Remote validation of embedded boards

INTRODUCTION:
In today’s era of distributed development, the ability to test and validate embedded systems remotely is becoming as crucial as secure firmware design itself. Traditional validation workflows depend on direct physical access to development boards, leading to inefficiencies, limited scalability, and increased turnaround time. As embedded systems grow more complex and teams operate across different locations, there is a strong demand for an automated, flexible, and location-independent validation framework.
Our project introduces Remote Validation it is a cloud-connected testing platform that enables engineers to program, monitor, and validate embedded boards such as ESP 32 from anywhere in the world. Using a Raspberry Pi as the control hub, the system automates essential operations like firmware flashing, serial communication, and power cycling. This setup eliminates the need for manual intervention, allowing continuous integration, automated regression testing, and round-the-clock validation of firmware.
Beyond its industrial advantages, Remote Validation also transforms education and research. It empowers students to perform real hardware experiments through online labs, enables startups to test IoT prototypes remotely, and allows organisations to manage multiple test nodes through a centralized cloud dashboard.
In essence, Remote Validation bridges the gap between physical embedded hardware and digital accessibility — creating a scalable, affordable, and fully automated ecosystem for next-generation embedded development and testing.

LITERATURE SURVEY ON EXISTING METHODS:
Over the past decade, researchers have increasingly focused on remote access, automation, and validation of embedded systems — driven by the need for efficient testing, scalable experimentation, and distributed collaboration. As embedded devices and IoT systems become more interconnected, traditional validation methods that rely on direct physical access are proving inadequate for modern development environments.
Salazar et al. [1] implemented a low-cost remote monitoring and control system using Raspberry Pi, demonstrating that web-based interfaces can effectively manage GPIO peripherals and log environmental data. While their approach was simple and affordable, it offered limited scalability and control features.
Zhang et al. [2] developed a GSM/GPRS-based environmental monitoring system capable of collecting and transmitting real-time data remotely. Their work proved the feasibility of long-range data communication, though it lacked detailed security mechanisms — a crucial consideration for modern connected devices.
Jacko et al. [3] introduced a remote IoT education laboratory based on STM 32 microcontrollers, enabling students to perform programming and debugging tasks remotely. This study showcased the educational value of online embedded experiments but was limited to specific hardware and heavily dependent on stable internet connectivity.
Angulo et al. [4] proposed a cloud-based control system for remote experimentation with embedded technologies. Their platform enhanced engineering education by allowing real-time interaction with hardware through web-based tools, though it required hardware-specific configurations that reduced general applicability.
Finally, Watanabe et al. [5] presented IoT-REX, a secure remote-control system leveraging Multi-Designated Verifier Signatures to ensure that only authenticated commands are executed by IoT devices. While this approach greatly improved remote control security, it introduced added complexity and required specialized secure modules.
Together, these studies highlight a clear research and systems have explored remote control and monitoring, most solutions either focus on specific applications or depend heavily on hardware customisation. There remains a need for a scalable, secure, and hardware-agnostic remote validation framework that can automate firmware flashing, monitoring, and testing in a distributed environment.
This motivates the development of Remote Validation — a lightweight, cloud-enabled platform that enables engineers, educators, and researchers to perform real-time hardware testing and debugging from anywhere, using accessible tools like Raspberry Pi and open-source automation frameworks.

1. Identifying the Problem In embedded system development, hardware validation is an essential process to ensure proper functionality of firmware and physical components. Traditionally, this validation requires direct physical access to the development board for tasks such as firmware flashing, serial log monitoring, and GPIO testing. As projects become more complex and teams increasingly work remotely, this manual process has become time-consuming, inflexible, and prone to human error. Existing tools provide limited remote monitoring capabilities but lack a unified solution that integrates programming, power control, debugging, and real-time validation. This creates a significant barrier to efficient testing and automation, highlighting the need for a scalable and accessible remote validation platform for embedded systems.
2. Designing the System: Remote Validation Platform To overcome the limitations of manual embedded testing, the proposed approach — Remote Validation — introduces automation and remote accessibility into the hardware validation process. The system enables developers to program, test, and monitor embedded boards from any location without physical interaction. Core Design Features: Automated Firmware Programming: The platform automates flashing operations through ST-Link or USB interfaces, eliminating the need for manual intervention. Remote Power Control: Relay modules are integrated to enable software-controlled power cycling and reset operations. GPIO and Serial Monitoring: Real-time GPIO toggling and UART log streaming provide continuous visibility into system behavior. Web-Based Dashboard: A user-friendly interface allows firmware uploads, test execution, and live data visualization through any web browser. By integrating these features, the Remote Validation system acts as a unified control and testing environment, improving efficiency, repeatability, and accessibility in embedded development
3. Implementation Details The Remote Validation System was implemented using a combination of hardware and software components designed for automation and accessibility. A Raspberry Pi serves as the central controller, managing tasks such as firmware flashing, serial communication, power cycling, and GPIO control. The system integrates a web-based interface, developed using Node-RED , allowing users to remotely upload firmware, monitor real-time logs, and control hardware peripherals from any location. Communication between the Raspberry Pi and the embedded development boards (e.g., STM32, ESP32) is established through USB and serial connections. All data and test results are stored with a cloud database

