Smart Greenhouse System for Cultivating Medicinal Plants for Patient Care with IoT Integration

Bangladesh is a developing and overpopulated coun- try, where the increase in population has led to a reduction in arable land while the demand for food is rising, and diseases are spreading due to people’s lack of awareness. New diseases and pathogens are emerging and spreading among people. Due to the increase in population, the demand for medicines has also increased, but the decrease in arable land has made it difficult to obtain complete medicinal plants. This research proposes a low-cost IoT-based greenhouse system capable of creating a suitable environment for cultivating medicinal plants. The advanced system uses several gas sensor nodes to detect NH3, CO, smoke, and CO2, and if harmful gases increase, it triggers an alarm and notifies via email/messages. Additionally, by using soil moisture sensors, we can determine when the soil needs watering or how much water is available, and whether the soil is wet or dry. Temperature sensors inside the greenhouse provide information on the temperature, and if it gets too hot, a cooling fan is used to regulate the temperature. Moreover, there are other sensors such as a water level sensor, which indicates how much water is accumulated in the tank or specific water storage areas. If the water level decreases, it automatically refills through a motor. A rain sensor also detects external rainfall. Using these sensors, environmental parameters are monitored in real-time to create an ideal environment for cultivating medicinal plants. This system addresses common challenges in traditional agriculture, such as resource waste and unfavorable growth conditions. Furthermore, with the increasing population, we are facing challenges in meeting food and medicinal needs, but the smart greenhouse system can fulfill these demands for food and medicine.

Smart Greenhouse, Internet of Things (IoT), En- vironmental Monitoring

1. A. Ranjithkumar, “Assessing the impact of agricultural land reduction on future global food security: Challenges and sustainable solutions.” [Google Scholar] [Crossref]

2. M. R. Rashel, M. Islam, S. Sultana, M. T. Ahmed, T. M. N. U. Akhund, and J. N. Sikta, “Internet of things platform for advantageous renewable energy generation,” in Proceedings of International Conference on Advanced Computing Applications, J. K. Mandal, R. Buyya, and D. De, Eds. Singapore: Springer Singapore, 2022, pp. 107–117. [Google Scholar] [Crossref]

3. M. S. Farooq, R. Javid, S. Riaz, and Z. Atal, “Iot based smart greenhouse framework and control strategies for sustainable agriculture,” IEEE Access, vol. 10, pp. 99 394–99 420, 2022. [Google Scholar] [Crossref]

4. B. Jacobson, P. H. Jones, J. Jones, and J. Paramore, “Real- time greenhouse monitoring and control with an expert system,” Computers and Electronics in Agriculture, vol. 3, no. 4,pp. 273–285, 1989. [Online]. Available: https://www.sciencedirect.com/science/article/pii/0168169989900185 [Google Scholar] [Crossref]

5. A. F. Subahi and K. E. Bouazza, “An intelligent iot-based system design for controlling and monitoring greenhouse temperature,” IEEE Access, vol. 8, pp. 125 488–125 500, 2020. [Google Scholar] [Crossref]

6. N. Sadek, N. kamal, and D. Shehata, “Internet of things based smart automated indoor hydroponics and aeroponics greenhouse in egypt,” Ain Shams Engineering Journal, vol. 15, no. 2, p. 102341, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2090447923002307 [Google Scholar] [Crossref]

7. R. Liao, S. Zhang, X. Zhang, M. Wang, H. Wu, and L. Zhangzhong, “Development of smart irrigation systems based on real-time soil moisture data in a greenhouse: Proof of concept,” Agricultural Water Management, vol. 245, p. 106632, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S037837742032179X [Google Scholar] [Crossref]

8. Y. Yang, S. Ding, Y. Liu, S. Meng, X. Chi, R. Ma, and C. Yan, “Fast wireless sensor for anomaly detection based on data stream in an edge-computing-enabled smart greenhouse,” Digital Communications and Networks, vol. 8, no. 4, pp. 498–507, 2022. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2352864821000948 [Google Scholar] [Crossref]

9. H. H. Nguyen, D.-Y. Shin, W.-S. Jung, T.-Y. Kim, and D.-H. Lee, “An integrated iot sensor-camera system toward leveraging edge computing for smart greenhouse mushroom cultivation,” Agriculture, vol. 14, no. 3, 2024. [Online]. Available: https://www.mdpi.com/2077-0472/14/3/489 [Google Scholar] [Crossref]

10. Y. Liu, “Smart greenhouse monitoring and controlling based on nodemcu,” International Journal of Advanced Computer Science and Applications, vol. 13, no. 9, 2022. [Google Scholar] [Crossref]

11. A. M. Okasha, H. G. Ibrahim, A. H. Elmetwalli, K. M. Khedher, Z. M. Yaseen, and S. Elsayed, “Designing low-cost capacitive-based soil moisture sensor and smart monitoring unit operated by solar cells for greenhouse irrigation management,” Sensors, vol. 21, no. 16, 2021. [Online]. Available: https://www.mdpi.com/1424-8220/21/16/5387 [Google Scholar] [Crossref]

12. H. Guan, “Greenhouse environmental monitoring and control system based on improved fuzzy pid and neural network algorithms,” Journal of Intelligent Systems, vol. 34, no. 1, p. 20240079, 2025. [Online]. Available: https://doi.org/10.1515/jisys-2024-0079 [Google Scholar] [Crossref]

13. P. Kirci, E. Ozturk, and Y. Celik, “A novel approach for monitoring of smart greenhouse and flowerpot parameters and detection of plant growth with sensors,” Agriculture, vol. 12, no. 10, 2022. [Online]. Available: https://www.mdpi.com/2077-0472/12/10/1705 [Google Scholar] [Crossref]

14. A. Mellit, M. Benghanem, O. Herrak, and A. Messalaoui, “Design of a novel remote monitoring system for smart greenhouses using the internet of things and deep convolutional neural networks,” Energies, vol. 14, no. 16, 2021. [Online]. Available: https://www.mdpi.com/1996- 1073/14/16/5045 [Google Scholar] [Crossref]

15. M. T. RANI, S. RAHUL, S. GOVARDHAN, D. VELMURUGAN, and J. REJINA, “Iot based smart and economic greenhouse monitoring and auto-tuned control system for rural farming,” Journal of Theoretical and Applied Information Technology, vol. 102, no. 8, 2024. [Google Scholar] [Crossref]

16. C. Bersani, C. Ruggiero, R. Sacile, A. Soussi, and E. Zero, “Internet of things approaches for monitoring and control of smart greenhouses in industry 4.0,” Energies, vol. 15, no. 10, p. 3834, 2022. [Google Scholar] [Crossref]

17. A. Kouadria, K. Mostefaoui, and M. Y. H. Al-Shamri, “Efficient smart greenhouse modeling for optimal energy consumption and climate conditions setting,” Computers and Electronics in Agriculture, vol. 229, p. 109674, 2025. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0168169924010652 [Google Scholar] [Crossref]

• The Impact of Ownership Structure on Dividend Payout Policy of Listed Plantation Companies in Sri Lanka
• Urban Sustainability in North-East India: A Study through the lens of NER-SDG index
• Performance Assessment of Predictive Forecasting Techniques for Enhancing Hospital Supply Chain Efficiency in Healthcare Logistics
• The Fractured Self in Julian Barnes' Postmodern Fiction: Identity Crisis and Deflation in Metroland and the Sense of an Ending
• Impact of Flood on the Employment, Labour Productivity and Migration of Agricultural Labour in North Bihar