Design and implementation of WSN and IoT for precision agriculture in tomato crops

被引:0
作者
Nunez, Juan M., V [1 ]
Fonthal R, Faruk [1 ]
Quezada, Yasmin M. L. [2 ]
机构
[1] Univ Autonoma Occidente, Fac Engn, Adv Mat Micro & Nanotechnol Res Grp, Cali, Colombia
[2] Fujian Agr & Forestry Univ, Crop Sci Sch, Fuzhou, Fujian, Peoples R China
来源
2018 IEEE ANDESCON | 2018年
关键词
Precision Agriculture; Wireless Sensor Network; tomatoes; geostatistics; production;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This research presents the design and implementation of a precision agriculture system using sensor networks as the basis in precision agriculture for farmers tomatoes (Solanum lycopersicum) in Colombia with the aim of transferring knowledge and mitigating the effects of the soil and climate change on of tomato crops. Finally we found the optimal ranges to improve productivity and avoid losses due to uncontrolled agroclimatic variables such as relative temperature, soil temperature, relative humidity, soil moisture and luminosity. Also, this paper aim a IoT architecture for the respective storage and traceability of tomato crops in the cloud.
引用
收藏
页数:5
相关论文
共 50 条
[41]   IoT-based optical sensor network for precision agriculture [J].
Sharma, Amit ;
Srivastava, Diksha ;
Krishnamoorthy, Ramkumar ;
Sinha, Sanjay Kumar ;
Jhansirani, P. ;
Barve, Amit .
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS, 2025, 46
[42]   DESIGN OF FARMLAND GIS FOR PRECISION AGRICULTURE [J].
An Kai ;
Xie Gao-di ;
Leng Yun-fa ;
Xiao Yu .
CHINESE GEOGRAPHICAL SCIENCE, 2003, 13 (01) :20-24
[43]   Design of farmland gis for precision agriculture [J].
Kai An ;
Gao-di Xie ;
Yun-fa Leng ;
Yu Xiao .
Chinese Geographical Science, 2003, 13 :20-24
[44]   DESIGN OF FARMLAND GIS FOR PRECISION AGRICULTURE [J].
AN Kai XIE Gaodi LENG Yunfa XIAO Yu Institute of Geographical Sciences and Natural Resources Research the Chinese Academy of Sciences Beijing P R China .
Chinese Geographical Science, 2003, (01) :22-26
[45]   Sensor and Communication Considerations in UAV-WSN Based System for Precision Agriculture [J].
Vlasceanu, Emilian ;
Dima, Marius ;
Popescu, Dan ;
Ichim, Loretta .
PROCEEDINGS OF THE IEEE 2019 9TH INTERNATIONAL CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS (CIS) ROBOTICS, AUTOMATION AND MECHATRONICS (RAM) (CIS & RAM 2019), 2019, :281-286
[46]   Hybrid neural network classification for irrigation control in WSN based precision agriculture [J].
Anguraj, Dinesh Kumar ;
Mandhala, Venkata Naresh ;
Bhattacharyya, Debnath ;
Kim, Tai-hoon .
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2021,
[47]   Predicting Health Status of Maize Crops by Integrating IoT Technology and Inception-v3 Convolutional Neural Network in Precision Agriculture [J].
Jururyishya, G. Bisetsa ;
Nzanywayingoma, F. ;
Musabe, R. ;
Habimana, J. Claude ;
Abingabiye, C. .
PROCEEDINGS OF NINTH INTERNATIONAL CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGY, VOL 8, ICICT 2024, 2024, 1004 :141-152
[48]   CropFinder: AI-based Detection and Tracking of Crops for Precision Agriculture [J].
Abayaratne, Savini ;
Su, Daobilige ;
Qiao, Yongliang .
2024 33RD INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS, ISIE 2024, 2024,
[49]   PROFITABILITY RANKING OF PRECISION AGRICULTURE MEASUREMENT SYSTEM IMPLEMENTATION [J].
Zacepins, Aleksejs ;
Stalidzans, Egils ;
Karasha, Toms .
12TH INTERNATIONAL SCIENTIFIC CONFERENCE ENGINEERING FOR RURAL DEVELOPMENT, 2013, :164-169
[50]   Understanding the barriers to the implementation of precision agriculture in the central region [J].
Markley, J. ;
Hughes, J. .
INTERNATIONAL SUGAR JOURNAL, 2014, 116 (1384) :278-285