IoT‑Enabled Real‑Time Monitoring for Disaster Management and

Sustainable Energy Optimization

P. Sukumar, Elamathi T. M., Dhanish S. and Manoj V.

Department of Computer Science and Engineering, Nandha Engineering College (Autonomous), Erode, Tamil Nadu, India

Keywords: Real‑Time Monitoring, Solar Tracking, Sustainable Energy, Arduino IoT Cloud, Blynk Integration, Vibration

Detection, Motion Security, Forest Fire Alert, Battery Management, Streetlight Monitoring, Renewable

Energy, Wireless Sensors, Automated Alerts.

Abstract: This research gives a comprehensive approach to monitoring with the implementation of an IoT-based system

that integrates various sensors and microcontroller that track the forest fires, land vibration levels, solar energy

efficiency, battery voltage and charge percentage, motion detection, and streetlight failures. One of the plus

features of this system is that it has an intelligent solar tracking mechanism in which a server motor tracks the

solar panel dynamically to maximize solar light absorption, hence increasing energy efficiency. Additionally,

a motion sensor will allow detection of unauthorized activities. The data collected from all the sensors by the

local XAMPP server, since it uses database in the objective of effective data logging and retrieval. There is a

web-based dashboard. The project enhances remote access also by integrating with Arduino IoT Cloud and

Blynk, allowing real-time graphical analysis, sensor readings of all the sensors, and control of the system

from any area.

1 INTRODUCTION

An IoT-based system for monitoring and automation

contains a mix of various sensors and a NodeMCU

microcontroller to monitor the main environmental

and security parameters like solar energy efficiency,

battery voltage level, motion detection, fire hazard,

seismic activity, and streetlight failure. G. S, P.

Umaeswari, et al., 2024; S. Durgadevi, et al, 2024,

The system's parameters reflect its high

responsiveness and sustainability in the fields of

security and energy efficiency through wireless

communication. Apart from that, key to this is the use

of a solar tracking mechanism that dynamically

adjusts the orientation of the solar panel through a

servo motor, thereby maximizing absorption of sun

rays and overall energy efficiency. D. M, S. A and S.

R, et al., 2023. The battery management system

allows energy stored in the battery to be used more

efficiently by observing the voltage levels, charge

percentage, and overall health of the battery. S. K.

Gupta and R. K. Singh, et al., 2023, For security, the

motion detection PIR sensors were used to observe

the environment and provide immediate alerts. M. S.

Hossain, et al, 2023, There is a high risk of fire in

several environments. The initiative is installing a fire

detection system based on flame sensors to raise early

warnings, allowing quick preventive steps A. K.

Verma et al, 2022. R. G. Baldovino, et al., 2024,

Another important feature is monitoring seismic

activity, with vibration sensors detecting movements

of the ground, helping in disaster prevention by

alerting authorities in case of potential landslides or

earthquakes. J. V. Anchitaalagammai, et al, 2023; A.

Sharma, et al., 2023. Additionally, street lighting

monitoring and automation for energy-efficient

usage. This system makes use of LDR sensors for

controlling the streetlights according to ambient light

conditions and simultaneously detects

malfunctions/failures for continuous illumination on

the streets. S. S. Vellela, et al, 2023, All the data

gathered from these sensors are stored and processed

into an XAMPP server. Users can access and analyze

information on an interactive web dashboard that

gives real-time graphical reports. R. Maruthaveni, et

al, 2023; F. T. Zohora Saima, et al, 2022, Beside all

this, integration with the Arduino IoT cloud and the

Blynk platform enhances further the cause of remote

access and control so that a user is able to monitor

sensor readings or receive automated alerts from

anywhere through a smartphone.

354

Sukumar, P., M., E. T., S., D. and V., M.

IoT-Enabled Real-Time Monitoring for Disaster Management and Sustainable Energy Optimization.

DOI: 10.5220/0013882900004919

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies (ICRDICCT‘25 2025) - Volume 2, pages

354-359

ISBN: 978-989-758-777-1

2 RELATED WORKS

Several research efforts have focused on integrating

IoT-based monitoring systems for disaster

management, energy optimization, and environmental

sustainability. The following studies provide insight

into various aspects relevant to this project.

Seetharaman et al. developed a system for real-time

fire detection and alert. Use of IoT-based sensors for

fire hazards and alerts, which is most useful in remote

locations where an immediate response is necessary

to mitigate wide-ranging losses due to fire

destruction. The output of our project is expanded to

fire detection with one or combination of other

disaster monitoring systems, such as vibration

analysis for landslide prediction. This work presents

an implementation of a real-time earthquake

monitoring system based on seismic activities.In

contrast to this setup, our project employs local

vibration sensors in concurrent monitoring of seismic

activity at any moment to ensure localized disaster

mitigation without the need for external data feeds.

