Mobile Solar Powered Irrigation System

Abstract

Water scarcity and rising fossil fuel prices present challenges to the global agricultural community. Conventional irrigation systems frequently depend on erratic power sources, are inefficient, and are stationary. This study suggests a mobile solar-powered irrigation system that maximizes energy and water resources. A solar panel for renewable energy, a DHT22 and pH sensor for water and environmental health analysis, and a Bluetooth module for local control are all integrated into the system using an ESP32 microcontroller. Additionally, the Webserver interface enables remotely accessing and managing the system.Using of Soil Moisture sensor for detection of water in soil for proper irrigation. The mobile feature of the system also enables it to irrigate several plot areas with a single unit, which is a major cost-saving factor. Preliminary results indicate that the system improves crop production while minimizing environmental degradation through data-driven irrigation. In the aftermath of worldwide climate change and the depletion of freshwater resources, the agricultural community is under a critical mandate to upgrade and modernize. Traditional irrigation systems are marked by inefficiency, labor intensity, and dependence on fossil fuel-based electricity. This research paper proposes a new Mobile Solar-Powered Irrigation System that combines the ESP32 microcontroller, IoT (Internet of Things) technology, and Android mobile control. Unlike traditional irrigation systems, this proposed system has a moveable chassis that is driven by renewable solar energy and can irrigate divided land parcels. The system uses a DHT22 sensor for environmental monitoring and a pH sensor mechanism for ensuring the availability of water nutrients. The data is transmitted through a Bluetooth module for local control and a Webserver for remote analysis. The proposed system design is cost-effective, scalable, and energy-independent, which optimizes water and crop yields to a great extent.

Introduction

Agriculture is increasingly strained by rising global food demand, climate change, and especially water scarcity. Traditional irrigation methods are inefficient, wasting large amounts of water and relying heavily on fossil fuels or unstable electricity supplies. This makes farming costly and environmentally unsustainable. As a result, “Smart Agriculture” (Agriculture 4.0) using IoT, automation, and renewable energy is becoming necessary.

However, existing automated irrigation systems have key limitations: they are usually fixed (not suitable for multiple small plots), depend on unreliable or non-renewable energy sources, and often ignore water quality factors like pH, which affects soil fertility and crop health.

To address these issues, the study proposes a mobile solar-powered irrigation rover. This system can move across farmland, use solar energy for power, and perform precision irrigation using sensors such as soil pH, temperature, and humidity. It also supports dual communication through Bluetooth (local control) and IoT web systems (remote monitoring and data logging).

The project aims to create a low-cost, scalable prototype that improves water efficiency, reduces energy dependence, and enables smarter farming decisions.

The literature review shows that while many smart irrigation systems use IoT, machine learning, or solar power, most are limited in one or more areas—such as lack of mobility, poor sustainability, limited automation, or weak real-world implementation. The proposed system attempts to combine mobility, renewable energy, and intelligent sensing into a single integrated solution.

Conclusion

• The Mobile Solar-Powered Irrigation System designed in this research work is a major technological break-through in the area of precision agriculture. The success-ful amalgamation of Robotics, Renewable Energy, and IoT in the system has effectively resolved the ”trilemma” of modern agriculture, which includes water scarcity, energy costs, and lack of human resources. • Operational Viability: The system has successfully proved that a mobile system can replace several fixed sensor nodes. By incorporating the sensing and pumping system into a rover, the system has shown a increase in coverage area compared to a fixed system of the same cost. • Resource Conservation: The system has successfully proved that data-driven irrigation, which was activated only when certain temperature, humidity, and pH levels were attained, has shown a reduction in water usage compared to traditional timer-controlled irrigation sys-tems. • Energy Independence: The system has successfully proved that the 20W Solar Panel and battery storage system were adequate to power the daily operations of the robot. The “Off-Grid” feature of the system allows it to be put to use immediately in rural areas where the electrical grid may be unreliable or unavailable altogether. • Holistic Monitoring: While conventional methods are mainly confined to measuring moisture content in the soil, it is significant to mention that the addition of a pH sensor system allows one to measure the quality of water used for irrigation. This is because maintaining water in a suitable pH range ensures proper development of crops by providing adequate nutrition. • Conclusion: This project has achieved its objectives in providing a cost-effective, scalable, and eco-friendly solution that enables farmers to shift from ”gut-feeling” farming to ”data-driven” farming. • Future Scope: Although the prototype developed is com-plete and functional, the ever-advancing nature of tech-nology opens up several directions for improvement. The following features are proposed to upgrade the system from an ”Automated Tool” to an ”Intelligent Assistant.”

