Smart radiator system for enhanced thermal management using IoT and hand gesture recognition

Hieu Minh Le; Uchenna Emeoha Ogenyi; Liucheng Guo

doi:10.1109/M2VIP62491.2024.10746202

Smart radiator system for enhanced thermal management using IoT and hand gesture recognition

Hieu Minh Le^*
, Uchenna Emeoha Ogenyi
, Liucheng Guo

^*Corresponding author for this work

Tangi0 Ltd

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper presents the design and implementation of an intelligent radiator system that leverages Internet of Things (IoT) technology and hand gesture recognition (HGR) to enhance thermal management and energy efficiency in residential environments. The system addresses the limitations of traditional heating systems by enabling users to control radiator temperature via a web interface and intuitive hand gestures. The system utilises a Raspberry Pi, an ESP32, and sensors (temperature, ultrasonic, and gyroscope sensors) to monitor the environment and enable precise control. The HGR functionality, powered by MediaPipe, allows for convenient, touchless adjustment of heating settings with an accuracy of 73.02%. The system’s performance is evaluated through a LEGO prototype, and potential refinements, such as dataset expansion and model optimisation, are discussed. The project demonstrates the potential of IoT technology to deliver innovative and practical solutions for energy management in smart homes. Future work envisions the integration of the system with a mobile robotic platform, enabling dynamic thermal data collection, enhanced human-robot interaction, and expanded home automation capabilities.

Original language	English
Title of host publication	2024 30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350391916
ISBN (Print)	9798350391923
DOIs	https://doi.org/10.1109/M2VIP62491.2024.10746202
Publication status	Published - 12 Nov 2024
Event	30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024 - Leeds, United Kingdom Duration: 3 Oct 2024 → 5 Oct 2024

Publication series

Name	IEEE M2VIP Proceedings
Publisher	IEEE
ISSN (Print)	2996-4156
ISSN (Electronic)	2996-4164

Conference

Conference	30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024
Country/Territory	United Kingdom
City	Leeds
Period	3/10/24 → 5/10/24

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Hand Gesture Recognition
Internet of Things (IoT)
Machine Learning
MediaPipe
Thermal Management

Access to Document

10.1109/M2VIP62491.2024.10746202

Cite this

@inproceedings{381dee12415f4f8fa1d6c2cc886cbf3d,

title = "Smart radiator system for enhanced thermal management using IoT and hand gesture recognition",

abstract = "This paper presents the design and implementation of an intelligent radiator system that leverages Internet of Things (IoT) technology and hand gesture recognition (HGR) to enhance thermal management and energy efficiency in residential environments. The system addresses the limitations of traditional heating systems by enabling users to control radiator temperature via a web interface and intuitive hand gestures. The system utilises a Raspberry Pi, an ESP32, and sensors (temperature, ultrasonic, and gyroscope sensors) to monitor the environment and enable precise control. The HGR functionality, powered by MediaPipe, allows for convenient, touchless adjustment of heating settings with an accuracy of 73.02\%. The system{\textquoteright}s performance is evaluated through a LEGO prototype, and potential refinements, such as dataset expansion and model optimisation, are discussed. The project demonstrates the potential of IoT technology to deliver innovative and practical solutions for energy management in smart homes. Future work envisions the integration of the system with a mobile robotic platform, enabling dynamic thermal data collection, enhanced human-robot interaction, and expanded home automation capabilities.",

keywords = "Hand Gesture Recognition, Internet of Things (IoT), Machine Learning, MediaPipe, Thermal Management",

author = "Le, \{Hieu Minh\} and Ogenyi, \{Uchenna Emeoha\} and Liucheng Guo",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024 ; Conference date: 03-10-2024 Through 05-10-2024",

year = "2024",

month = nov,

day = "12",

doi = "10.1109/M2VIP62491.2024.10746202",

language = "English",

isbn = "9798350391923",

series = "IEEE M2VIP Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2024 30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024",

address = "United States",

}

Le, HM, Ogenyi, UE & Guo, L 2024, Smart radiator system for enhanced thermal management using IoT and hand gesture recognition. in 2024 30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024. IEEE M2VIP Proceedings, Institute of Electrical and Electronics Engineers Inc., 30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024, Leeds, United Kingdom, 3/10/24. https://doi.org/10.1109/M2VIP62491.2024.10746202

Smart radiator system for enhanced thermal management using IoT and hand gesture recognition. / Le, Hieu Minh; Ogenyi, Uchenna Emeoha; Guo, Liucheng.
2024 30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024. Institute of Electrical and Electronics Engineers Inc., 2024. (IEEE M2VIP Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Smart radiator system for enhanced thermal management using IoT and hand gesture recognition

AU - Le, Hieu Minh

AU - Ogenyi, Uchenna Emeoha

AU - Guo, Liucheng

PY - 2024/11/12

Y1 - 2024/11/12

N2 - This paper presents the design and implementation of an intelligent radiator system that leverages Internet of Things (IoT) technology and hand gesture recognition (HGR) to enhance thermal management and energy efficiency in residential environments. The system addresses the limitations of traditional heating systems by enabling users to control radiator temperature via a web interface and intuitive hand gestures. The system utilises a Raspberry Pi, an ESP32, and sensors (temperature, ultrasonic, and gyroscope sensors) to monitor the environment and enable precise control. The HGR functionality, powered by MediaPipe, allows for convenient, touchless adjustment of heating settings with an accuracy of 73.02%. The system’s performance is evaluated through a LEGO prototype, and potential refinements, such as dataset expansion and model optimisation, are discussed. The project demonstrates the potential of IoT technology to deliver innovative and practical solutions for energy management in smart homes. Future work envisions the integration of the system with a mobile robotic platform, enabling dynamic thermal data collection, enhanced human-robot interaction, and expanded home automation capabilities.

AB - This paper presents the design and implementation of an intelligent radiator system that leverages Internet of Things (IoT) technology and hand gesture recognition (HGR) to enhance thermal management and energy efficiency in residential environments. The system addresses the limitations of traditional heating systems by enabling users to control radiator temperature via a web interface and intuitive hand gestures. The system utilises a Raspberry Pi, an ESP32, and sensors (temperature, ultrasonic, and gyroscope sensors) to monitor the environment and enable precise control. The HGR functionality, powered by MediaPipe, allows for convenient, touchless adjustment of heating settings with an accuracy of 73.02%. The system’s performance is evaluated through a LEGO prototype, and potential refinements, such as dataset expansion and model optimisation, are discussed. The project demonstrates the potential of IoT technology to deliver innovative and practical solutions for energy management in smart homes. Future work envisions the integration of the system with a mobile robotic platform, enabling dynamic thermal data collection, enhanced human-robot interaction, and expanded home automation capabilities.

KW - Hand Gesture Recognition

KW - Internet of Things (IoT)

KW - Machine Learning

KW - MediaPipe

KW - Thermal Management

UR - https://www.scopus.com/pages/publications/85214352424

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DO - 10.1109/M2VIP62491.2024.10746202

M3 - Conference contribution

AN - SCOPUS:85214352424

SN - 9798350391923

T3 - IEEE M2VIP Proceedings

BT - 2024 30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

Y2 - 3 October 2024 through 5 October 2024

ER -

Smart radiator system for enhanced thermal management using IoT and hand gesture recognition

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this