EcoMedRobo: Greentech Robotics for Physically Impaired Assistance and Mobility Autonomy

Abstract

This research introduces an independent solar-powered robotic system designed specifically to assist and care for elderly and physically disabled persons, embedding Internet of Things (IoT) technologies to improve accessibility and responsiveness of healthcare services. The system has a wireless relay system, allowing remote control and intervention by medical staff, thus making continuous patient monitoring and initial diagnostics possible. At the centre of the design is a robotic nursing unit that can travel autonomously to the patient\'s bedside, offering audio-guided instructions and performing basic hygiene services like automatic hand sanitization. To facilitate real-time health monitoring, the robot comes with essential diagnostic equipment in the form of a thermal scanner, pulse oximeter, and glucometer that enable the capture of vital health parameters. These data are transmitted securely to medical professionals through an integrated telemedicine platform that supports remote consultation, diagnosis, and treatment advice. The system focuses on sustainable energy consumption through the integration of solar power, facilitating long-term deployment in urban and rural healthcare settings. The application of this robotic solution illustrates great promise in enhancing medical service provision, patient independence, and distant healthcare effectiveness, particularly in areas with restricted access to timely medical care.

Introduction

1. Introduction

The rising elderly population and shortage of healthcare staff—especially nurses—present a global challenge, made worse during public health crises like pandemics. Robotic healthcare assistants offer a solution, providing remote support, real-time health monitoring, telepresence communication, and reduced contact in contagious environments. This study focuses on developing an autonomous, solar-powered robotic nurse with a hybrid ultra-capacitor battery system to ensure sustainable and continuous operation.

2. Methodology

The proposed system integrates IoT technology, enabling the robot to serve as a mobile health companion that communicates remotely with patients and medical staff. It consists of several modules:

• Remote Navigation: Wirelessly controlled motors allow the robot to move to patient locations.

• Sensor Integration: Includes IR, pulse, temperature, and glucometer sensors for real-time vital monitoring.

• Real-Time Communication: A wireless camera and speaker system support video streaming and doctor-patient interaction.

3. Key Challenges Identified

1. Low solar panel efficiency, especially indoors or in low-light.

2. Insufficient battery storage for cloudy or nighttime operation.

3. Interruptions in service due to weak power backup.

4. Limited multifunctionality in existing healthcare robots.

5. High initial cost due to advanced sensors and solar integration.

6. Navigation limitations in complex or diverse environments.

4. Proposed System: EcoMedRobo

A modular robotic platform powered by solar energy and a hybrid battery is designed to:

• Enhance healthcare access for elderly and disabled individuals.

• Operate autonomously using an ATmega2560 microcontroller.

• Continuously monitor health using biomedical sensors (pulse oximeter, glucometer, temperature sensor).

• Navigate autonomously using a line-following sensor and DC motors.

• Enable telemedicine via wireless video streaming and data sharing over IoT.

• Include automated dispensers for medicine and sanitizer.

• Provide scalability for future sensor or actuator additions.

5. Test Results & Performance

• Path-Following Accuracy: Mean deviation of 2.3 cm (less than 5% error).

• Energy Efficiency:

  • Peak solar output: 12 W; 68% stored in battery.

  • System operated 3.5 hours without grid power.

  • Overall energy efficiency: 54%.

• Solar Metrics:

  • Conversion efficiency: 17%.

  • Round-trip battery efficiency: 88%.

• Obstacle Avoidance: 93% detection success; rerouting within 0.7 seconds.

• Environmental Robustness: Stable performance in varying light/shadow and on sloped/uneven terrain.

6. Comparative & User Feedback

• Outperformed previous solar-powered robots with:

  • 20% longer operation

  • 15% better path accuracy

• Users praised:

  • Ease of deployment

  • Intuitive LCD feedback

  • Extended autonomy

Conclusion

The Smart Medical Auto Nursing System for Doctor Communication through Android App represents a transformative approach to modern healthcare, addressing critical challenges in patient care and nursing automation. By integrating real-time monitoring, automated nursing tasks, and seamless doctor communication, this system enhances the efficiency, accuracy, and reliability of medical services. The use of advanced sensors ensures continuous monitoring of patient vitals, while the motorized tray mechanism automates routine tasks such as medication delivery, reducing the workload on healthcare staff. The Android app bridges the gap between doctors and the system, allowing remote monitoring, control, and quick response to emergencies. This innovation not only reduces human error but also ensures timely interventions, especially in critical scenarios. By leveraging automation and communication technologies, the system aligns with the vision of a smarter, more connected healthcare ecosystem, ultimately improving patient outcomes and satisfaction.

