The turret can be controlled wirelessly through a web page using a smartphone or any internet-enabled device from anywhere in the world. An ESP32-CAM module captures and streams live video to the user, allowing real-time monitoring and accurate control of the turret. A laser light is also controlled wirelessly for targeting purposes. The SR04 ultrasonic sensor is used for obstacle detection, while the DHT11 sensor measures temperature and humidity values, which are displayed on an LCD and uploaded to the web page through IoT. The ESP32 module continuously communicates with the Arduino Nano to execute control commands. The entire system is programmed using Embedded C language. This project demonstrates the integration of IoT, robotics, wireless communication, and embedded systems for smart remote surveillance and control applications.

Objectives:

1. To design and develop an IoT-based wireless gun turret system for remote surveillance and control.
2. To control the turret movement in UP-DOWN and LEFT-RIGHT directions using servo motors.
3. To implement a firing mechanism using DC motors and servo motors for dart launching.
4. To provide wireless control of the turret through a web page using a smartphone or internet-enabled device.
5. To integrate the ESP32-CAM module for live video streaming and real-time monitoring.
6. To control laser light and turret operations remotely through Wi-Fi communication.
7. To detect nearby obstacles using the SR04 ultrasonic sensor for safety and monitoring purposes.
8. To measure and monitor environmental temperature and humidity using the DHT11 sensor.
9. To display sensor data on an LCD and upload the values to a web page through IoT technology.
10. To establish communication between the ESP32 module and Arduino Nano for efficient system control.
11. To program the complete system using Embedded C language for reliable operation.
12. To develop a compact, low-cost, and smart surveillance system using embedded and IoT technologies.

The major building blocks of this project are:

1. Li-Ion Battery power supply.
2. Arduino Nano.
3. ESP32 CAM.
4. Two LM2596 buck converter modules.
5. Three servo motors.
6. Two DC motors.
7. DHT11(temperature sensor).
8. SR04 Ultrasonic sensor.
9. LASER light.

Software’s used in the project:

1. ARDUINO IDE.
2. Embedded C language.
3. Express SCH for Circuit Design.

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The project integrates IoT technology through the Blynk application, enabling real-time parking status monitoring  on a smartphone using ESP8266 WI-FI module. The system helps reduce traffic congestion, saves parking time, and improves parking management efficiency. This smart and low-cost solution is suitable for shopping malls, offices, apartments, and public parking areas.

The features of the project are:

1. IR sensor-based vehicle detection.
2. IOT based vacant slot monitoring system.
3. Using blynk mobile application to know the vacant slots.

The major building blocks of this project are:

1. Adapter Power Supply
2. Arduino UNO.
3. Four IR sensors for detecting the parking slots.
4. Two IR sensors for detecting the vehicle at enter/exit.
5. SERVO for Gate.
6. LCD display.
7. ESP8266 WI-FI Module.

Software’s used:

1. Embedded C programming.
2. Arduino IDE for dumping code into Micro controller.
3. Express SCH for Circuit design.

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Features:

• Design of real time wheel chair can be operated with multiple methods.
• To control the wheel chair using joystick, mems and push buttons.
• Automatic obstacle detection and alerting system.

The major building blocks of this project are:

1. Battery power supply.
2. PIC Microcontroller.
3. Arduino Nano.
4. RF transmitter and receiver.
5. DC motors with driver.
6. Joystick.
7. Push buttons.
8. MEMS.
9. Wheel chair.
10. Crystal oscillator.
11. Reset button.
12. LED indicator.
13. CAP.

Software’s used:

1. PIC-C compiler for Embedded C programming.
2. PIC kit 2 programmer for dumping code into Micro controller.
3.  Express SCH for Circuit design.

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The system operates by continuously monitoring the temperature and humidity levels inside the drying chamber using the DHT11 sensor. The Arduino UNO processes this data and controls a relay module to activate or deactivate the heater based on predefined threshold values. A DC motor rotates aluminum foil, which serves as a heat distributor, ensuring uniform heat application to the paddy seeds. This rotating mechanism prevents overheating and promotes even drying. The system remains operational until the target humidity level is achieved, after which the heater is automatically turned off to prevent excessive drying.

The LCD display provides real-time monitoring of temperature and humidity, allowing users to track the drying process. This automated and energy-efficient approach significantly improves drying efficiency, reduces labor requirements, and ensures optimal moisture content for seed storage and germination.

Features:

• Automated humidity and temperature control using a DHT11 sensor.
• Rotating aluminum foil mechanism driven by a DC motor for uniform heat distribution.
• Relay-controlled heater that operates based on predefined drying conditions.
• Real-time monitoring via an LCD display.
• Energy-efficient and time-saving solution compared to traditional drying methods.

The major building blocks of this project are:

• Power supply.
• Arduino UNO.
• DHT11(Temperature and Humidity) sensor.
• LCD display.
• DC motor-driven aluminum foil mechanism.
• L293d motor driver.
• Relay along with Heater.

