A Comprehensive Survey on IoT-Enabled and Hand Gesture Controlled Robotic Arm Using Blynk IoT and OpenCV

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Notice

nThis is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.n

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Year : 2025 [if 2224 equals=””]29/09/2025 at 10:39 AM[/if 2224] | [if 1553 equals=””] Volume : 12 [else] Volume : 12[/if 1553] | [if 424 equals=”Regular Issue”]Issue : [/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 03 | Page : 35 40

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    Yogesh Bhangale, Ruchira Pagar, Bhaven Bankar,

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  1. Student, Student, Student, Electronics and Telecommunication, Sinhgad College of Engineering Vadgaon (BK), Pune, Electronics and Telecommunication, Sinhgad College of Engineering Vadgaon (BK), Pune, Electronics and Telecommunication, Sinhgad College of Engineering Vadgaon (BK), Pune, Maharashtra, Maharashtra, Maharashtra, India, India, India

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Abstract

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nThis venture presents an IoT-enabled and hand gesture-managed robot arm that operates in three distinct modes: automated control, IoT-based control via the Blynk app, and gesture-based control using OpenCV. The gadget integrates a NodeMCU microcontroller for wireless verbal exchange and management, with MQTT protocol enabling real-time messaging among the devices. In automated mode, the robotic arm plays predefined tasks autonomously. In IoT mode, users can remotely manage the arm using the Blynk IoT platform, allowing for real-time manipulation over the net. In gesture mode, the pc’s camera captures hand gestures, which can be processed by OpenCV to come across precise motions, such as swiping or the hand, and sends control instructions to the robotic arm through the MQTT protocol. The venture combines pc vision, wireless communication, and robotics, making it distinctly versatile for applications in automation, assistive generation, and clever environments. It demonstrates the sensible integration of IoT with robotics, allowing far off control, gesture-based interaction, and autonomous operation in a cost-effective and scalable solution. The capabilities and adaptability of IoT-enabled robotic arms can be greatly increased by using machine learning (ML). These systems can learn from data, adjust to changing conditions, and make wiser judgments by integrating machine learning algorithms. For instance, ML can be applied to enhance gesture detection, allowing for more precise and user-friendly robotic arm control. The arm can carry out activities more effectively and efficiently if ML is employed to optimize task preparation and execution. Additionally, ML can be used to create predictive maintenance models, which can assist minimize downtime and detect possible problems before they arise.nn

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Keywords: IoT enabled robotic arm, gesture recognition, automation, controlled robotic, machine learning

n[if 424 equals=”Regular Issue”][This article belongs to Journal of Advancements in Robotics ]

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[/if 424][if 424 equals=”Special Issue”][This article belongs to Special Issue under section in Journal of Advancements in Robotics (joarb)][/if 424][if 424 equals=”Conference”]This article belongs to Conference [/if 424]

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How to cite this article:
nYogesh Bhangale, Ruchira Pagar, Bhaven Bankar. [if 2584 equals=”][226 wpautop=0 striphtml=1][else]A Comprehensive Survey on IoT-Enabled and Hand Gesture Controlled Robotic Arm Using Blynk IoT and OpenCV[/if 2584]. Journal of Advancements in Robotics. 19/09/2025; 12(03):35-40.

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How to cite this URL:
nYogesh Bhangale, Ruchira Pagar, Bhaven Bankar. [if 2584 equals=”][226 striphtml=1][else]A Comprehensive Survey on IoT-Enabled and Hand Gesture Controlled Robotic Arm Using Blynk IoT and OpenCV[/if 2584]. Journal of Advancements in Robotics. 19/09/2025; 12(03):35-40. Available from: https://journals.stmjournals.com/joarb/article=19/09/2025/view=0

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  1. Paterson J, Aldabbagh A. Gesture-controlled robotic arm utilizing OpenCV. In 2021 IEEE 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA). 2021 Jun 11; 1–6.
  2. Patel N, He SJ. A survey on hand gesture recognition techniques, methods and tools. Int J Res Advent Technol. 2018 Jun; 6(6): 939–957.
  3. Polvara R, Sharma S, Wan J, Manning A, Sutton R. Vision-based autonomous landing of a quadrotor on the perturbed deck of an unmanned surface vehicle. Drones. 2018 Apr 14; 2(2): 15.
  4. Bokade AU, Ratnaparkhe VR. Video surveillance robot control using smartphone and Raspberry pi. In 2016 IEEE International conference on communication and signal processing (ICCSP). 2016 Apr 6; 2094–2097.
  5. Saha S, Singh A, Bera P, Kamal MN, Dutta S, Gorian U, Pramanik S, Khan A, Sur S. GPS based smart spy surveillance robotic system using Raspberry Pi for security application and remote sensing. In 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). 2017 Oct 3; 705–709.
  6. Jayakumar AJ, Muthulakshmi S. Raspberry Pi-based surveillance system with IoT. In Intelligent Embedded Systems: Select Proceedings of ICNETS2, Vol. II. Singapore: Springer Singapore; 2018 Feb 17; 173–185.
  7. Dziri A, Duranton M, Chapuis R. Real-time multiple objects tracking on Raspberry-Pi-based smart embedded camera. J Electron Imaging. 2016 Jul 1; 25(4): 041005.
  8. Agarwal D, Rastogi A, Rustagi P, Nijhawan V. Real time RF based gesture controlled robotic vehicle. In 2021 IEEE 8th International Conference on Computing for Sustainable Global Development (INDIACom). 2021 Mar 17; 848–852.
  9. Pradipa R, Kavitha S. Hand gesture recognition–analysis of various techniques, methods and their algorithms. Int J Innov Res Sci Eng Technol. 2014 Mar; 3(3): 2003–10.
  10. Singh D, Zaware P, Nandgaonkar A. Wi-Fi surveillance bot with real time audio & video streaming through Android mobile. In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). 2017 May 19; 746–750.

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[if 424 not_equal=””]Regular Issue[else]Published[/if 424] Subscription Review Article

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Journal of Advancements in Robotics

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[if 344 not_equal=””]ISSN: 2455-1872[/if 344]

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Volume 12
[if 424 equals=”Regular Issue”]Issue[/if 424][if 424 equals=”Special Issue”]Special Issue[/if 424] [if 424 equals=”Conference”][/if 424] 03
Received 05/05/2025
Accepted 04/08/2025
Published 19/09/2025
Retracted
Publication Time 137 Days

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