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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67126
Volume:
10 |
9 |
Sep 2026
Pages:
1-10
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Applications
Visvesvaraya Technological University
Department of Computer Applications
Visvesvaraya Technological University
This paper presents a Smart IoT-Based Mini Greenhouse designed to automate environmental monitoring and control for precision agriculture. The proposed system uses a NodeMCU ESP8266 with temperature, humidity, soil-moisture, and mist sensors to continuously observe greenhouse conditions. Based on predefined environmental thresholds, the controller automatically operates a water pump, exhaust fan, misting unit, and LED grow light to maintain suitable conditions for plant growth. An LCD provides local information, while the Blynk IoT platform enables remote monitoring, alerts, and actuator control through a mobile application. The system reduces dependence on continuous manual supervision and supports more efficient use of water and energy. The implemented prototype demonstrates the feasibility of combining IoT sensing, automated actuation, and remote connectivity for small-scale greenhouse applications. The modular design can also be extended with additional sensors, data analytics, machine learning, and predictive control techniques for improved crop management.
KEYWORDS
The proposed Smart IoT-Based Mini Greenhouse combines environmental sensing, automated control, and IoT-based monitoring to support efficient greenhouse management. The NodeMCU ESP8266 receives data from temperature, humidity, soil-moisture, and mist sensors and controls the water pump, exhaust fan, misting unit, and LED grow light according to predefined conditions. A 16×2 LCD provides local information, while the Blynk IoT platform enables remote monitoring and notifications. The developed system reduces the need for continuous manual supervision and provides an integrated approach to greenhouse environmental management. In future, the system can be improved by incorporating machine learning for predictive control, additional sensors for detailed crop monitoring, computer vision for plant health assessment, solar-powered operation, and cloud-based data analytics, making the greenhouse more adaptive and suitable for advanced precision agriculture.
[1] B. S. Pochal and A. A. Patil, “An Agricultural Robotic Device to Monitor Soil Moisture, Temperature, Humidity and Illumination Using IOT Cloud Visualization,” Journal of Emerging Technologies and Innovative Research (JETIR), vol. 5, no. 7, pp. 414–421, July 2018, ISSN: 2349-5162. ORCID ID: 0000-0001-9562-8420 [2] Bharati S. Pochal and Anitha, “An Advanced IoT Based Multi Activity Agriculture Robotic Platform with Android Controlled Navigation,” International Journal of Emerging Technologies and Innovative Research (JETIR), ISSN: 2349-5162, vol. 5, no. 8, pp. 714–724, Aug. 2018. [3] S. Arala and B. S. Pochal, “Application Framework for the Prediction of Common Diseases Using Machine Learning,” Journal of Scientific Research and Technology (JSRT), vol. 2, no. 8, Aug. 2024. [4] Rajguru and B. S. Pochal, “Skin Cancer Detection Using Deep Learning,” International Journal for Multidisciplinary Research (IJFMR), vol. 6, no. 6, Nov.–Dec. 2024. [5] S. Silpa, “Smart Greenhouses: IoT Technologies for Controlled Environments,” 2024. [6] S. Li, X. Li, and H. Wang, “IoT-Based Environmental Monitoring and Control for Smart Greenhouse Agriculture,” Computers and Electronics in Agriculture, 2021. [7] C. Bersani, C. Ruggiero, R. Sacile, E. Zero, and A. Delfino, “IoT-Based Smart Greenhouse: A Review,” 2022. [8] P. V. B. Astillo, J. Kim, V. Sharma, and I. You, “SGF-MD: Behavior Rule Specification-Based Distributed Misbehavior Detection of Embedded IoT Devices in a Closed-Loop Smart Greenhouse Farming System,” IEEE Access, 2020. [9] L. F. Urbano, M. A. C. others, “Smart Irrigation Systems Using Soil Moisture Sensors and IoT Technologies,” Sensors, 2020. [10] R. Rayhana, G. Xiao, and Z. Liu, “Internet of Things Empowered Smart Greenhouse,” IEEE Journal of Emerging and Selected Topics in Industrial Electronics, 2020.
Publication Date
9/5/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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