Design and Implementation of a Remotely Operated Vehicle for Real-Time Monitoring Application

Abstract

Efficient surveillance of large-scale commercial warehouses and private properties guarantees asset security, operational lapse, and real-time situational awareness. Conventional surveillance systems often lack mobility and flexibility, which reduces their effectiveness in dynamic environments. This paper discusses the design and implementation of a flexible, low-cost, and energy-efficient Remotely Operated Vehicle (ROV) developed and designed for real-time remote surveillance of spacious commercial premises. The main goal of this project is to facilitate remote monitoring with real-time video streaming, providing an affordable option compared to fixed camera setups and costly autonomous patrol robots. The suggested system uses an STM32F4xx series microcontroller for real-time management, a 2.4 GHz NRF24L01 transceiver for wireless connectivity, and a Python-driven video streaming module combined with an HTML-based control interface reachable over the local network. The power system incorporates a 76?Wh LiFePO? battery, with stable voltage regulation achieved using LM2596 and AMS1117 modules for different subsystems. The software architecture combines Arduino C, Python, and HTML, allowing effective control, live feed management, and user-friendly access. The system’s novelty lies in its hybrid multi-platform design, wireless range, and energy efficiency, tailored for indoor and semi-outdoor commercial environments. Experimental results show that the ROV achieves a stable control range of over 50 meters and continuous operation exceeding 1.5 hours on a single charge. Video streaming performance remains consistent with minimal possible latency, even in warehouse environments with moderate interference. While currently designed for commercial and industrial use, the system’s modularity allows future integration of features such as autonomous navigation, object detection, and deployment in hazardous and defence-sensitive environments. In conclusion, the proposed ROV offers a scalable and practical solution for commercial surveillance, contributing towards intelligent, mobile, and energy-efficient monitoring systems.

Introduction

Due to the increasing incidents of theft and unauthorized access in large properties like bungalows, offices, and warehouses, modern surveillance systems are essential. Traditional fixed cameras have limited coverage, especially in large or complex areas, creating security vulnerabilities. This paper proposes a Remotely Operated Vehicle (ROV) designed for real-time surveillance in extensive, unmanned locations. The ROV, equipped with cameras and sensors, offers a flexible, cost-effective alternative to fixed cameras and expensive autonomous robots. It can be remotely controlled or semi-autonomous, streaming live video over a local network, allowing remote asset monitoring.

The system uses an STM32 microcontroller for control, an NRF24L01 wireless module for communication, and a Python-based browser-accessible video interface. Powered by a LiFePO4 battery with regulated voltage supplies, it features a telemetry display providing live feedback such as battery and positioning data. The paper details the design, development, and evaluation of the ROV and discusses future enhancements like autonomous navigation, aiming to extend its use to hazardous or disaster-prone environments.

The ROV integrates robotics, wireless communication, and embedded systems, enabling efficient remote surveillance applicable across security, industrial inspection, military, and search-and-rescue operations. Key components include motor drivers, servo and DC motors for movement, a camera for live feed, Raspberry Pi as the processing unit, TOF sensors for obstacle detection, and a joystick for manual control.

The Raspberry Pi was chosen for its powerful processing capabilities, networking features, and ease of integration, running a full Linux OS and supporting various programming environments. The control module utilizes microcontrollers to manage motors via PWM signals for precise movement control.

Conclusion

Existing surveillance systems—ranging from traditional fixed CCTV setups to advanced autonomous patrol robots—exhibit notable limitations in terms of mobility, cost, adaptability, and energy efficiency. Fixed CCTV systems, although reliable for static monitoring, fail to provide flexible coverage in dynamic or spacious environments and are not cost-effective in all use cases. On the other hand, mobile surveillance robots offer flexibility but are often burdened by high costs, complex SLAM-based navigation, and increased power consumption.

References

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Copyright

Copyright © 2025 Prof. Mahesh A. Kamthe, Ayush S. Patil, Tanish D. Kansara, Komal R. Molekar, Sanskar S. Patil. 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.