Software’s used:

• ARDUINO IDE.
• Embedded C language.
• Express SCH for circuit design.

Regulated power supply:

video:

As shown in the block diagram, the system consists of a regulated power supply, temperature sensor, ADXL345 MEMS sensor, relay module, servo motor-based steam control, OLED display, and a web-based control interface. The ESP32 controller receives temperature data from the temperature sensor and motion/inactivity data from the ADXL345 MEMS sensor. Based on these inputs, the controller intelligently manages the heating element and steam flow of the iron box.

The relay module is used to switch the iron box heating element ON and OFF safely according to the required temperature settings. The servo motor controls the steam release mechanism, allowing optimized steam control for efficient ironing. An OLED display is provided to show real-time parameters such as temperature, steam status, and timer information.

The system also supports steam and timer control through a web page, enabling users to remotely monitor and control the iron box using Wi-Fi connectivity provided by the ESP32 controller. The ADXL345 MEMS sensor detects inactivity or abnormal movement, and the system automatically turns OFF the iron after a certain idle period, thereby preventing overheating, reducing power consumption, and improving safety.

This project demonstrates the effective integration of IoT, sensor technology, automation, and wireless control in household appliances, providing a smart, energy-efficient, and user-friendly ironing solution.

Objectives of the project:

1. To design a smart iron box using an ESP32 controller.
2. To control temperature and steam automatically for efficient ironing.
3. To provide remote monitoring and control through a web page.
4. To improve safety using auto shut-off with ADXL345 MEMS sensor.
5. To reduce power consumption and enhance energy efficiency.

The major building blocks of the project are:

• Regulated power supply.
• ESP32 controller.
• MEMS ADXL345 sensor
• Relay
• OLED.
• Servo.
• Iron box.

Software’s used:

• Embedded C programming.
• Arduino IDE programmer for dumping code into Micro controller.
• Express SCH for Circuit design.
• IOT technology.

Regulated power Supply:

video:

The project makes use of sensors like air quality, Methane gas sensor, DHT11 to detect the quality of food based on smell and gases which releases from spoiled items. The main controlling device of the project is Arduino UNO controller and Raspeberry Pi 3 B+ processor to achieve this task.

This technology, when combined with IoT, is able to provide intimation to the user about quality of food. It’s just like a food inspection technology. More precisely, our system consists of MQ-3 Methane Gas sensor, MQ-135 air quality, DHT11, IR sensor which are interfaced to the Arduino provides the essential information needed for evaluating the quality of the food. In this IR sensor is used to detect the food presence in the chamber and based on the sensors data the Arduino analyzes the quality of food and this information is transmitted to Raspberry Pi3 B+ processor. The processor takes responsibility to display the monitored data received from Arduino UNO onto the LCD and uploads the food quality analysis into the thingspeak cloud.

To perform this intelligent task, using Arduino is loaded with a program written in embedded ‘C’ language. To perform this task, Raspberry Pi processor is programmed using embedded ‘Linux’.

The main objectives of the project are:

1. By using this project, we can identify the quality of food.
2. Sending intimation to the user using IOT.
3. Visible alerts using LCD display.

The main building blocks of the project are:

1. Power supply.
2. Raspberry Pi 3 B+ processor
3. ARDUINOP UNO.
4. MQ-3 Methane sensor.
5. MQ-135 Air quality sensor.
6. DHT11.
7. LCD display.
8. IR sensor.

Software’s used:

1. ARDUINO IDE compiler for Embedded C programming.
2. Express SCH for Circuit design.
3. Thingspeak technology.
4. Python Language.
5. Raspbian OS.

Regulated Power Supply:

Block Diagram:

video:

The system includes a DS18B20 Temperature Sensor for temperature measurement, a pH sensor to detect acidity or alkalinity of water, a turbidity sensor to measure water clarity, and a TDS sensor to determine the total dissolved solids present in the water. All sensor data are read and processed by the ESP32 microcontroller which has an inbuilt Wi-Fi.

Using the built-in Wi-Fi capability of ESP32, the measured parameters are uploaded to the cloud platform ThingSpeak for real-time monitoring and data storage. This IoT-based monitoring system helps in early detection of water contamination and enables remote monitoring through the cloud. The proposed system is low-cost, efficient, and suitable for applications such as drinking water monitoring, industrial water quality checking, and environmental water analysis.

The main objectives of the project are:

  To design and develop an IoT-based water quality monitoring system using the ESP32 for real-time data processing and communication.

  To measure important water quality parameters such as temperature, pH level, turbidity, and total dissolved solids (TDS) using sensors like the DS18B20 Temperature Sensor, pH sensor, turbidity sensor, and TDS sensor.

  To upload and store water quality data in the cloud using the IoT platform ThingSpeak for remote monitoring and analysis.

  To develop a low-cost, efficient, and continuous monitoring system that can be used in drinking water systems, industries, and environmental water monitoring applications.