Gupta and Singh introduced smart motion detection

system based on IoT using NodeMCU and Blynk that

provides monitoring through real-time security alerts.

This project enhances it by integrating motion

detection with additional security features of real-time

alarms and web monitoring in order to ensure real-

time security for remote areas. Durgadevi et al.

suggested a solar monitoring system on IoT, which

aids real-time monitoring of solar power generation

efficiency. Their system collects and analyzes solar

energy data periodically for performance

optimization. Our project enhances this by

implementing a dynamic solar tracking mechanism

using servo motors to maximize the absorption of

solar energy for efficient utilization.

Anchitaalagammai et al. developed an IoT-based

automated streetlight control system for fault

detection and reporting. System ensures efficient

functioning of streetlight, with reduction of power

wastage.

We extend this work on integrating LDR-based

streetlight control system and fault detection to ensure

real-time alerts in case of a malfunction and efficient

power consumption. Most recently, G. S et al.

explored IoT applications to monitor earthquakes and

fire detection indirectly, emphasizing the importance

of integrating safety measures with IoT. Our work

also develops on this, integrating vibration

monitoring, fire detection, and security surveillance

into one IoT-based setup. The studies reviewed above

give instances where IoT has been proved to be a great

assist in disaster management, but it is unique in our

project since it embodies such multifaceted

monitoring features in a common system, thereby

maximizing the capacity for real-time monitoring in

relation to sustainability, security, and disaster

averted.

3 METHODOLOGY

3.1 Landslide Detection System Using

Vibration Sensors

An IoT-based landslide monitoring and detection

system, making use of vibration sensors, is correlated

with this part of our project, which also seeks to

implement IoT-based real-time environmental

monitoring. While the focus of Bhardwaj's work is

disaster avoidance, our system adds on and expands

the scope to that of solar energy optimization, battery

monitoring, streetlight fault detection, and security

upgrades. Both the works emphasize IoT-based real-

time data collection, storage, and visualization to

develop sustainable and smart infrastructure that

ensures proactive decision-making and better

resource management.

3.2 Real Time Fire Detection and

Intimation System

This project is aimed to use IoT sensors for detecting

fire hazards so that instant intimation can be

communicated to avoid damage. We are following

same approach in our project but instead of only fire

detection we also want to monitor environmental

risks like vibrations (landslide), optimize solar energy

and streetlight failures. Since both projects require

real-time data collection and cloud-based

notifications to ensure a rapid response, the two sets

of techs are an excellent fit. Our system is built on

integrated sensors and automated alerts for

environmental & infrastructure monitoring with an

extended scope of safety, efficiency and reach.

3.3 Motion Detection Sensors for

Monitoring in a Smart Campus

The motion sensor in the IOT-based smart monitoring

system provide the best options to enhance security

for the energy efficiency that provides automatic

monitoring for the whole campus. By detecting

movements from different areas, the system can

assume intelligence by turning lights on and off,

ringing security alarms, or alerting authorities via

IoT-Enabled Real-Time Monitoring for Disaster Management and Sustainable Energy Optimization

355

unauthorized access. This approach made the campus

safer and really cost-effective with respect to energy.

3.4 IoT-Based Automated Street Light

Control with Fault Detection and

Reporting System

This project proposes a smart control system for

managing street light while also detecting street light

faults and reporting them in real-time. The automation

ensures efficiency in energy consumption, a reduction

in manual intervention, and an increase in the

response time for maintenance. This project extends

the smart street light control systems to IoT-based

fault detection, optimizes solar energy utilization and

monitors the environment. Their work has primarily

focused on streetlight automation and fault reporting,

while our approach includes further applications

toward public safety and infrastructure management

with the intention of creating a truly integrated smart

management system.

3.5 IoT-Based Power Quality

Monitoring in Smart Grid

In our project, to address both power efficiency and

sustainability we used the concept of voltage

monitoring along with battery percentage while

managing a smart street lighting system which in turn

follow these design principles. Our system uses IoT

sensors for data collection resulting in energy

conservation, intelligent battery usage and preventive

fault detection. This not only makes the grid more

reliable and power distribution efficient, but also

helps in creating a smarter as well as stronger

infrastructure.

3.6 Battery Storage and Power

Reliability in Off-Grid Systems

Battery storage systems serve as a anchor for the solid

foundation of off-grid solar solutions, especially in

regions with irregular sunshine. Nowadays, it is well-

accepted that battery technologies are more than

capable of capturing excess solar energy and giving a

steady supply of energy during, say, cloudy conditions

or nighttime.

