The system is built around a Raspberry Pi 4, which acts as the central processing unit. Voice commands are captured through a microphone module and processed locally using TinyML-based deep learning models, allowing efficient and low-latency voice recognition without continuous cloud dependency. Advanced noise filtering techniques are implemented to ensure high accuracy even in noisy environments. Recognized commands are matched with predefined keywords such as “Open Door” and “Close Door”.

Upon successful recognition, the Raspberry Pi drives a servo motor to perform precise door movement operations. The current system status, including command recognition and door position, is displayed on an LCD display for real-time user feedback. An SD card is used for data storage, including trained models and system logs. The entire system operates on a 5V DC power supply, making it suitable for embedded and IoT applications.

This project demonstrates an efficient, low-power, and cost-effective voice-controlled smart door system using TinyML and deep learning, with potential applications in smart homes, assistive technology, and secure access control systems.

The main objectives of this project are:

• To design and develop a voice recognition–based door control system using TinyML and deep learning techniques.
• To implement offline voice command recognition on an IoT device for improved privacy and low latency.
• To efficiently filter background noise and improve voice recognition accuracy using TinyML models.
• To control a servo motor for door opening and closing based on recognized voice commands.
• To display the system status and door operation (Open/Close) on an LCD display.
• To utilize Raspberry Pi 4 as the main controller for processing voice commands and device control.
• To create a low-power, cost-effective, and user-friendly smart door automation system.
• To demonstrate the applicability of TinyML in real-time IoT applications such as smart homes and access control systems.

The major building blocks of this project are:

1. Adapter power supply.
2. Raspberry pi 4.
3. SD card.
4. LCD display.
5. Micro phone.
6. Servo Motor.

Software’s used:

• Raspbian OS.
• TinyML and deep learning techniques.

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Achieving balance between power consumption and power production is a bigger challenge today. The best way to solve this imbalanced equation is to use solar energy as efficiently as possible. The problem in the usage of solar energy is with solar cell panel should be exposed maximum to the sun light. If the solar panel is fixed in a particular direction then the sun light intensity varies from morning to evening. Moving the solar cell panel in the direction of sun can increase the solar energy generated from the solar cell.

This project consists of few sun light sensors and a motorized mechanism for rotating the panel in the direction of sun. Arduino based control system takes care of sensing sunlight and controlling the motorized mechanism. This system works continuously without any interruption.

The main controlling device of the project is Aduino uno microcontroller which LDR’s and servo motor with panel setup is interfaced. The Microcontroller gets input from LDR sensors regarding the direction of sun and controller process this information and controls the movement of solar panel attached to servo motor. This solar energy is stored into the battery. This system runs with battery power. The Microcontroller is programmed using powerful Embedded C language.

The main object of this project:

• Design a single axis solar tracker.
• Conservation of Non Renewable energy sources.
• Maximum output can be obtained.
• Using of arduino to archive this task.

The major building blocks of this project are:

1. Power supply.
2. Arduino UNO
3. Sun light Sensor to sense the sun direction.
4. Motorized mechanism to control the position of solar panel.
5. Servo motor.

Software’s used:

1. ARDUINO IDE STUDIO compiler for Embedded C programming.
2. Express SCH for Circuit design.

Regulated power supply:

Block Diagram:

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The project aims in designing a train accident avoiding system using Arduino. The proposed system is an enhanced technique for monitoring the object which uses Arduino microcontroller, ultrasonic sensor, and radar module. The radar will get the distance from the object and ultrasonic sensor will ensure to avoid the accidents that may occur by the clash between the train and objects.

The controlling device of the whole system is a Microcontroller. Ultrasonic sensor, servo motor long with barrier gates are interfaced to the Microcontroller. When the ultrasonic sensor detects the train, microcontroller will close the barrier gates to let the person in. To achieving the task, the controller is loaded with a program written using Embedded ‘C’ language.

The main objectives of the project are:

1. Automatic train arrival/despatcher detection using ultrasonic sensor.
2. Automatic barrier gates open/close.

The major building blocks of the project are:

1. Regulated Power Supply.
2. PIC Microcontroller.
3. Ultrasonic sensor.
4. Servo motor through barrier gates.
5. Crystal oscillator.
6. Reset.
7. LED indicators.

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.

Regulated Power Supply:

Block diagram:

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Smart Receptionist with smart lock system is mainly designed and developed for security system. This smart security system is used to see a visitor when the main door of the office or Home is closed. Wi-Fi (Short for Wireless Fidelity) is a wireless technology that uses radio frequency to transmit data through the air. Wi-Fi has initial speeds of 1mbps to 2mbps. Wi-Fi transmits data in the frequency band of 2.4 GHz. It implements the concept of frequency division multiplexing technology. Range of Wi-Fi technology is 40-300 feet.

The controlling device of the whole system is a raspberry pi processor; it has an inbuilt Ethernet. LCD display, Pi-camera, servo Motor is interfaced to the raspberry pi processor. In this system whenever a person presses the calling bell, image of the person is captured by the Pi-camera and it will send the raspberry pi then the processor mails the person image to owner. Once the image is uploaded user need to check the image and take decision accordingly like access/denies through mail. If the person denies the permission to open the door, door will remain locked and the system will give buzzer alert. The status of the project is displayed on LCD display. Raspberry Pi is the controlling section in our project. We program it using Python Language and the OS used here is Linux.

Objectives of the project:

• Buzzer alert for unknown persons.
• Door access/denies from MAIL.
• Using Pi camera to capture the image.
• Servo motor-based door lock/unlock.
• Using raspberry pi ZERO W to achieve this task.

The major building blocks of the project are:

• Power Supply. u Raspberry pi ZERO W.
• SD card. u Pi camera. u Buzzer.
• LCD display.
• Servo motor.

Software’s used:

• Raspbian OS.
• Python programming language.
• Express SCH for Circuit design.
• IOT technology.

Block diagram:

video: