Design and implementation of outdoor home smart farming based on raspberry pi for home assistant management

Mohd Nazmin Maslan; Izzat Rafaie Ramli; Muhammad Hafidz Fazli Md Fauadi; Mohd Erdi Ayob; Mohamad Faizal Baharom; Ihwan Ghazali; Tia Tanjung

doi:10.31893/multiscience.2025418

Keywords:

outdoor home smart farming

Abstract

Outdoor home smart farming, also known as urban farming, is the practice of cultivating fruits, herbs, or vegetables for personal consumption on a small scale within a residential area. It is more sustainable compared to conventional agriculture in all aspects. However, there were various challenges in implementing outdoor home smart farming, including limitation or lack of skills, resources, or infrastructure to produce good and high-quality crops. This study addresses these challenges by integrating Python scripting and Linux OS with hardware components like the Raspberry Pi 4 Model B, ESP32, soil moisture sensors, and UV lights. Home Assistant, an open-source software, was utilized to run the script programming for outdoor home smart farming. The integrated smart devices into Home Assistant were used to monitor and analyze the farming parameters outcomes to assist decision-making and provide further user action. As a result, the system was efficient due to only consuming 0.16% for water usage and 0.64% for energy consumption compared to daily household use, as well as reducing water usage by up to 82.45% for the watering process. These results highlight the system’s capability to optimize resource usage and enhance crop productivity while minimizing environmental impact. By leveraging smart devices and IoT frameworks, the study showcases how modern technology can revolutionize traditional farming practices. The automated system not only reduces manual labor but also provides real-time data to assist in decision-making and further user actions. In conclusion, the implementation of Home Assistant management based on Raspberry Pi in outdoor home smart farming effectively addresses the challenges of urban agriculture.
References
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to cite

Maslan, M. N., Ramli, I. R., Md Fauadi, M. H. F., Ayob, M. E., Baharom, M. F., Ghazali, I., & Tanjung, T. (2025). Design and implementation of outdoor home smart farming based on raspberry pi for home assistant management. Multidisciplinary Science Journal, 7(8), 2025418. https://doi.org/10.31893/multiscience.2025418

[1] Chauhdary, J. N., Li, H., Jiang, Y., Pan, X., Hussain, Z., Javaid, M., & Rizwan, M. (2024). Advances in Sprinkler Irrigation: A Review in the Context of Precision Irrigation for Crop Production. Agronomy, 14(1), 47. https://doi.org/10.3390/agronomy14010047

[2] Dev, P., Khandelwal, S., Yadav, S. C., Arya, V., Mali, H. R., & Poonam (2023). Climate based smart agriculture: Need for food security and sustainability. International Journal of Enviornment and Climate Change, 13(3), 224–231. https://doi.org/10.9734/IJECC/2023/V13I31702

[3] Edwards, J., Laskowski, M., Baskin, T. I., Mitchell, N., & DeMeo, B. (2019). The role of water in fast plant movements. Integrative and Comparative Biology, 59(6), 1525–1534. https://doi.org/10.1093/icb/icz081

[4] Gebresenbet, G., Bosona, T., Patterson, D., Persson, H., Fischer, B., Mandaluniz, N., Chirici, G., Zacepins, A., Komasilovs, V., Pitulac, T., & Nasirahmadi, A. (2023). A concept for application of integrated digital technologies to enhance future smart agricultural systems. Smart Agricultural Technology, 5, 100255. https://doi.org/10.1016/J.ATECH.2023.100255

[5] Gómez, C., Currey, C. J., Dickson, R. W., Kim, H. J., Hernández, R., Sabeh, N. C., Raudales, R. E., Brumfield, R. G., Laury-Shaw, A., Wilke, A. K., Lopez, R. G., & Burnett, S. E. (2019). Controlled environment food production for urban agriculture. HortScience, 54(9), 1448–1458. https://doi.org/10.21273/HORTSCI14073-19

[6] Katunský, D., Korjenic, A., Katunská, J., & Lopušniak, M. (2011). Evaluation of energy consumption for heating of industrial building in-situ. Engineering, 3(5), 470-477. https://doi.org/10.4236/eng.2011.35054

