Surveillance Robotic Vehicle

Authors: Ms.Shruti Sanjay Patil, Ms. Rutuja Balaso Chavan, Ms. Komal Mahadev Kumbhar, Mr. Anup Bhaskar Kamble, Prof. L. S. More

DOI Link: https://doi.org/10.22214/ijraset.2026.83222

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Abstract

This paper introduces an advanced robotic surveillance system that enhances monitoring across sensitive, restricted public areas.The robot is integrated with a wireless camera capable of capturing live video during both daytime and nighttime conditions. It can be remotely operated through a mobile application using an ESP Wi-Fi module, ensuring smooth communication between the robot and an Android device. The system utilizes the Blynk application to control the robot’s movements based on commands sent from the Android phone. By minimizing direct human involvement, this approach ensures continuous observation and security in dangerous environments.The main objective of the project is to develop a smart spy robotic vehicle capable of providing continuous surveillance in challenging locations while transmitting live video feeds in real time. Additionally, the robot is designed to recognize and monitor different human activities through live video streaming. The Android application enables users to control the robot remotely over a significant distance using Wi-Fi connectivity, offering flexibility and ease of operation. The project also has strong potential for future development in sectors such as defines , military surveillance, and mining industries. With further improvements, the robotic system could play an important role in enhancing security operations, monitoring hazardous areas, and reducing risks to human personnel.

Introduction

This study presents a Wi-Fi-enabled robotic surveillance system that integrates an ESP8266 module, camera, Raspberry Pi, and Android application for remote monitoring and real-time human activity recognition. The system aims to monitor environments where direct human supervision is difficult by identifying activities such as walking, talking, and falling through computer vision and machine learning, eliminating the need for wearable sensors. The ESP8266 provides wireless communication, the Blynk app enables remote control, and the Raspberry Pi processes video data for activity recognition. A literature review highlights related work in IoT surveillance robots and human activity recognition. Experimental results demonstrate successful integration of hardware and software, with accurate real-time activity detection and reliable robotic operation. Performance evaluation shows high communication reliability (98.5–99.9%) and activity recognition accuracy ranging from 75–92%, with Random Forest outperforming Decision Tree and K-Nearest Neighbors classifiers. Future enhancements include autonomous navigation, edge AI processing using platforms such as NVIDIA Jetson, and onboard machine learning to improve response time, reduce latency, and enable large-scale intelligent surveillance applications.

Conclusion

The surveillance robot is developed to provide an efficient and user-friendly monitoring solution with simple operation and reliable performance. The system is capable of supporting surveillance functions such as visual monitoring and motion detection, ensuring effective observation of different environments. The robot is designed with flexibility in mind, allowing it to adapt easily to locations such as warehouses, underground areas, and multi-story buildings. Its modular structure and scalable architecture make the system highly customizable according to specific user requirements and operational conditions. In addition, the expandable design allows future integration of advanced control features and technological upgrades. This improves system accessibility, enhances overall functionality, and offers a more efficient alternative to conventional surveillance methods.

References

[1] Abdulmalek Akilan, T., Satyam Chaudhary, Princi Kumari, and Utkarsh Pandey. \"Surveillance robot in hazardous place using IoT technology,IEEE, 2020. [2] Patoliya, Jignesh, Haard Mehta, and Hitesh Patel. \"Arduino controlled war field spy robot using night vision wireless camera and Android application.\" In 2015 5th Nirma University International Conference on Engineering (Nui CONE), pp. 1-5. IEEE, 2015. [3] Shah, Mohammad Shoeb, and P. B. Borole. \"Surveillance and rescue robot using Android smartphone and the Internet.\" In 2016 International Conference on Communication and Signal Processing (ICCSP), pp. 1526-1530. IEEE, 2016. [4] R. Bhardwaj, S. Kumar, and S. C. Gupta, “Human activity recognition in real world,” in 2017 2nd International Conference on Telecommunication and Networks (TEL-NET).

Copyright

Copyright © 2026 Ms.Shruti Sanjay Patil, Ms. Rutuja Balaso Chavan, Ms. Komal Mahadev Kumbhar, Mr. Anup Bhaskar Kamble, Prof. L. S. More. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Paper Id : IJRASET83222

Publish Date : 2026-05-27

ISSN : 2321-9653

Publisher Name : IJRASET

DOI Link : Click Here