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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	2019 Third International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) s. 456 - 462
Hlavní autoři:	Neethu, B.N., Jayanthy, S, J, Judeson Antony Kovilpillai
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.12.2019
Témata:	automation Modified K-Means Clustering Algorithm Sensors STM32F 401RE Arm-Cortex-M4 based Microcontroller Traditional K-Means Clustering algorithm
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	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