TY - GEN
T1 - ANFIS for Vegetation Effects Prediction in Paddy Field for Wireless Sensor Network
AU - Burapattanasiri, Bancha
AU - Phaiboon, Supachai
AU - Phokharatkul, Pisit
AU - Liswadiratanakul, Danai
AU - Kimpan, Chom
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Currently, the establishment of a dedicated wireless sensor network distributed in agricultural areas. Monitor and record the physical conditions of the environment and forward the collected data to a control center. The wireless sensor network (WSN) measures the environmental conditions such as temperature, humidity and rainfall. But the height of plants, the height of the transmitting antenna, the distance and the frequency of the WSN system have the effect on the transmission of radio waves. In this experiment, the measurement data set includes the height of rice grown 105 cm, antenna height 55 cm, 105 cm and 155 cm were used to find the vegetation effect for wireless sensor network using adaptive neuro-fuzzy inference system (ANFIS). The frequency of 2400 MHz and 930 MHz were used at different distances from 5 m to 55 m. The results from the ANFIS model were more accurate compared to the Weissberger model. Furthermore, the antenna heights at 55 cm. and 105 cm. Furthermore, the antenna heights of 55 cm and 105 cm, radio signal transmission was attenuation due to rice plants significantly.
AB - Currently, the establishment of a dedicated wireless sensor network distributed in agricultural areas. Monitor and record the physical conditions of the environment and forward the collected data to a control center. The wireless sensor network (WSN) measures the environmental conditions such as temperature, humidity and rainfall. But the height of plants, the height of the transmitting antenna, the distance and the frequency of the WSN system have the effect on the transmission of radio waves. In this experiment, the measurement data set includes the height of rice grown 105 cm, antenna height 55 cm, 105 cm and 155 cm were used to find the vegetation effect for wireless sensor network using adaptive neuro-fuzzy inference system (ANFIS). The frequency of 2400 MHz and 930 MHz were used at different distances from 5 m to 55 m. The results from the ANFIS model were more accurate compared to the Weissberger model. Furthermore, the antenna heights at 55 cm. and 105 cm. Furthermore, the antenna heights of 55 cm and 105 cm, radio signal transmission was attenuation due to rice plants significantly.
KW - ANFIS
KW - Vegetation Effects prediction
KW - WSN
KW - Weissberger model
KW - paddy field
UR - https://www.scopus.com/pages/publications/85165709873
U2 - 10.1109/ICEAST58324.2023.10157426
DO - 10.1109/ICEAST58324.2023.10157426
M3 - Conference contribution
AN - SCOPUS:85165709873
T3 - 2023 9th International Conference on Engineering, Applied Sciences, and Technology, ICEAST 2023 - Proceeding
SP - 29
EP - 32
BT - 2023 9th International Conference on Engineering, Applied Sciences, and Technology, ICEAST 2023 - Proceeding
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Engineering, Applied Sciences, and Technology, ICEAST 2023
Y2 - 1 June 2023 through 4 June 2023
ER -