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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue III, March 2026
Energy-Efficient Automation System Using Sensor and IOT
Kathires J
1*
,Mamathi Saru G
2
, Ramer M
3
Department of Electrical Engineering; Sri Ranganathar Institute of Engineering and Technology
Coimbatore, India
*
Corresponding Author
DOI:
https://doi.org/10.51583/IJLTEMAS.2026.150300119
Received: 28 March 2026; 02 April 2026; Published: 23 April 2026
ABSTRACT
This paper presents an energy-efficient smart automation system based on a hybrid sensing approach using
Passive Infrared (PIR) and ultrasonic sensors integrated with Internet of Things (IOT) technology. The main
objective of the system is to reduce unnecessary energy consumption by automatically controlling electrical
appliances based on human presence.
The PIR sensor is used to detect motion, while the ultrasonic sensor measures distance to identify both moving
and stationary occupants. A predefined threshold distance of 150 cm and a delay time of 45 seconds are
implemented to ensure reliable operation and to avoid unnecessary switching. The sensed data is processed using
the ESP 32 microcontroller, which controls the appliances through a relay module.
The system supports both local and remote control. A web-based interface developed using XAMPP enables
users to monitor and control appliances within a local network, while Blynk Cloud allows remote access through
a mobile application. In addition, voice control functionality is provided through the application interface for
user convenience.
Experimental results confirm that the proposed system effectively reduces energy consumption and achieves
significant energy and cost savings under practical operating conditions. The system is simple, cost-effective,
and suitable for applications such as smart classrooms, homes, and offices
Keywords: IOT, Energy Efficiency, Ultrasonic Sensor, ESP 32, PIR
INTRODUCTION
Energy conservation has become a critical requirement in modern society due to the increasing demand for
electricity and the rising cost of energy resources. In many indoor environments such as classrooms, offices, and
residential buildings, electrical appliances like lights and fans are often left ON unnecessarily, leading to
significant energy wastage. This issue highlights the need for intelligent automation systems that can efficiently
manage electrical loads without continuous human intervention.
Recent advancements in Internet of Things (IOT) technology have enabled the development of smart systems
capable of monitoring and controlling devices in real time. IoT-based automation systems offer improved
convenience, flexibility, and energy efficiency by allowing devices to communicate over wireless networks. In
this context, occupancy-based control systems play a crucial role in reducing unnecessary power consumption
by automatically switching appliances based on human presence.
Various sensors have been used for occupancy detection, among which Passive Infrared (PIR) sensors and
ultrasonic sensors are widely adopted. PIR sensors detect motion based on infrared radiation emitted by the
human body and provide wide-area coverage. However, they may fail to detect stationary occupants. On the
other hand, ultrasonic sensors measure distance using high-frequency sound waves and can detect both moving
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and stationary objects, but they have limited coverage. Therefore, relying on a single sensor may not provide
optimal performance.
To overcome these limitations, this paper proposes a hybrid sensing approach that combines PIR and ultrasonic
sensors for accurate and reliable human presence detection. The system utilizes an ESP 32 microcontroller as
the central control unit, which processes sensor data and controls electrical appliances through a relay module.
Additionally, a web-based interface is developed using XAMPP to enable remote monitoring and manual control
of appliances via Wi-Fi.
The novelty of the proposed system lies in its hybrid sensor integration, which enhances detection accuracy
while reducing false triggering and energy wastage. A delay-based control mechanism is also implemented to
improve user comfort and prevent frequent switching of appliances. The system is designed to be cost-effective,
scalable, and easy to implement, making it suitable for applications in smart classrooms, homes, and offices.
Overall, the proposed system contributes to energy conservation by providing an efficient and intelligent
automation solution that combines real-time sensing, IoT communication, and user-friendly control.
LITERATURE REVIEW
Recent advancements in smart building technologies have significantly improved energy efficiency through the
integration of Internet of Things (IoT) and sensor-based automation systems. Several studies have explored
occupancy detection and intelligent control of electrical appliances to reduce unnecessary energy consumption
in indoor environments.
Kumar et al. (2020) proposed a microcontroller-based smart home automation system that automatically controls
lighting and electrical appliances based on user presence. Their system demonstrated reduced energy
consumption; however, it primarily relied on simple motion detection, which may not accurately detect
stationary occupants.
