely warnings, residents are often caught off guard by sudden and severe floods,
leading to increased risk of casualties and injuries. The lack of advance notice prevents
individuals from taking necessary precautions, such as evacuating to safer areas or securing
their properties, resulting in higher rates of property damage and loss. The inability to predict
and respond to floods also hampers emergency services, delaying rescue operations and relief
efforts, which exacerbates the impact on affected communities. Additionally, prolonged
exposure to contaminated floodwaters without prior warning can lead to serious public health
issues, including outbreaks of waterborne diseases. Overall, the absence of a robust warning
system undermines preparedness and resilience, heightening the adverse effects of flooding
and complicating recovery efforts.

The traditional approach to flood monitoring involves manual readings, which are laborious
and risky. Wireless networks use low-cost, low-power sensors to address this. By
continuously collecting data on water level, these sensors enable more informed decisions to
be made about the allocation of resources and the timely issuance of flood warnings. In this
field, research is focused on developing reliable communication protocols, data analysis tools,
and effective sensor to build a comprehensive flood monitoring system. In addition, the data

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can be used to identify flood-prone areas, assess the effectiveness of the current flood
monitoring systems, and empower authorities to take preventative action

Flood alarms play a crucial role in flood-prone areas by providing early, clear alerts that give
people enough time to act before the situation becomes critical. The loud, attention-grabbing
sound ensures that everyone in the vicinity is notified, even those without smartphones,
helping the entire community stay informed and prepared. With these alarms, residents can
take immediate action, such as moving valuables to higher ground, evacuating at-risk areas,
and setting up flood barriers to protect their homes. Additionally, flood alarms significantly
enhance the effectiveness of emergency responders by enabling them to quickly pinpoint the
most affected areas and allocate resources where they’re most needed. This timely response
not only saves precious time but also increases the likelihood of assisting more people and
reducing overall damage.

Explores the role of the Internet of Things (IoT) in managing flood data. With floods being a
widespread natural disaster, effective management is crucial. The study reviews existing
projects using IoT for flood data ang proposes an IoT architecture for streamlined data
collection, transmission, and management. Synthesis: According to the study by
Chandrika,M. S, et al (2023), focusing on flood management, the paper examines how IoT
can enhance data systems. It summarized previous IoT-Based flood projects and suggest a
tailored IoT architecture for efficient data handling. This contributes to the progress of flood
information management.

Experiment shows that the system if efficient at keeping track of water level and sending out
flood alerts as they increase. The systems mobility and high accuracy of the ultrasonic sensor
make it a useful tool for managing floods in various risky areas. Synthesis: The study by
Daud, E., and Bakar, M. I. (2021) is to detect and give early warning to residents near bodies
of water especially river that is impacted when dams release their water. This will save lives
and valuable properties as the warning system alerts the user, thus giving time for evacuation.

According to Hadi, M., et al. (2020) demonstrate it efficiency in early warning, flood
detection, and water level monitoring. It makes use of technologies, such as GPS, IoT
connectivity, and ultrasonic sensors, to deliver precise data and timely alerts to users,
improving their capacity to respond to flood-related dangers and minimize potential damages.
Synthesis: The goal of study by Hadi, M., et al. (2020) is to develop a flood detection and

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avoidance system using the internet of things, which is viewed as a great way to assist solve
the flooding issues in major cities.

This tool works well to generate output information level data and flood early
warning. Information thing speak water level using a platform that can be seen by the public
in real-time early warning and notification platform using a wire in anticipation of the
impending flood dangers. Ultrasonic sensors used can work well with the accuracy of data to
the error value, average error of 1 cm and the relative error was 0.78%. synthesis: Diriyana,
A., et al.’s 2019 project aims to create an autonomous flood detection system that can track
water level and issue early warning of impending flooding. The IOT was the foundation of
this water level monitoring system, which provided real-time data to determine the water
level created at specific levels.

Implementing an IoT-based flood level monitoring system provides numerous

advantages that significantly enhance flood management and response. One of the primary
benefits is real-time data collection and analysis, as IoT sensors continuously monitor water
levels and transmit data, allowing authorities to detect rising water and potential flood threats
as they emerge. This immediacy enables timely decision-making and effective responses to
developing flood situations. Early warning and alert capabilities are another critical
advantage; when sensors identify that water levels are approaching predefined thresholds, the
system can automatically issue alerts to residents and emergency services, allowing for timely
evacuations and preventive measures that reduce the risk of casualties and property damage.

