research-article

Intelligent Control and Information Management System for Plant Growth Cabinet Based on Internet of Things

Authors:

ICMSS '17: Proceedings of the 2017 International Conference on Management Engineering, Software Engineering and Service Sciences

Pages 246 - 249

https://doi.org/10.1145/3034950.3034970

Published: 14 January 2017 Publication History

Get Access

Abstract

plant growth cabinet (PGC) is a closed plant growth environment that can provide temperature, humidity and other factors required in the process of plant growth and development. In this study, we propose an intelligent control and information management system based on Internet of Things (IoT). Every IOT system has three layers that are the sensing layer, the transmission layer, and the application layer. We implement the sensing layer through the Android subsystem software design with environmental parameters. The Android application software was built to realize the many functions such as the plants' morphological data collection, display of the environmental information in the PGC, and monitor ship of the plant growth process in real time, make the reasonable regulation of the control node meanwhile. The IoT transmission layer communicates in WiFi wireless way. In the application layer, the vegetable maturity could be forecast by fusing the images information through two artificial neural networks on the IoT server. Moreover, the several other feature functions, including remotely monitoring the PGC and the posting the environmental data, pictures and videos of the plant in the SQL database, are available for the user to manage the PGC. The experimental results indicate that the control strategy in IoT sensing layer and maturity prediction model in IoT application layer are of high-efficiency. The IoT system design is effective to provide an appropriate growth environment guidance and management for the plant growth.

References

[1]

ui, S. G., Han, S. L., Wu, X. L. and Liang, F. 2014. The design of Hardware of Smart Plant Growth Cabinet. Applied Mechanics and Materials, (577): 624--627.

Google Scholar

[2]

Wu, X. l., Cui, S. G., Zi, H., Wei, M. Q., Zhao, L. and Liang, F. 2015.Temperature control device of the nutrient solution for the LED intelligent plant growth cabinet. Journal of Chinese Agriculture Mechanization, 36(3):106--109.

Google Scholar

[3]

Cui, S. G., Dong, J. L., Liang, F., Wu, X. L. and Tian, L. G. 2015. The design of intelligent monitoring system for the plant growth cabinet based on the internet of things Android platform. Journal of Chinese Agriculture Mechanization, 36(3):110--113.

Google Scholar

[4]

Liang F, Dong J L, Cui S G, Wu X-L, Xie J. J. 2015, Software design of plant growth cabinet based on the internet of things. Research of Agricultural Modernization, 36(4): 716--720.

Google Scholar

[5]

LIANG Fan, YANG Lili, CUI Shi-gang. 2015. Application of Image Processing Technology in the Monitoring of Hydroponic Vegetable Growth, Hubei Agricultural Sciences, 2015(17):4288--4291

Google Scholar

[6]

LIANG Fan, YANG Lili, CUI Shi-gang. 2015. Vision detection method of Rapeseed maturity level based on Artificial Neural Network. Jiangsu Agricultural Sciences, 2015,43(8):403--405

Google Scholar

[7]

Liang, F., et al. Detection method of vegetable maturity based on neural network and Bayesian information fusions. in proceeding of Sixth International Conference on Electronics and Information Engineering. 2015. International Society for Optics and Photonics.

Google Scholar

[8]

Liang, F., et al. Design of Intelligent Measure and Control Software of Plant Growth Cabinet Based on Android System. In Applied Mechanics and Materials. 2015. Trans Tech Publ.

Google Scholar

[9]

Nandi, C.S., Tutu, B. & Kelly, C. A Machine Vision-Based Maturity Prediction System for Sorting Harvested Mangoes. IEEE Trans. Instrum. Meas. 2014, 63, 1722--1730.

Google Scholar

[10]

Shahriar, M., Fleming, I. S., Sarraf, H. S. and Hequet, E.(2013). A machine vision system to estimate cotton fiber maturity from longitudinal view using a transfer learning approach. Machine Vision and Applications, 24(8):1661--1683.

Digital Library

Google Scholar

[11]

Wu, C. Y., Zhang, W. Z., Ouyang, Q. and Hong, T. S. (2007). BP neural network model for the measurement of the leaf area of litchi. Transactions of the CSAE, 23(7): 166--169.