Patel and Sharma (2021) developed an IoT-enabled automation system that allows remote monitoring and control
of appliances through a web-based interface. While the system improved user convenience and flexibility, it
lacked robust occupancy detection mechanisms, leading to potential inefficiencies in energy management.
Rao et al. (2019) investigated the use of ultrasonic sensors for occupancy detection, highlighting their ability to
accurately measure distance and detect both moving and stationary objects. The study showed improved
detection reliability compared to traditional motion sensors, especially in environments with varying lighting
conditions.
Similarly, Singh et al. (2022) implemented a smart classroom automation system using PIR sensors for motion
detection combined with IoT-based control. Although the system provided wide-area coverage, it faced
limitations in detecting occupants who remained stationary for extended periods, which affected overall
efficiency.
Recent studies by Zhang and Kong (2025) and Elhassan (2026) emphasized the importance of advanced
occupancy detection techniques using hybrid sensing and intelligent algorithms to enhance energy efficiency in
smart buildings. These works suggest that combining multiple sensors can significantly improve detection
accuracy and reduce false triggering.
From the above studies, it is evident that single-sensor-based systems, such as PIR-only or ultrasonic-only
approaches, have inherent limitations in terms of coverage and accuracy. Therefore, there exists a research gap
in developing a cost-effective hybrid system that combines the advantages of multiple sensors while maintaining
simplicity and reliability.
To address this gap, the proposed work introduces a hybrid sensing approach that integrates both PIR and
ultrasonic sensors with an ESP 32-based IoT platform. This combination enhances occupancy detection
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accuracy, ensures reliable operation for both moving and stationary users, and improves overall energy
efficiency. The system also incorporates a web-based control interface, providing both automation and user
flexibility.
METHODOLOGY
System Operation
The proposed energy-efficient automation system operates based on real-time human presence detection using
a hybrid sensing approach that integrates a Passive Infrared (PIR) sensor and an ultrasonic sensor. The system
continuously monitors the environment and automatically controls electrical appliances such as lights and fans
to minimize unnecessary energy consumption.
Initially, the PIR sensor scans the surrounding area to detect motion by sensing infrared radiation emitted by the
human body. Due to its wide detection angle, the PIR sensor can cover a large portion of the room and provides
an initial indication of occupancy. However, since PIR sensors are unable to detect stationary occupants
effectively, an ultrasonic sensor is used to enhance detection accuracy.
The ultrasonic sensor operates by emitting high-frequency sound waves (approximately 40 kHz) and measuring
the time taken for the echo to return after reflecting from an object. Using this time-of-flight principle, the
distance between the sensor and the object is calculated. A predefined threshold distance of 150 cm is set in the
system to determine the presence of a person.
The ESP 32 microcontroller continuously receives data from both sensors and processes the inputs using
programmed control logic. When the PIR sensor detects motion or the ultrasonic sensor measures a distance less
than the threshold value, the system identifies that a person is present in the monitored area. As a result, the ESP
32 sends a control signal to the relay module, which switches ON the connected electrical appliances.
In contrast, when no motion is detected and the measured distance exceeds the threshold value, the system
assumes that the area is unoccupied. To avoid frequent switching due to temporary absence or sensor noise, a
delay timer of 45 seconds is implemented. If no presence is detected during this interval, the ESP 32 deactivates
the relay module, thereby switching OFF the appliances and reducing energy wastage.
Additionally, the system supports manual control through an IoT-based web interface developed using XAMPP.
The ESP 32 connects to the local Wi-Fi network and communicates with the web server, allowing users to
monitor and control appliances remotely using a web browser. User commands are processed in real time,
enabling flexible operation alongside automatic control.
Overall, the system operates efficiently by combining wide-area motion detection with accurate distance-based
confirmation, ensuring reliable performance, reduced false triggering, and enhanced energy savings in smart
environments such as classrooms, homes, and offices.
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Block Diagram:
Figure 1: Block Diagram
Hardware Components
Ultrasonic Sensor
The ultrasonic sensor (HC-SR04) is used for accurate human presence detection by measuring the distance
between the sensor and nearby objects. It operates by emitting high-frequency sound waves at approximately 40
kHz and calculating the time taken for the echo to return.
The distance is calculated using the time-of-flight principle based on the speed of sound (approximately 343 m/s).
The sensor has an effective detection range of 2 cm to 400 cm, with an optimal working range of 2–300 cm for
reliable operation.