Furthermore, IoT systems enhance flood forecasting by integrating data from multiple
sources, which improves the accuracy of predictions regarding the timing, severity, and
impact of flood events. This enhanced forecasting capability supports better preparedness and
more efficient resource allocation. During flood events, the ability to manage resources
effectively is crucial, and IoT systems facilitate this by providing precise data for directing
emergency response efforts and distributing relief supplies where they are most needed.

Thus, the researchers developed an IoT-Based Flood Water Level Detection and Alarm
System designed to improve flood management strategies. The data collected validated the
system’s effectiveness and provided insights for future enhancements. These trials highlight
the critical role IoT systems can play in monitoring floods in different areas. By delivering
real-time data, the system can monitor and control water levels, triggering an alarm when

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flood levels reach critical thresholds, promoting efficient water management and enabling
timely flood responses. The primary objective of this research is to create a dependable tool
for flood prevention and resource management, ultimately mitigating the devastating effects
of flooding.

Objectives of the Study

This investigatory research projects aimed to design and develop a SMARTFLOODGUARD:

IoT- Integrated Flood Detection and Alarm System.

Specifically, it aimed to:

1. construct a water level monitoring device and alarm system for real-time flood
detection within an Internet of Things (IoT) Framework.
2. evaluate the sensing device reading with response text of the
SMARTFLOODGUARD device in terms of:
a. alert state
b. alarm state
c. critical state
3. assess the cost effectiveness of the SMARTFLOODGUARD device.

Significance of the Study

The development of an IoT-Integrated Flood Detection and Alarm System is highly

beneficial to various sectors, particularly in flood-prone communities. The results of this
research hold significant value to the following groups:

Philippine Atmospheric Geophysical and Astronomical Services Administration (PAGASA)

The integration of IoT in flood monitoring systems can enhance PAGASA’s ability to
provide real-time data, improving the accuracy of their weather forecasts and flood alerts. By
utilizing automated and networked sensors, critical information on rising water level can be
relayed directly to PAGASA, enabling them to issue timely and accurate flood warning to the

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National Weather Service, public officials, and communities. This system can save live,
reduce property damage, and better protect vulnerable populations from severe flooding.

Local Government Units (LGU)

Many LGUs face challenges in implementing effective disaster risk management

strategies due to limited resources and technical capacity. This IoT-Based System
empower LGUs by providing them with precise and real-time data on flood levels,
enabling better disaster preparedness and response. The data-driven insights can support
the formulation of more effective Disaster Risk Management Plan and improve local
governments capacity to gather, interpret, and act on critical flood information.

Department of Science and Technology (DOST)

This project aligns with DOST’s mandate to advance science and technology for
community welfare. By promoting innovative IoT solutions, the study provides a pathway
for DOST to prioritize research and development in disaster risk reduction. This project,
through its focus on automation and sensor technologies, can guide the institution in
identifying strategic areas where science and technology can be leveraged to enhance the
resilience of communities.

The Community

The IoT-Based Flood Water Level Monitoring System directly benefits communities
by providing early warnings that allow them to prepare and respond proactively to flooding.
The system’s real-time alerts, whether through light indicators, alarms, or mobile
notifications, enable residents to take timely action, securing their belongings and ensuring
their safety. The loud alarm further amplifies the urgency of the situation, ensuring that the
community is quickly alerted to rising flood risks. By offering more lead time between
flood detection and arrival, this system reduces casualties, minimizes damage to movable
property, and contributes to safer and more resilient communities.

Scope and Limitations

This investigatory project focused on the design and development of

SMARTFLOODGUARD: IoT- Integrated Flood Detection and Alarm System. The study

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aimed to create a real-time flood detection system within the Internet of Things (IoT)
framework to effectively monitor and manage water levels. Specifically, the research project
covered the development and testing of a water level monitoring device capable of responding
to various flood conditions, including alert, alarm, and critical states. Additionally, the
SMARTFLOODGUARD device's cost-effectiveness was evaluated.

