TY - GEN
T1 - Developing Smart Farm and Traceability System for Agricultural Products using IoT Technology
AU - Wongpatikaseree, Konlakorn
AU - Kanka, Promprasit
AU - Ratikan, Arunee
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/14
Y1 - 2018/9/14
N2 - In the past, most farmers have taken care of their products by relying on basic observation and general knowledge. The quality of agricultural products depends on the farmer's skill and experience. Therefore, transferring knowledge of planting techniques from one generation to another is not an easy task. In recent years, the smart farm concept has been introduced. However, most current smart farming focuses on monitoring, without utilising the observed data in other ways. Therefore, the aim of this research is to propose a traceability system, summarising and presenting observed data from the smart farm. The Internet of Things (IoT) has been introduced in this research, using several sensors to detect the environmental data in the smart farm. The entire data from the results was computed and presented using a traceability system. Customers are provided with more information support, especially concerning the quality of the planting process, before buying an agricultural product by scanning a quick response (QR) code through a mobile application. This gives the customer greater confidence in the product.
AB - In the past, most farmers have taken care of their products by relying on basic observation and general knowledge. The quality of agricultural products depends on the farmer's skill and experience. Therefore, transferring knowledge of planting techniques from one generation to another is not an easy task. In recent years, the smart farm concept has been introduced. However, most current smart farming focuses on monitoring, without utilising the observed data in other ways. Therefore, the aim of this research is to propose a traceability system, summarising and presenting observed data from the smart farm. The Internet of Things (IoT) has been introduced in this research, using several sensors to detect the environmental data in the smart farm. The entire data from the results was computed and presented using a traceability system. Customers are provided with more information support, especially concerning the quality of the planting process, before buying an agricultural product by scanning a quick response (QR) code through a mobile application. This gives the customer greater confidence in the product.
UR - https://www.scopus.com/pages/publications/85055710728
U2 - 10.1109/ICIS.2018.8466479
DO - 10.1109/ICIS.2018.8466479
M3 - Conference contribution
AN - SCOPUS:85055710728
T3 - Proceedings - 17th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2018
SP - 180
EP - 184
BT - Proceedings - 17th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2018
A2 - Xiong, Wei
A2 - Shang, Wenqiang
A2 - Xu, Simon
A2 - Lee, Hwee-Kuan
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 17th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2018
Y2 - 6 June 2018 through 8 June 2018
ER -