A predefined threshold distance of 150 cm is set in the system. If the measured distance is less than this value,
the system considers the presence of a person. The sensor has a detection angle of approximately 15°, making it
suitable for focused and accurate measurement.
Specifications:
Operating Voltage: 5V
Operating Frequency: 40 kHz
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Measuring Range: 2 cm – 400 cm
Effective Range: up to 300 cm
Detection Angle: ~15°
Accuracy: ±3 mm
The ultrasonic sensor provides continuous real-time distance data to the ESP 32, enabling precise control of
electrical appliances.
PIR Sensor
The Passive Infrared (PIR) sensor is used for detecting motion over a wide area by sensing infrared radiation
emitted by the human body. It is highly sensitive to movement and is commonly used for occupancy detection.
The PIR sensor has a detection range of approximately 3 to 7 meters, with a wide detection angle of about 110°
to 120°, allowing it to cover a large area. When motion is detected, the sensor outputs a digital HIGH signal.
However, PIR sensors cannot detect stationary occupants effectively. Therefore, it is combined with an ultrasonic
sensor to improve system reliability.
Specifications:
Operating Voltage: 3.3V – 5V
Detection Range: 3 – 7 meters
Detection Angle: 110° – 120°
Output Type: Digital (HIGH/LOW)
Delay Time: Adjustable (typically 5 sec – 300 sec)
ESP 32 Microcontroller
The ESP 32 microcontroller serves as the central processing unit of the system. It processes data from both sensors
and executes control logic for automation.
The ESP 32 features a dual-core processor with integrated Wi-Fi and Bluetooth capabilities, making it suitable
for IoT applications. It operates at 3.3V logic level and supports multiple GPIO pins for interfacing sensors and
actuators.
Specifications:
Operating Voltage: 3.3V
Clock Frequency: up to 240 MHz
Wi-Fi: 802.11 b/g/n (2.4 GHz)
Bluetooth: v4.2 (BLE)
GPIO Pins: ~30
Flash Memory: 4MB (typical)
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Relay Module
The relay module is used to control high-voltage electrical appliances using low-voltage signals from the ESP 32.
It acts as an electrically operated switch.
The relay provides isolation between the control circuit and the load circuit, ensuring safe operation.
Specifications:
Operating Voltage: 5V
Switching Voltage: up to 250V AC
Switching Current: up to 10A
Channel Type: Single/Multiple channel
Trigger Type: Low-level trigger
Electrical Appliances
The system controls electrical appliances such as lights, fans, and other loads. These devices operate on standard
AC supply and are controlled via the relay module.
The appliances are switched ON when human presence is detected and switched OFF when no presence is
detected within the delay time.
SOFTWARE METHODOLOGY
The software architecture of the proposed system is designed to enable real-time sensing, intelligent decision-
making, and remote control using IoT technology. The system integrates embedded programming, wireless
communication, web server interaction, and cloud-based control to ensure efficient and flexible operation.
Embedded System Programming
The ES P 32 microcontroller is programmed using the Arduino IDE, which provides a user-friendly environment
for writing, compiling, and uploading code. The software is developed using Embedded C/C++ and follows a
continuous loop execution model.
The program begins with initialization routines, where all GPIO pins, sensors, Wi-Fi credentials, and
communication protocols are configured. The PIR sensor is connected to a digital input pin, while the ultrasonic
sensor uses trigger and echo pins for distance measurement.
The ultrasonic distance is calculated using the time-of-flight equation:
Distance = (Speed of Sound × Time) / 2
The speed of sound is considered as 343 m/s. The division by 2 accounts for the forward and return travel of the
sound wave.
Sensor Data Acquisition and Processing
The system continuously reads input from both PIR and ultrasonic sensors.
The PIR sensor outputs a digital HIGH signal when motion is detected
The ultrasonic sensor provides distance measurements in centimetres
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A predefined threshold distance of 150 cm is used to determine human presence. The sensor data is filtered and
validated to reduce noise and false readings.
Decision-Making Algorithm
The ESP 32 executes a control algorithm based on sensor inputs:
If PIR = HIGH (motion detected)
or
If Ultrasonic Distance < 150 cm
The system confirms human presence
Once presence is confirmed, the ESP 32 sends a signal to activate the relay module, turning ON the connected
appliances.