The study was conducted in Centro 3, Lasam, Cagayan, from October 27,2024 to
November 8, 2024, within a controlled environment. The system’s functionality was assessed
based on its ability to provide real-time data on water levels, send corresponding text
notifications for different flood risk levels, and emit an alarm during alert states to warn
nearby residents. The project scope was limited to testing within the local geographical area
and did not include long-term deployment or large-scale testing across multiple regions.

Definition of Terms

Blynk- Refers to a platform that allows for easy development of Internet of Things (IoT)
applications. It provides a cloud-based service where real-time data from devices, such as
sensors monitoring floodwater levels, can be visualized and managed through a user-friendly
mobile or web application.

Buzzer – A small electronic device that emits sound signals to alert users when the flood level
reaches a critical point. The buzzer helps notify the community and emergency responders of
an impending flood or danger, providing an audible warning to prompt timely action.

Early Warning Device - An IoT-enabled device that provides real-time alerts for potential
flooding, allowing early evacuation.

ESP32 - A Wi-Fi-enabled chip used to connect sensors that measure water levels, enabling
remote monitoring.

Flood Notification System - An IoT-based system that alerts residents and authorities when
flood levels reach critical points, using sirens, lights, and mobile notifications.

GPIO Pins – General Purpose Input/Output (GPIO) pins are programmable pins found on
microcontrollers like the ESP32, used to send and receive signals from external components.
These pins can control devices such as LEDs, sensors, or relays, enabling the system to

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interact with the environment and perform actions like triggering alarms or activating flood
indicators.

IoT - Refers to a system that integrates sensors and communication technologies to monitor,
collect, and manage data in real time.

IoT-Based Light and Sound Indicator - An automated system using lights (green, orange,
red) and alarms to signal flood severity.

ISO 25010 - A software quality standard used to ensure the system is effective, efficient, and
reliable.

LED (Light Emitting Diode) – An energy-efficient light source used to visually indicate the
flood risk level. The LED emits different colors, such as green for aler water levels, yellow
for alarm, and red for critical flood conditions, providing clear, immediate visual cues.

Ultrasonic Sensor - A sensor that uses sound waves to measure the distance to the water
surface, determining water levels.

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 Chapter 2

METHODOLOGY

Materials

In this project, the following components and materials were used: Ultrasonic Sensor,
ESP32 Microcontroller, Battery Case, Battery, Buck Converter, Micro USB Cable, Utility
Box, Consumables (Jumper Wires, Lead & Screws), and Switch.

Figure 1. Flow Chart of the Study

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 Construction of the SMARTFLOODGUARD Device

Attaching the Battery Pack

The ESP32 system was established to set up the power supply. A battery pack,
typically providing a higher voltage, such as 9V or 12V, was connected to the input
terminals of a buck converter. The buck converter was responsible for stepping down the
input voltage to a stable 3.3V, necessary for the proper functioning of the ESP32. The
buck converter was adjusted using a small screw mechanism to fine-tune the output
voltage. A multimeter was used to verify that the converter output exactly 3.3V before
connecting it to the ESP32.

Incorporating the Switch

Once the buck converter was adjusted to output the correct voltage, a switch was
integrated into the circuit. The output of the buck converter was connected to the ESP32
through the switch. This allowed for easy control of the power supply to the ESP32,
enabling users to turn the device on or off as needed. The switch simplified power
management, enhanced energy efficiency by preventing unnecessary power draw when
the ESP32 was not in use, and extended battery life. It also added convenience by
eliminating the need to physically disconnect and reconnect the battery pack.

ESP32 Connections

The correct power connections between the ultrasonic module and the ESP32 were
established. The VCC pin of the ultrasonic module was connected to the 5V pin on the
ESP32 to supply the necessary power. Similarly, the GND pin of the module was
connected to one of the ESP32’s ground pins. It was important to verify that the 5V pin
on the ESP32 could supply adequate current to the ultrasonic module without causing an
overload. Ensuring proper power connections was essential for the ultrasonic module to
function correctly and reliably.