References

[1] Y. Gamal, A. Soltan, L. A. Said, A. H. Madian and A. G. Radwan, ”Smart Irrigation Systems: Overview,” in IEEE Access, vol. 13, pp. 66109-66121, 2025, doi: 10.1109/ACCESS.2023.3251655. keywords: [2] Irrigation;Crops;Water resources;Soil moisture;Agriculture;Intelligent sensors;Artificial neural networks;Smart irrigation;soil monitoring;smart agriculture;IoT;energy harvesting, [3] Abdelhamid, M.A., Abdelkader, T.K., Sayed, H.A.A. et al. De-sign and evaluation of a solar powered smart irrigation sys-tem for sustainable urban agriculture. Sci Rep 15, 11761 (2025). https://doi.org/10.1038/s41598-025-94251-3 [4] Tace, Youness, et al. ”Smart irrigation system based on IoT and machine learning.” Energy Reports 8 (2022): 1025-1036. [5] Gamal, Yomna, et al. ”Smart irrigation systems: Overview.” Ieee Access (2023). [6] Ragab, Mohammed Ali, et al. ”IOT based smart irrigation system.” International Journal of Industry and Sustainable Development 3.1 (2022): 76-86. [7] Pereira, Gilroy P., Mohamed Z. Chaari, and Fawwad Daroge. ”IoT-enabled smart drip irrigation system using ESP32.” IoT 4.3 (2023): 221-243. [8] Shouqi, Yuan, et al. ”Optimization of movable irrigation system and performance assessment of distribution uniformity under varying condi-tions.” International Journal of Agricultural and Biological Engineering 10.1 (2017): 72-79. [9] Kumar, Utkarsh, and Shyam Nath. ”Performance Evaluation of Irrigation Characteristics Operated by Movable Solar Irrigation System Using Micro-irrigation Techniques in Hilly Region of Uttarakhand.” National Academy Science Letters (2026): 1-14. [10] Kanda, Edwin Kimutai, and Valery Osimbo Lutta. ”The status and challenges of a modern irrigation system in Kenya: A systematic review.” Irrigation and Drainage 71 (2022): 27-38. [11] Del-Coco, Marco, Marco Leo, and Pierluigi Carcagn`?. ”Machine learn-ing for smart irrigation in agriculture: How far along are we?.” Infor-mation 15.6 (2024): 306. [12] Touil, Sami, et al. ”A review on smart irrigation management strategies and their effect on water savings and crop yield.” Irrigation and Drainage [13] 71.5 (2022): 1396-1416. [14] Bwambale, Erion, Felix K. Abagale, and Geophrey K. Anornu. ”Smart irrigation monitoring and control strategies for improving water use efficiency in precision agriculture: A review.” Agricultural Water Man-agement 260 (2022): 107324. [15] Et-Taibi, Bouali, et al. ”Enhancing water management in smart agri-culture: A cloud and IoT-Based smart irrigation system.” Results in Engineering 22 (2024): 102283. [16] Ragab, Mohammed Ali, et al. ”IOT based smart irrigation system.” International Journal of Industry and Sustainable Development 3.1 (2022): 76-86. [17] Abuzanouneh, Khalil Ibrahim Mohammad, et al. ”Design of machine learning based smart irrigation system for precision agriculture.” Com-puters, Materials, and Continua 72.1 (2022): 109. [18] Saraf, Shweta B., and Dhanashri H. Gawali. ”IoT based smart irrigation monitoring and controlling system.” 2017 2nd IEEE international con-ference on recent trends in electronics, information and communication technology (RTEICT). IEEE, 2017. [19] Ali, Awais, Tajamul Hussain, and Azlan Zahid. ”Smart irrigation tech-nologies and prospects for enhancing water use efficiency for sustainable agriculture.” AgriEngineering 7.4 (2025): 106. [20] Srivastava, Ritika, et al. ”A research paper on smart agriculture using IoT.” International Research Journal of Engineering and Technology (IRJET) 7.07 (2020): 2708-2710. [21] Risheh, Ali, Amirmohammad Jalili, and Ehsan Nazerfard. ”Smart Irri-gation IoT solution using transfer learning for neural networks.” 2020 10th International Conference on Computer and Knowledge Engineering (ICCKE). IEEE, 2020. [22] Obaideen, Khaled, et al. ”An overview of smart irrigation systems using IoT.” Energy Nexus 7 (2022): 100124. [23] Wanyama, Joshua, et al. ”Development of a solar powered smart irrigation control system Kit.” Smart Agricultural Technology 5 (2023): 100273. [24] Daraz, Umar, S?tefan Bojnec, and Younas Khan. ”Energy-efficient smart irrigation technologies: A pathway to water and energy sustainability in agriculture.” Agriculture 15.5 (2025): 554. [25] V. Reddy et al., “Solar powered irrigation automation system,” IEEE, 2021. [26] H. Zhang et al., “Fuzzy logic-based irrigation control system,” IEEE, 2024.

Copyright

Copyright © 2026 Shriraj Joshi, Samruddhi Kadam, Ashutosh Adsar. 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.