If no presence is detected, a delay timer of 45 seconds is initiated. If the absence continues during this period,
the system turns OFF the appliances. This delay mechanism prevents frequent switching and improves system
stability.
Wi-Fi Communication Protocol
The ESP 32 uses its built-in Wi-Fi module to connect to a local wireless network. Communication is established
using TCP/IP protocols.
The system periodically sends data such as:
Sensor status
Appliance state
System condition
It also listens for incoming control commands from the web server or cloud platform.
Web Server Implementation using XAMPP
A local web server is developed using XAMPP, which includes Apache HTTP Server and MySQL database
support.
Apache Server handles HTTP requests between the ESP 32 and the web interface
MySQL Database stores appliance status and user commands
The ESP 32 communicates with the server using HTTP GET/POST requests. When a user interacts with the web
interface, the request is processed by the server and forwarded to the ESP 32.
Web Interface Design (HTML + Database Integration)
The user interface is designed using HTML, providing a simple and interactive dashboard. It includes:
ON/OFF control buttons
Appliance status indicators
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Real-time updates
User commands are stored in the MySQL database and fetched by the ESP 32. This ensures synchronized control
between user input and system response.
Blynk Cloud Integration
To enable remote access beyond the local network, the system integrates Blynk Cloud. The ESP 32 connects to
the Blynk server using authentication tokens and communicates over the internet.
The Blynk mobile application provides:
Real-time monitoring
Remote ON/OFF control
Graphical interface
This cloud-based approach allows users to control appliances from anywhere, enhancing system accessibility
and usability.
Software Execution Flow
The complete software operation follows a cyclic process:
1. Initialize system and connect to Wi-Fi
2. Read PIR and ultrasonic sensor data
3. Calculate distance and compare with threshold (150 cm)
4. Execute decision logic
5. Control relay module
6. Update status to web server and Blynk cloud
7. Receive user commands
8. Repeat continuously
Error Handling and Reliability
Basic error handling mechanisms are implemented to ensure stable operation:
Invalid sensor readings are ignored
Wi-Fi reconnection is attempted automatically
Delay logic prevents rapid switching
Data synchronization ensures consistent system state
Advantages of Software Design
Real-time automation and control
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Hybrid sensor data processing
Remote monitoring via IoT
Reduced energy consumption
High reliability and flexibility
Voice Control Integration
The proposed system utilizes a web-based interface developed using XAMPP as the primary platform
for monitoring and controlling electrical appliances. The interface is designed using HTML and MySQL,
allowing users to access the system through a web browser within a local network.
The ESP 32 microcontroller communicates with the web server using Wi-Fi and HTTP protocols. User
commands from the web interface are processed by the server and transmitted to the ESP 32, which
controls the relay module accordingly.
In addition to local control, the system integrates Blynk Cloud to enable remote monitoring and control
over the internet. The ESP 32 connects to the Blynk Cloud server, allowing users to access the system
from anywhere using a mobile application.
Furthermore, the system supports voice control functionality through the application interface. The user
can provide voice commands such as “Light ON” or “Fan OFF,” which are converted into digital signals
and transmitted to the ESP 32 via the respective platform. The ESP 32 processes these commands and
controls the appliances accordingly.
Thus, the system combines local web-based control using XAMPP with cloud-based remote access using
Blynk, ensuring flexibility, accessibility, and improved user interaction
Algorithm
Step 1: Start the system.
Step 2: Initialize the ESP 32 microcontroller.
Step 3: Initialize all hardware modules:
• PIR Sensor
• Ultrasonic Sensor
• Relay Module
Step 4: Initialize Wi-Fi connection for IoT communication.
Step 5: Connect to the web server (XAMPP) and Blynk Cloud platform.
Step 6: Continuously read sensor data:
• Read PIR sensor (motion detection)
• Measure distance using Ultrasonic Sensor
Step 7: Compare ultrasonic distance with threshold value (150 cm).
Step 8: Check presence condition:
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• If PIR = HIGH (motion detected)
or
• If Distance < 150 cm
→ Human presence is confirmed
Step 9: If presence is detected:
• Send signal to relay module
• Turn ON the electrical appliances
Step 10: If no presence is detected:
• Start delay timer (45 seconds)
Step 11: If no detection during delay time:
• Turn OFF the appliances
Step 12: Check for user input from web interface or mobile app:
• Manual ON/OFF command
• Voice command (through application)
Step 13: If command is received:
• Process the command
• Override automatic control if necessary
• Update relay status accordingly
Step 14: Update system status to web server and cloud platform.