References

[1] Subashka Ramesh, Tarun keshri, Sakshi singh, Aastha sharma, “Solar Powered Obstacle Avoiding Robot”, nternational Journal of Emerging Technologies in Engineering Research (IJETER)Volume 6, Issue 4, April (2018). [2] Zannatun Nayem, Istiaq Ahmed, Liton Kumar Biswas, “Solar Powered Explorer Robotic System Using GSM Technology”, DOI: 10.1109/ICAEEE.2018.8642996, Conference: 2018 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE). [3] Adam Kaplan, Nathaniel Kingry, Paul Uhing, Ran Dai, “Time-Optimal Path Planning With Power Schedules for a Solar-Powered Ground Robot”, IEEE Transactions on Automation Science and Engineering ( Volume: 14, Issue: 2, April 2017), DOI: 10.1109/TASE.2016.2533418. [4] Tarunpreet Kaur, Dilip Kumar, “Design and Development of Solar Powered and Cell Phone Operated Mobile Robot for Border Surveillance”, IJECT Vol. 5, IssuE 3, July - sEpT 2014, ISSN : 2230-7109 (Online) | ISSN : 2230-9543 (Print). [5] Shaik Meeravali, Suthagar S, “Automatic Solar Tracker Robot”, International Journal of Engineering Research & Technology (IJERT)Vol. 1 Issue 6, August – 2012, ISSN: 2278-0181. [6] A.B. Afarulrazi; W. M. Utomo; K.L. Liew; M. Zarafi, “Solar Tracker Robot using microcontroller”, 2011 International Conference on Business, Engineering and Industrial Applications, DOI: 10.1109/ICBEIA.2011.5994256, 22 August 2011. [7] Dario, P., Guglielmelli, E., & Laschi, C. (2019). Healthcare robotics: Automating routine tasks in patient care. IEEE Robotics & Automation Magazine, 26(2), 14-27. [8] Aronson, J. K., & Ferner, R. E. (2020). Automated medication delivery systems: A review of the technology. Journal of Clinical Pharmacy and Therapeutics, 45(3), 345-355. [9] Kim, J., Ryu, H., & Lee, S. (2018). IoT-based wearable devices for continuous vital sign monitoring. Sensors and Actuators A: Physical, 281, 74-85. [10] Singh, P., Sharma, A., & Gupta, R. (2021). Real-time emergency alert systems using microcontrollers and sensors. International Journal of Embedded Systems, 8(4), 187-198. [11] Zhang, H., Li, X., & Chen, Y. (2017). Android-based doctor-patient communication platforms: A review. Telemedicine and e-Health, 23(10), 873-881. [12] Patel, S., Desai, R., & Patel, H. (2019). Bluetooth and GSM-based healthcare communication systems: Challenges and opportunities. International Journal of Advanced Research in Computer Engineering & Technology, 8(9), 349-356. [13] Sharma, S., Verma, P., & Gupta, M. (2020). IoT-enabled frameworks for smart nursing systems. IEEE Internet of Things Journal, 7(6), 4990-5001. [14] Rao, V., Kumar, S., & Shankar, R. (2018). Mobile-controlled automation in healthcare devices. Procedia Computer Science, 125, 456-462. [15] Gupta, A., Choudhary, K., & Mishra, P. (2020). Addressing real-time reliability in healthcare systems. IEEE Transactions on Reliability, 69(1), 42-52. [16] Huang, Y., Wu, C., & Zhang, L. (2021). Integration challenges in hardware and communication systems for healthcare automation. Journal of Systems Engineering and Electronics, 32(5), 872-884.

Copyright

Copyright © 2025 Muthuram G, Dineshkumar S, Gokulakrishnan D, John Peter L, Ramaprakash S. 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.