[7] Keneti, A., Farsadizadeh, D., Bahramian, Y., & Javadi, A. (2022). Sprinkler irrigation efficiency in relation to water surface tension: Pesticide and fertilizer effect on drop size and soil water uptake. Water Conservation Science and Engineering, 7, 173-181. https://doi.org/10.1007/s41101-021-00124-x

[8] Khaleefah, R. M., Al-isawi, N. A., Hussein, M. K., & Alduais, N. A. M. (2023). Optimizing IoT data transmission in smart agriculture: A comparative study of reduction techniques. In 2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) (p. 1-5). Istanbul, Turkiye. https://doi.org/10.1109/HORA58378.2023.10156757

[9] Maraveas, C. (2023). Incorporating Artificial Intelligence Technology in Smart Greenhouses: Current State of the Art. Applied Sciences, 13(1), 14. https://doi.org/10.3390/app13010014

[10] Nederhoff, E., & Stanghellini, C. (2010). Water use efficiency of tomatoes-in greenhouses and hydroponics. Practical Hydroponics and Greenhouses, https://edepot.wur.nl/156932. Accessed on April 15, 2024.

[11] Parvin, K., Hafiz, W., Abdullah, M., Hannan, M., & Salam, M. (2020). Estimation of building energy management toward minimizing energy consumption and carbon emission. Journal of Advanced Manufacturing Technology (JAMT), 14(2(2), 1-12. https://jamt.utem.edu.my/jamt/article/view/6053

[12] Quy, V. K., Hau, N. Van, Anh, D. Van, Quy, N. M., Ban, N. T., Lanza, S., Randazzo, G., & Muzirafuti, A. (2022). IoT-enabled smart agriculture: Architecture, applications, and challenges. Applied Sciences, 12(7), 1-19. https://doi.org/10.3390/APP12073396

[13] Sadewa, D. P. P. (2016). Pemanfaatan Padatan Digestat sebagai Media Tanam Pak Choi (Brassica rapa L.) dengan Sistem Irigasi Bawah Permukaan (Master thesis). Fakultas Pertanian, Universitas Lampung, Bandar Lampung, Indonesia.

[14] Sahin, G., Isik, G., & van Sark, W. G. J. H. M. (2023). Predictive modeling of PV solar power plant efficiency considering weather conditions: A comparative analysis of artificial neural networks and multiple linear regression. Energy Reports, 10, 2837–2849. https://doi.org/10.1016/j.egyr.2023.09.097

[15] Sahoo, R. S., Tripathy, C. K., Samantasinghar, U., & Biswal, P. (2022). Implementation of an indoor deep water culture farming system using IoT. In 2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC). Gunupur, Odisha, India. https://doi.org/10.1109/iSSSC56467.2022.10051358

[16] Sendari, S., Rahmawati, Y., Ramadhan, F., Alqodri, F., Tibyani, T., Matsumoto, T., Fujiyama, A., & Rachman, I. (2022). Energy usage monitoring system for environmental mobile station. Journal of Advanced Manufacturing Technology (JAMT), 16(3), 1-14. https://jamt.utem.edu.my/jamt/article/view/6406

[17] Touil, S., Richa, A., Fizir, M., Argente García, J. E., & Skarmeta Gómez, A. F. (2022). A review on smart irrigation management strategies and their effect on water savings and crop yield. Irrigation and Drainage, 71(5), 1396–1416. https://doi.org/10.1002/ird.2735

[18] Vallejo-Gómez, D., Osorio, M., & Hincapié, C. A. (2023). Smart Irrigation Systems in Agriculture: A Systematic Review. Agronomy, 13(2), 342. https://doi.org/10.3390/agronomy13020342

[19] Verschae, R. (2023). Smart Technologies in Agriculture. In Q. Zhang (Eds.), Encyclopedia of Smart Agriculture Technologies (pp. 1–11). Springer. https://doi.org/10.1007/978-3-030-89123-7_234-1

Abstract

References

How to cite