From the discussions, battery health is being

expressed in such a way as to ensure long service and

effective energy use. Energy independence for stand-

alone communities entails less reliance on external

sources of supply, thus allowing for a more self-

sufficient and resilient energy supply. Figure 1

illustrates the system architecture design.

Figure 1: System Architecture Diagram.

4 EXPERIMENTAL RESULTS &

DISCUSSION

We have deployed IoT-enabled sustainable

monitoring and the real-time tracking system which

effectively reveals it efficiency in terms of

environmental parameters monitoring energy usage

optimization and security enhancement in secluded

places. The efficiency of the system was tested

against different parameters to determine its handling

with regards to data collection and processing, as well

as response mechanisms. Figure 2 shows the IoT-

Based Smart Monitoring System Prototype.

Figure 2: IoT-Based Smart Monitoring System Prototype.

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COMMUNICATION, AND COMPUTING TECHNOLOGIES

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4.1 Real-Time Data Acquisition and

Monitoring

The Data from a lot of sensors including vibration,

fire, motion and LDR were effectively collected by

the NodeMCU micro controller. This data was then

sent from NodeMCU to a local XAMPP server and

displayed in visual format on the arduino IOT cloud

platform and at same time this is streamed up live on

blynk dashboard. The visualization of sensor values

made a significant contribution to the fact that users

could quickly access current data of the environment.

Figure 3 shows the Real-Time Monitoring on Arduino

IoT Cloud.

Figure 3: Real-Time Monitoring on Arduino IoT Cloud.

4.2 Landslide and Fire Detection

The vibration sensor was able to recognize that there

was an unusual movement of land and send alerts

when it went above given limits. In the same way, the

fire sensor detects flame perfectly and sent real time

notifications through Blynk mobile app. These kind of

early warning systems were relied upon to manage a

disaster and keep the safety features in place (figure 3

and 4).

Figure 3: Landslide Monitoring.

Figure 4: Fire Detection.

4.3 Energy Optimization through Solar

Tracking

The servo-controlled solar panel was capable of

following a shrinking shadow dynamically and

receive the maximum amount of sunlight. Battery

voltage and percentage monitoring takes good care of

power usage, which avoid sudden shutdown. The

tracking system, which enables the setup to capture

energy through its adjustment of solar panels

according to position and time of day, which makes

this project more sustainable. Figure 5 shows the

Solar Voltage and Battery Charge Monitoring.

Figure 5: Solar Voltage and Battery Charge Monitoring.

4.4 Security and Fault Detection

The motion sensor properly responded to

unauthorized activities and alarmed the detection of

breaches, so that security is heightened. This LDR-

based streetlight fault detection system successfully

identified faulty lights, by generating the required

notifications to maintain them. Figure 6 depicts the

motion sensor activity monitoring.

IoT-Enabled Real-Time Monitoring for Disaster Management and Sustainable Energy Optimization

357

Figure 6: Motion Sensor Activity Monitoring.

4.5 System Performance and

Reliability

The system was reliable to a high degree of accuracy

in real-time tracking and data processing. The quick

response for alerts was important to offer instant

recognition of potential threats. Its integration with

cloud-based platforms made it effortless for remote

monitoring and analysis. Figure 7 shows the Arduino

IoT Cloud Visualization.

Figure 7: Arduino IoT Cloud Visualization.

5 CONCLUSIONS

This outlines one complete system of IoT that is

meant for infrastructure management via real-time

monitoring, analysis of power quality, and fault

detection using real-time techniques. The connecting

devices will be visible, displayed and controlled

remotely through the Arduino IoT Cloud and Blynk.

The information such as motion detection, voltage

level, and battery percentage are safely stored for

proper data management and analysis on the XAMPP

server. The smart streetlights work with energy-

saving mechanisms to facilitate remote fault detection

that relieves maintenance pressure and increases

reliability. A whole list of renewable energy,

especially solar energy, propels a step toward

realizing the journey to sustainable flow towards the

mass adoption of Smart technology. Future

enhancements will include the use of machine

learning-based predictive analytics, edge computing

for real-time data processing, and blockchain

technology applications for secure data storage, thus

opening up the era of smart, efficient, and resilient

technology.

6 FUTURE WORK

The vision for future iterations of this project is to

further supplement the system with powerful AI-

based algorithms such as predictive maintenance and

fault detection. Data trend analysis and projections /

Machine Learning Models can be used to further tune

the system in order to predict future energy demand

patterns so that we can use power more efficiently.

Further, it’s possible to use edge computing to help

reduce the data latency and reliance on cloud servers.

Including environmental factors in the monitoring

system, like quality of air and temperature to provide

a more complete intelligent solution. In the future,

additional efforts will be concentrated on scalability

towards large-scale deployments in smart cities for

sustainable energy solutions and urban management.

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