The project presents an AI and IoT-based hand gesture control system for home appliances, utilizing MEMS and flex sensors for gesture recognition and emergency alerts. It enables hands-free operation and remote control via the Blynk app, integrating multiple control modes for enhanced accessibility. Key components include sensors, an ESP32 microcontroller, and software platforms such as Arduino and Anaconda IDE.

1. TKR College of Engineering And Technology
Department of ECE
AI AND IOT- BASED HAND GESTURE HOME APPLIANCES CONTROL
SYSTEM
Under the Guidance of
G.Venkata subba rao
Asst.prof(ECE)
Project coordinators: By
1.DR.P.Venkatalavanya(Asst.Professor) 1.V.Vamshi goud 21K91A04R2
2.Mrs.CH.Divya (Asst.Professor) 2.M.Sainath 22K95A0419
3.Mrs.G.Mahesh (Asst.Professor) 3.M.Rajesh 22K95A0418
TKR college of engineering and technology. Dept. Of ECE

2. CONTENTS:
➢AIM
➢OBJECTIVE
➢INTRODUCTION
➢BLOCK DIAGRAM
TKR college of engineering and technology Dept.of ECE

3. TKR college of engineering and technology
Dept.of ECE
AIM:
➢This project is about recognize the hand gesture using image processing and to
control home appliances.
➢To recognise the hand orientation using memes sensor and emergency detection
using flex sensor and alert via buzzer and IOT.
➢To control the appliances using IOT based Blynk App for remote control
operations.

4. OBJECTIVE
➢Enable hands-free control of home appliances through AI-based hand
gesture recognition.
➢ Provide sensor-based control using MEMS and flex sensors for physical
interaction.
➢ Incorporate IoT to enable remote control and monitoring of appliances.
TKR college of engineering and technology Dept.of ECE

5. INTRODUCTION
➢This project presents an advanced home appliance control system integrating AI for
hand gesture recognition, MEMS and flex sensor technology, and IoT for enhanced
convenience and accessibility.
➢The system offers multiple modes of control, including gesture recognition, sensor-
based control, and remote IoT-based control using the Blynk platform.
➢The sensor and anancoda (IDE) platform we are using for control the applicances.
TKR college of engineering and technology Dept.of ECE

6. BLOCK DIAGRAM:
TKR college of engineering and technology Dept.of ECE
➢ The proposed system integrates
AI-based gesture control using
OpenCV and AI models, sensor-
based control via MEMS and flex
sensors, and IoT-based remote
control through the Blynk
platform.
➢ It allows for hands-free operation
of home appliances, remote
monitoring, and increased energy
efficiency.
purpose:

7. TKR college of engineering and technology
BLOCK DIAGRAM:
➢ This is block diagram used for
detecting hand motion in anaconda
IDE.

8. TKR college of engineering and technology
Dept. Of ECE
•
HARDWARE COMPONENTS:
➢ Led
➢ Power supply
➢ Memes and flex sensor
➢ Regulator
➢ ESP32(Microcontroller)
➢ Relay
➢ DC cooling fan
SOFTWARE COMPONENTS:
➢Arduino complier
➢Blynk APP
➢Python and C++
➢Anaconda IDE
Dept of ECE

9. TKR college of engineering and technology
Thank you