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Connecting the Sensor Pins

After completing the power connections, the ultrasonic module’s Trigger and Echo
pins were connected to specific GPIO pins on the ESP32. The choice of GPIO pins varied
depending on the application and the code being used. Accurate pin assignment and
secure connections were critical for effective communication between the ultrasonic
sensor and the ESP32, ensuring that data transmission was reliable and accurate.
Integrating the LED indicators and Buzzer

To provide visual and auditory alerts, an LED system with red, orange, and green
LEDs, along with a buzzer, was added to the FLOODGUARD device. Each LED
represented a different status: the green LED indicated an alert level, the orange LED
signaled an Alarm level, and the red LED represented a Critical water level, warning of
severe flooding risk. The LEDs were connected to individual GPIO pins on the ESP32
with resistors to limit current. Additionally, a buzzer was connected to another GPIO pin
and programmed to activate alongside the red LED, providing an audible alarm. This
setup allowed the device to provide real-time feedback on water levels through lights and
sound, enhancing its flood warning capabilities.

Figure 2. Circuit Diagram of the Study

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Ultrasonic Sensor Setup

The waterproof ultrasonic sensor was connected to the ultrasonic module. The sensor
emitted ultrasonic pulses and measured the time it took for the pulses to bounce back from an
object, such as the water surface.

Programming the ESP32

The ESP32 was connected to a computer using a USB cable. Code was written and
uploaded to the ESP32 to control the ultrasonic sensor, read distance measurements, and
process them according to the application. The code set the Trigger pin high for a short
duration to send a pulse, then measured the time it took for the Echo pin to go high. This
pulse duration was converted into a distance measurement.

Placing the Sensor in the Utility Box

The sensor was mounted in a position that provided a clear line of sight for accurate
distance measurements. Appropriate hardware was used to secure the sensor to prevent
movement. The wiring was routed and secured to avoid interference and potential damage,
ensuring stable and insulated connections. After mounting and wiring, the sensor was tested
to confirm proper operation. The setup was finalized by sealing the utility box to protect
against environmental factors, and the configuration was documented for future reference and
maintenance.

Testing and Deployment

After the code was uploaded, the USB cable was disconnected. The switch was used
to power on the circuit with the battery pack. The ESP32 outputs were monitored via a serial
monitor to check if the ultrasonic sensor was functioning correctly and providing accurate
distance measurements

The voltage and current ratings specified for each component were strictly adhered to.
Each part was verified to ensure it operated within its designated limits to prevent overheating
and damage. Components were regularly monitored during operation, and any that showed
signs of overheating were replaced.

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 Additionally, the device was protected from water exposure. Waterproof components,
such as specific ultrasonic sensors, were identified, and all non-waterproof electronics were
kept dry and shielded to ensure proper functionality.

Final Adjustments

The code and physical setup were fine-tuned, including sensor placement and power
adjustments, if necessary. The circuit was securely housed, especially since the waterproof
ultrasonic sensor could be exposed to moisture or water. This setup was intended for
applications like water level monitoring, distance measurement in industrial setups, or
environmental sensing.

Process Flow in Programming the SMARTFLOODGUARD Device

Programming the SMARTFLOODGUARD system involved a structured process that

began with developing the code to manage water level monitoring and integrating it with the
Blynk IoT platform. The ESP32 microcontroller was then connected to a computer via USB
to upload the code.

Once the code was uploaded, the device was tested in a controlled environment, such
as a drum container filled with water, to simulate flood conditions. This ensured that the
sensors accurately detected water levels and the system sent notifications as expected.

Figure 1. Procedures in Programming the Device

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Testing the Sensing Device Reading of SMARTFLOODGUARD Device

Figure 3. Programmed Water Level Conditions and Their Ranges

WATER LEVEL CONDITION

(m)

0.2 – 0.39 ALERT

0.40 – 0.59 ALARM

0.60 – Above CRITICAL

Figure 3 shows the programmed water level conditions and their corresponding ranges.
These were utilized to test the accuracy of the SMARTFLOODGUARD device.

A controlled set- up with an initial amount of water, and the SMARTFLOODGUARD

device was positioned at a precise height to accurately monitor changes in the water level.
The experiment was conducted in three phases: alert, alarm, and critical conditions, each with
multiple trials to ensure consistency in the device’s performance.

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 For the Alert Condition, three trials were performed. In the first trial, the
SMARTFLOODGUARD measured the initial water level in the controlled set-up. In the
second and third trials, water was gradually added, and the device recorded the increasing
levels under alert conditions, this indicates the need to prepare for evacuation. The goal was
to ensure the device could accurately capture variations in this phase.

In the Alarm Condition, three additional trials were conducted. More water was
added until the level reached the alarm threshold, indicating potential flooding risks. The
SMARTFLOODGUARD device continuously monitored and recorded these changes,
ensuring accurate detection, reliable notification, and sound alarms once the water level
approached the alarm level.

For the Critical Condition, another three trials were performed by adding more water
to the controlled set-up until it reached the alert threshold, signifying dangerous flooding
levels.

The SMAERTFLOODGUARD device was tested for its ability to reliably detect and signal
this critical condition, providing timely warnings and alarm to ensure safety.

Safety Precautions While Assembling the Device

To ensure the safety and reliability of the SMARTFLOODGUARD system, the

researchers followed established procedures. All connections within the device were secured
by carefully inspecting and tightening each one to prevent short circuits. Proper insulation and
firm attachment were essential to avoid potential malfunctions or damage caused by loose or
poorly connected wires.

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 Chapter 3

RESULTS AND DISCUSSIONS

This chapter presents the results of the study based on the thorough evaluation of the
FLOODGUARD Device.

Table 1. Sensing Device Reading with Response Text Under Alert Condition

Level of Water

TRIAL RESPONSE TEXT

Steel Tape Smart

Measure FloodGuard

1 0.41 meters 0.41 meter EVACUATION IS INFORCED.

The water level is below 60% and
approximately .90 meters high or
lower.

2 0.57 meters 0.57 meter EVACUATION IS INFORCED.

The water level is below 60% and
approximately .90 meters high or
lower.

3 0.57 meters 0.57 meter EVACUATION IS INFORCED.

The water level is below 60% and

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 approximately .90 meters high or
lower.

The SMARTFLOODGUARD device demonstrated exceptional accuracy, measuring water levels

of 0.41 meters and 0.57 meters, consistently aligning with the readings from the steel tape measure in
all trials. The response text was issued without triggering a sound alarm, which was appropriate given
the low-risk scenario.

This approach ensures that users are notified of potential risks without causing undue panic,
fostering a calm yet alert environment. The precision of the SMARTFLOODGUARD's readings
emphasizes its reliability in monitoring early flood risks, enabling users to take timely precautionary
measures. This performance highlights the device’s role in supporting proactive disaster preparedness
through clear notifications.

Table 2: Sensing Device Reading with Response Text Under Alarm Condition

Level of Water

TRIAL RESPONSE TEXT

Steel Tape Smart

Measure FloodGuard

1 0.89 meter 0.89 meter PREPARE FOR EVACUATION.

The water level is above 61% and
approximately .91 meters high or
lower.

2 0.90 meter 0.90 meter PREPARE FOR EVACUATION.

The water level is above 61% and
approximately .91 meters high or
lower.

3 0.93 meter 0.93 meter PREPARE FOR EVACUATION.

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 The water level is above 61% and
approximately .91 meters high or
lower.

During the Alarm condition, the SMARTFLOODGUARD consistently matched the steel tape
measure with readings of 0.89 meters, 0.90 meters, and 0.93 meters, maintaining high accuracy.
It issued the response text accompanied by a medium-pitched, intermittent sound alarm. This
combination of precise detection and audible alerts effectively reinforces the need for
heightened awareness and preparedness.

The audible alarm draws attention to the escalating risk, ensuring users are encouraged to
take proactive actions such as securing their property and planning evacuation routes. The
system’s performance during this condition strengthens its ability to manage transitional flood
risks, maintaining urgency without creating panic.

Table 3: Sensing Device Reading with Response Text Under Critical Condition

Level of Water

TRIAL RESPONSE TEXT

Steel Tape Smart

Measure FloodGuard

1 1.06 meter 1.06 meter MANDATORY EVACUATION.

The water level is above 81% and
approximately 1.20 meters high
or higher.

2 1.14 meter 1.14 meter MANDATORY EVACUATION.

The water level is above 81% and
approximately 1.20 meters high
or higher.

3 1.18 meter 1.18 meter MANDATORY EVACUATION.

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 The water level is above 81% and
approximately 1.20 meters high
or higher.

The SMARTFLOODGUARD recorded accurate water levels of 1.06 meters, 1.14 meters,
and 1.18 meters, consistent with the steel tape measure’s readings. The response text was
accompanied by a high-pitched, continuous sound alarm to highlight the severe and life-
threatening nature of the situation. The continuous alarm serves to immediately alert users of the
critical condition, ensuring that evacuation becomes the top priority.

The device’s precise measurements and the urgency conveyed by the persistent alarm
ensure swift action, minimizing risks in extreme flood scenarios. This performance underlines
the SMARTFLOODGUARD's purpose of delivering reliable, accurate, and actionable guidance
during high-stakes emergencies, helping to safeguard lives during critical flood events.

Accuracy of Length Measurements by Computing SMARTFLOODGUARD with a Steel

Tape Measure

Steel Tape Measure Smart FloodGuard

0.57 meter 0.57 meter

0.93 meter 0.93 meter

1.18 meter 1.18 meter

The accuracy of the SMARTFLOODGUARD device was assessed by comparing its

measurements with those taken from a steel tape measure. In all three trials, the
FLOODGUARD provided readings that matched the steel tape measure exactly. For instance,
at 0.57 meters, the SMARTFLOODGUARD recorded the same value, showing perfect
alignment. Similarly, for water levels of 0.93 meters and 1.18 meters, the FLOODGUARD's

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readings were identical to the steel tape measure, demonstrating 100% accuracy in all cases.
This high level of precision validates the device's reliability and effectiveness in monitoring
water levels for flood detection.

Table 4. Cost of the SMARTFLOODGUARD Device

MATERIALS COSTS

Ultrasonic Sensor ₱395

Esp32 Microcontroller ₱367

Battery Case ₱178

Battery ₱955

Buck Converter ₱125

Micro USB Cable ₱76

Utility Box ₱230

Consumables (Jumper Wires, Lead & ₱150

Screws)

Switch ₱40

LED (green, orange, red) ₱105

Resistors ₱20

Buzzer ₱140

Total: ₱2781

Table 4 provides a detailed breakdown of the individual and total costs incurred in
developing the SMARTFLOODGUARD system. The documentation shows a total
expenditure of ₱2,781, covering all materials used in the construction.

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 This comprehensive breakdown underscores the system’s cost-effectiveness, demonstrating
that it can deliver reliable and efficient flood detection without demanding a large financial
investment. The affordability paired with its functionality makes SMARTFLOODGUARD an
accessible solution for communities prone to flooding, ensuring that safety does not come at
an excessive cost.

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 Chapter 4

CONCLUSIONS AND RECOMMENDATIONS

Conclusions

After examining the results of the study, the following conclusions were drawn:

The SMARTFLOODGUARD system has consistently demonstrated accurate tracking

of water levels across alert, alarm, and critical conditions, proving its reliability as an early
warning device for flood preparedness. Its ability to provide real-time data and send timely
alerts enables communities and authorities to take swift action, significantly reducing flood
risks. The cost analysis, which totals ₱2,781, underscores the affordability of the system,
making it a cost-effective solution for flood detection, especially in areas with limited
resources. Despite its low cost, SMARTFLOODGUARD remains effective in monitoring
water levels and providing essential alerts, proving to be an invaluable tool for flood
management. By utilizing IoT technologies like the ESP32 microcontroller and Blynk for
remote monitoring, SMARTFLOODGUARD leverages the power of IoT to deliver smooth
data transmission, clear visual alerts, and sound alarms during the Alarm and Critical states,
ensuring users receive timely, appropriate notifications. The simplicity, low cost, and
efficiency of the SMARTFLOODGUARD system make it ideal for widespread deployment
in flood-prone areas, offering practical, cost-effective flood detection solutions for both urban
and rural communities, particularly in regions lacking advanced flood monitoring
infrastructure.

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Recommendations

To improve the SMARTFLOODGUARD system, several important recommendations

are suggested. First, conducting pilot tests in different areas with varying conditions will help
understand how the system performs and allow for adjustments to improve its effectiveness.

Second, partnering with local emergency services is key to ensuring

SMARTFLOODGUARD is part of current disaster management plans, enabling a
coordinated response during floods. This collaboration will help speed up decision-making
and make evacuations more efficient.