Google Scholar

[12]

Zhang, C. L., Fang J. L. and Pan W. (2001). Automated Identification of Tomato Maturation Using Multilayer Feedforward Neural Network With Genetic Algorithms (GA). Transactions of the CSAE, 17(3): 153--156.

Google Scholar

Cited By

View all

Chang MShen CMaheshwari ADanielescu AYao L(2022)Patterns and Opportunities for the Design of Human-Plant InteractionProceedings of the 2022 ACM Designing Interactive Systems Conference10.1145/3532106.3533555(925-948)Online publication date: 13-Jun-2022
https://dl.acm.org/doi/10.1145/3532106.3533555
P SC YH M(2019)A Controlled Environment Agriculture with Hydroponics: Variants, Parameters, Methodologies and Challenges for Smart Farming2019 Fifteenth International Conference on Information Processing (ICINPRO)10.1109/ICInPro47689.2019.9092043(1-8)Online publication date: Dec-2019
https://doi.org/10.1109/ICInPro47689.2019.9092043
Ali FBarnes TGarcia DHawthorne EPérez-Quiñones M(2018)Experiences in Teaching the Internet of Things CoursesProceedings of the 49th ACM Technical Symposium on Computer Science Education10.1145/3159450.3159549(378-383)Online publication date: 21-Feb-2018
https://dl.acm.org/doi/10.1145/3159450.3159549

Recommendations

Security of the Internet of Things: perspectives and challenges

Internet of Things (IoT) is playing a more and more important role after its showing up, it covers from traditional equipment to general household objects such as WSNs and RFID. With the great potential of IoT, there come all kinds of challenges. This ...
Perception layer security in Internet of Things
Abstract
Internet of Things (IoT) is one of the rising innovations of the current era that has largely attracted both the industry and the academia. Life without the IoT is entirely indispensable. To dispel the doubts, if any, about the widespread ...
Highlights
- WSNs, RFID and RSN are the key enabling technologies of IoT.
- Security at perception layer followed by IoT security requirements.
- Taxonomic classification of the core enabling technologies on perception layer.
- Security ...
Security of the Internet of Things: An Overview
ICCIS '16: Proceedings of the 2016 International Conference on Communication and Information Systems

Over the last several decades, the pace of progress of Internet technology has undergone rapid developments, especially in the Internet of Things (IoT). The recent advancements that have changed the way people live are called Smart devices, which are ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

ICMSS '17: Proceedings of the 2017 International Conference on Management Engineering, Software Engineering and Service Sciences

January 2017

339 pages

ISBN:9781450348348

DOI:10.1145/3034950

Editor:
Yulin Wang

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

Wuhan Univ.: Wuhan University, China

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 January 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Funding Sources

Student's Platform for Innovation and Entrepreneurship Training Program
Tianjin Sino-German University of Applied Science College funding
Chinese National Science Foundation Grant
Tianjin Natural Foundation Grant in China

Conference

ICMSS '17

ICMSS '17: 2017 International Conference on Management Engineering, Software Engineering and Service Sciences

January 14 - 16, 2017

Wuhan, China

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
189
Total Downloads

Downloads (Last 12 months)18
Downloads (Last 6 weeks)1

Reflects downloads up to 19 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Chang MShen CMaheshwari ADanielescu AYao L(2022)Patterns and Opportunities for the Design of Human-Plant InteractionProceedings of the 2022 ACM Designing Interactive Systems Conference10.1145/3532106.3533555(925-948)Online publication date: 13-Jun-2022
https://dl.acm.org/doi/10.1145/3532106.3533555
P SC YH M(2019)A Controlled Environment Agriculture with Hydroponics: Variants, Parameters, Methodologies and Challenges for Smart Farming2019 Fifteenth International Conference on Information Processing (ICINPRO)10.1109/ICInPro47689.2019.9092043(1-8)Online publication date: Dec-2019
https://doi.org/10.1109/ICInPro47689.2019.9092043
Ali FBarnes TGarcia DHawthorne EPérez-Quiñones M(2018)Experiences in Teaching the Internet of Things CoursesProceedings of the 49th ACM Technical Symposium on Computer Science Education10.1145/3159450.3159549(378-383)Online publication date: 21-Feb-2018
https://dl.acm.org/doi/10.1145/3159450.3159549

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Recommendations

Security of the Internet of Things: perspectives and challenges

Perception layer security in Internet of Things

Security of the Internet of Things: An Overview