The major building blocks of this project are:

• Adapter Power supply.
• ESP32.
• PH sensor.
• Temperature sensor.
• Turbidity
• TDS sensor.

Software’s used:

• Arduino IDE for compiling and dumping code into Microcontroller.
• Thingspeak Cloud.
• Express SCH for Circuit design.

video:

The system can be interconnected with the vehicle and alert the owner on his mobile phone. This tracking system is composed of a GPS receiver, ARDUINO Microcontroller and a GSM Modem. GPS Receiver gets the location information from satellites in the form of latitude and longitude. The Arduino Microcontroller processes this information and this processed information is sent to the user/owner using GSM modem. The system also controls the ignition of the vehicle. The status of the project will display on LCD.

The presented application is a low-cost solution for automobile position and status, very useful in case of car theft situations, for monitoring adolescent drivers by their parents as well as in car tracking system applications. The system also controls the ignition of the vehicle using DC motor. The proposed solution can be used in other types of application, where the information needed is requested rarely and at irregular period of time (when requested).

Objectives:

• To design a vehicle tracking system using GPS and GSM technology.
• To determine the real-time location of the vehicle using GPS satellites.
• To send vehicle location details to the owner through SMS alerts.
• To control vehicle ignition using a DC motor mechanism.
• To display vehicle status and tracking information on an LCD.
• To provide security against vehicle theft and unauthorized usage.
• To develop a low-cost and efficient automobile monitoring system.
• To enable remote monitoring and tracking of vehicles anytime.

The Major Building blocks of this project are:

1. Regulated power supply (RPS)
2. Arduino UNO.
3. GSM.
4. GPS
5. DC Motor
6. LCD display.

Software’s used:

• Arduino IDE compiler for Embedded C programming.

2. Express SCH for Circuit design.

Block Diagram:

video:

The Pi Camera continuously monitors the scene in front of the user. Upon pressing an input switch, it captures an image and classifies objects using trained machine learning models. These classifications, such as “chair” or “person,” are announced through voice output via earphones, allowing the user to understand their surroundings non-visually. The LIDAR sensor is employed to detect obstacles within a 50 cm range, prompting vibration and audible alerts to prevent collisions.

In emergencies, a dedicated panic switch can be activated to send an SMS alert with GPS coordinates to a registered phone number using the GSM module. This feature enhances personal safety by providing location-based assistance during critical situations. The system also includes a rechargeable battery pack managed by an LM2596 voltage regulator, ensuring stable 5V power distribution across all modules.

A supportive hotspot and mobile application (Network Analyzer) enable temporary video streaming and network diagnostics for setup and testing. Overall, the Smart Cane combines AI-based object recognition, real-time alerts, and communication technologies to deliver a comprehensive assistive solution tailored for the visually impaired, promoting confidence and autonomy in everyday navigation.

Objectives:

• Detect obstacles using LIDAR and alert the user through sound and vibration.
• Classify objects in front using a Pi Camera and announce them via voice output.
• Provide real-time audio feedback through earphones for object identification.
• Enable emergency alert functionality via a panic switch.
• Send SMS alerts with GPS location to a registered phone number during emergencies.
• Ensure portable operation with a rechargeable battery and regulated power supply.
• Utilize Raspberry Pi as the central controller for processing and coordination.
• Offer basic mobile interface for testing object classification outputs.

The major building blocks of the project are:

1. Power supply.
2. Raspberry Pi3 b+ processor.
3. Pi Camera.
4. SD card.

5. LIDAR Sensor.
6. GSM Module .
7. GPS Module.
8. EARPHONES.
9. Buzzer .
10. Two Push Buttons.
11. Rechargeable Battery.
12. LM2596 Voltage Regulator.

Software’s used:

1. Embedded Linux programming.
2. Express SCH for Circuit design.
3. Python-tesseract is an optical character recognition (OCR).

video:

The ESP32 serves as the core controller, leveraging its inbuilt Bluetooth functionality to wirelessly transmit gesture data to a paired device, such as a laptop or smartphone. This eliminates the need for traditional wired peripherals and enhances user freedom of movement. A wearable prototype is mounted on the right hand, enabling seamless interaction after Bluetooth pairing with a standard PIN. The system is powered by a rechargeable battery, with LED indicators showing the charge status.

This solution offers a versatile, portable, and user-friendly interface suitable for remote control, accessibility applications, and smart device interaction. Its simple pairing process, cross-platform compatibility, and real-time gesture response showcase the potential of ESP32-based wearables in modern human-computer interaction.

Objectives:

• Design a wireless mouse controlled by hand gestures.
• Use a gyroscope sensor to control cursor movement.
• Implement flex sensors for left and right click detection.
• Integrate ESP32 for processing and Bluetooth communication.

Components Used:

• Battery Power Supply.
• ESP32 controller.
• MEMS sensor.
• Flex sensors.
• Hand Glove.

Software’s Used:

1. Arduino IDE studio compiler for dumping program.
2. Express SCH for Circuit design.

video: