Greenhouse Monitoring and Controlling using Modified K Means Clustering Algorithm

An embedded system is developed for monitoring and controlling the parameters that affect the growth of plants using STM32F401RE ARM Cortex M4 based Microcontrollers. Parameters such as Light intensity, Soil Moisture, CO2, Temperature, are monitored. The measured values are processed using Modified...

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Veröffentlicht in:	2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) S. 456 - 462
Hauptverfasser:	Neethu, B.N., Jayanthy, S, J, Judeson Antony Kovilpillai
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2019
Schlagworte:	automation Modified K-Means Clustering Algorithm Sensors STM32F 401RE Arm-Cortex-M4 based Microcontroller Traditional K-Means Clustering algorithm
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Beschreibung
Zusammenfassung:	An embedded system is developed for monitoring and controlling the parameters that affect the growth of plants using STM32F401RE ARM Cortex M4 based Microcontrollers. Parameters such as Light intensity, Soil Moisture, CO2, Temperature, are monitored. The measured values are processed using Modified K Means Clustering Algorithm to find if the values are needed to be optimized to the required level to enhance the plant growth. The results are compared with the Traditional K-Means Clustering algorithm. The results indicate that the proposed algorithm gives better results in terms of accuracy and execution time compared to traditional one. The data that are measured and predicted are viewed using Cool Term.
DOI:	10.1109/I-SMAC47947.2019.9032656