Additionally, creating a feedback system where users can share their experiences and
suggestions will provide useful insights for future improvements. This will help ensure the
system stays effective and meets the needs of the community. By following these
recommendations, SMARTFLOODGUARD can continue to improve and better serve its
purpose in flood prevention and response.

25
 ACKNOWLEDGEMENT

This research would like to extend the immeasurable appreciation and gratitude for the
support of the following persons who helped us and contributed to making this study
possible.

To Joseph C. Inggan Ph. D., head of the Science Department, whose brilliant insights and
countless suggestions for the improvement of this study. His mentorship opened doors to
numerous opportunities that made this research possible.

To Ethel N. Urian Ph. D., whose unwavering patience and support were instrumental
throughout the entire research process.

To Mr. Sam Lester Capacite Agcaoili, and Mr. Ronald Molina Apolinario Jr. for their
invaluable assistance in conducting this study. They turned this study into a tangible reality.

26
To our parents. Mr&Mrs. Sagisi, and Mr&Mrs. Coloma, and Mr&Mrs. Cachola for
their prayers, boundless love, sacrifices, and financial support served as a wellspring of
inspiration, guiding us through every obstacle and ultimately contributing to the successful
completion of this work

Most of all, to the God Almighty, for guiding us throughout this conduct, illuminating our
paths and ensuring our safety.

BIBLIOGRAPHY

Chandrika, M. S., Author2, A. B., & Author3, C. D. (2023). IoT-energy: Possibility of

enhanced IoT data systems and architecture for efficient data handling. SmartTech
Publishing. https://www.smarttechpublishing.com/iot-energy-systems

Daud, E., & Bakar, M. I. (2021). Possibility of early warning of floods to residences near
bodies of water. FloodTech Solutions. https://www.floodtechsolutions.com/early-
warningfloods

Hadi, M., Author2, E. F., & Author3, G. H. (2020). Efficiency of early warning, flood
detection, and water level monitoring using GPS and IoT. IoT Innovations Press.
https://www.iotinnovationspress.com/early-warning-flood-detection

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Diriyana, A., et al. (2019). Possibility of generating Flood Detection System which can track
water level. possible outcomes. Diriyana, A., et al. Research 17, 143-145. Flood Detection
System

APPENDICES A
MATERIALS USED

Ultrasonic Sensor is an instrument that

measures the distance to an object using
ultrasonic waves.

ESP32 Microcontroller is a chip that

provides Wi-Fi and Bluetooth
connectivity for embedded devices.

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 A Battery Case is a container designed to
hold and to protect batteries. It keeps the
batteries secure and organized, that
makes them easily used in various
devices.

18650 Battery is a rechargeable

lithiumion battery. They tend to have a
nominal voltage of 3.6V and range in
capacity from 1800mAh to 3600mAh.

Buck Converter is a Dc-to-Dc Converter

that efficiently converts a high voltage to
a low voltage efficiently.

Micro USBs are used for various

applications, from powering and
charging smaller devices to transmitting
data between them.

Utility Box is a type of box that houses

electrical sockets, switches, or other
fixtures.

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 Jumper Wires are simply wires that have
connector pins at each end, allowing them
to be used to connect two points to each
other without soldering.

Lead Wire is a single conductor wire

insulated with plastic or rubber. It is used
to connect the component to a circuit or
another component.

A Screw is a small metal rod with a notch

in the top that’s used as a fastener. It is
capable in tightening or released by a
twisting force to the head.

Rocker Switch is an electrical switch that

is being pressed on one side to turn a
device on and the other to turn it off.

30
 LED (Light Emitting Diode) is a
semiconductor device that emits
light when current flows through
it. It is commonly used as an
indicator to signal various
conditions, with different colors
representing different statuses or
warnings.

A Buzzer is an electronic
component that produces a loud
sound to alert or draw attention to
a specific condition or event. It is
used to provide an audible
warning or notification, often in
emergency situations.

APPENDIX B

Pictorials

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 Connecting the Sensor Connecting the Sensor Pins

Connecting the Battery Pack Programming

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Placing the sensor in the utility box Finished Product

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 APPENDIX C

Testing of the device on the three water level states

Alert Alarm

Critical

34
 APPENDIX D

Consultation with the MDRRMO

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