Step 15: Repeat the loop continuously for real-time operation
RESULTS AND DISCUSSION
The proposed smart automation system was successfully implemented and tested in a real-time indoor
environment such as a classroom or laboratory. The performance of the system was evaluated based on sensor
accuracy, response time, automation efficiency, and energy saving capability.
Sensor Performance Analysis
The PIR sensor effectively detected motion within a wide coverage angle of approximately 110°–120°. It
provided quick response when a person entered the monitored area. However, it was observed that the PIR sensor
alone could not detect stationary occupants.
The ultrasonic sensor accurately measured distance within the range of 2 cm to 300 cm. By using a predefined
threshold value of 150 cm, the system successfully detected both moving and stationary individuals. The
combination of PIR and ultrasonic sensors improved detection accuracy and minimized false triggering.
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System Operation Results
Condition
System Response
Person enters room
Appliances turned ON
Person stationary
Appliances remain ON
No presence detected
Delay timer activated (45s)
After delay (no detection)
Appliances turned OFF
Table 1: System Operation
The system operated reliably under all test conditions, ensuring user comfort while minimizing energy wastage.
Energy Consumption Analysis
Table 2: Energy Consumption Analysis
Energy and Cost Saving
Parameter
Value
Energy Saved / Day
1.2 kWh
Cost per Unit
₹6
Daily Saving
₹7.2
Monthly Saving
₹216
Yearly Saving
₹2592
Table 3: Energy and Cost Saving
The results show that the system significantly reduces energy consumption and provides noticeable cost savings
over time.
IOT and Control Performance
The ESP 32 microcontroller successfully communicated with the XAMPP-based web server and Blynk Cloud
platform via Wi-Fi. The system enabled:
Real-time monitoring of appliance status
Manual control through web interface
Remote access using mobile application
Voice-based control through application
The response time of the system was fast and reliable, ensuring smooth operation without noticeable delay.
Load-Based Performance Observation
The energy saving achieved by the proposed system depends significantly on the connected load. It is observed
that as the load value increases, the total energy consumption also increases, thereby resulting in higher energy
savings when automation is applied.
Parameter
Without Automation
Power Consumption
300 W
Operating Time
8 hours/day
Energy
Consumption
2.4 kWh
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For example, in environments with multiple appliances such as classrooms or offices, the system achieves greater
savings compared to a single-device setup.
Higher the load value → Higher the energy consumption → Greater the energy saving
This makes the system highly suitable for large-scale and high-power applications.
DISCUSSION
The experimental results confirm that the proposed hybrid sensing system effectively reduces energy
consumption by automatically controlling appliances based on occupancy. The integration of PIR and ultrasonic
sensors enhances detection accuracy, while IoT-based control improves flexibility and user convenience.
The system achieved an estimated annual cost saving of approximately ₹2500, demonstrating its practical
effectiveness in real-world applications.
Figure 2: Mobile Screen Figure 3: Output Device
However, minor limitations include dependency on Wi-Fi connectivity and reduced ultrasonic accuracy in noisy
environments. These limitations can be addressed in future improvements.
CONCLUSION
The proposed system successfully integrates automatic human presence detection with remote manual control,
providing both energy efficiency and enhanced user convenience. The ultrasonic sensor-based detection proved
reliable under various environmental conditions, while the web interface enabled real-time monitoring and control
of connected appliances.
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By implementing automatic switching of lights and fans, the system achieved a significant reduction in energy
consumption—up to 25% in the test environment—demonstrating its effectiveness in practical energy
management. The IoT-based architecture is low-cost, modular, and scalable, allowing for easy integration into
smart classrooms, offices, homes, and industrial settings.
The stable operation, low latency, and safe handling of high-voltage loads highlight the system’s reliability and
suitability for real-world applications. Moreover, the design is adaptable, allowing future enhancements such as
multi-zone coverage, predictive occupancy control using AI algorithms, and integration with other smart building
management systems.
Overall, this system offers a practical, cost-effective, and sustainable solution for energy conservation while
maintaining user comfort and operational flexibility, contributing to smarter, greener, and more responsive
environments.
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