This implementation eliminates the need for constant physical interaction with development boards, making the system cost-effective, flexible, and scalable for education, and IoT development environments.

1. Integration with Cloud and Automation Framework The Remote Validation system is designed for seamless integration into cloud-based and automated development workflows. System Architecture: Raspberry Pi (Control Layer): Acts as the central node managing communication between users and the connected devices. Embedded Board (Validation Layer): Executes firmware uploaded by users and sends operational data back to the controller. Cloud Dashboard: Provides remote access for multiple users to control and monitor boards simultaneously through secure authentication. Advantages: Supports multi-user and multi-board scalability through centralized management. Facilitates real-time log analysis and automated error detection the system bridges the gap between physical embedded validation and online automation—making global remote testing practical and efficient.

Results and Analysis

The results confirm that remote testing can match traditional in-lab validation in precision while offering significant improvements in efficiency and scalability.
System Performance Evaluation
The system was deployed using a Raspberry Pi 4 as the controller .
Key operations — such as firmware flashing, serial communication, and GPIO control were executed and timed under both manual and remote (automated) conditions.

Future Research :
Looking ahead, our next step is to enhance the Remote Validation platform with intelligent automation and improved scalability for large-scale embedded testing. One major direction is the integration of AI where machine learning analyse UART logs, sensor outputs, and execution data to automatically identify anomalies or malfunction patterns. This would enable predictive diagnostics, reducing manual intervention and improving testing efficiency.
Another important focus is cloud-based expansion and multi-user management. By deploying the platform on a secure cloud infrastructure, multiple developers or students will be able to simultaneously access and validate different devices under controlled permissions. This will transform the system into a collaborative and distributed testing environment suitable for research, education, and industrial development.
The wireless connectivity through modules such as ESP 32 and STM 32 boards with Wi-Fi or Bluetooth, enabling over-the-air (OTA) firmware updates and mobile-based control. Finally, these advancements will transform Remote Validation into a fully intelligent, cloud-enabled, and scalable testing ecosystem for next-generation embedded and IoT systems.

Conclusion
This research demonstrates that efficient embedded system validation does not require complex or expensive laboratory setups. Through the integration of firmware automation and network-based control, the Remote Validation Platform enables seamless programming, testing, and monitoring of embedded boards entirely through remote access.
The results show that even low-cost hardware such as the Raspberry Pi can reliably manage firmware flashing, power cycling, and real-time data logging with precision comparable to traditional, hands-on validation methods. By emphasizing software-driven automation, this approach offers an affordable, scalable.
It bridges the gap between physical hardware and cloud accessibility, paving the way for a new generation of intelligent, location-independent validation ecosystems.

References
[1] L. F. Salazar, C. Sanchez, G. Brito, H. J. Velasteguí, J. Buele, and A. Soria,
“Remote Control and Monitoring of an Academic Station Using a Low-Cost Embedded Device,”Proc. Int. Conf. on Recent Innovations in Electrical, Electronics & Communication Engineering, 2018.
[2] Z. Haidong, Q. Liang, and W. Minglang,“Research of Remote Environmental Data Monitoring System,”Proc. 3rd Int. Conf. on Consumer Electronics, Communications and Networks, 2013.
[3] P. Jacko, M. Beres, I. Kovacova, J. Molnar, T. Vince, J. Dziak, B. Fecko, S. Gans, and D. Kovac,“Remote IoT Education Laboratory for Microcontrollers Based on the STM32 Chips,”
Electronics, vol. 22, no. 4, article no. 1440, 2022.
[4] I. Angulo, J. Garcia-Zubia, L. Rodríguez-Gil, and P. Orduna,“A NewApproach to Conduct Remote Experimentation over Embedded Technologies,”
Proc. 13th Int. Conf. on Remote Engineering and Virtual Instrumentation, 2016.
[5] Y. Watanabe, N. Yanai, and J. Shikata,“IoT-REX: A Secure Remote-Control System for IoT Devices from Centralized Multi-Designated Verifier Signatures,”Proc. Int. Conf. on Information Security Practice and Experience, pp. 105–122, 2023.