Abstract
Under the environment of Internet of things, agricultural network information service is open and resource sharing. In order to improve the intelligence of agricultural network information service under the environment of Internet of things, an agricultural network information resource sharing system based on Internet of things is constructed. The overall design description and function modularization analysis of agricultural network information resource sharing system are carried out. The system design includes agricultural network information service resource retrieval module, agricultural network information resource integration processing module, bus control module, resource information fusion module, program loading and compilation module and human-computer interaction module. The bottom module of agricultural network information resource sharing system is designed by using B/S architecture protocol and bus server system, the retrieval of massive agricultural network information service resources is designed based on Internet of things technology, the information dispatching network center of agricultural network information service resources is established under the environment of Internet of things technology, and the Internet of things networking design of agricultural network information resource sharing system is carried out by using network networking methods such as ZigBee and GPRS. The process management and file configuration are carried out under MVB bus control protocol, and the software development and design of agricultural network information resource sharing system are realized under embedded ARM environment. The test results show that the information resource sharing system of agricultural network based on Internet of things technology has good human-computer interaction and resource scheduling, and the execution time cost is small and the reliability is high.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Huang, H., Xiaotian, G.E., Chen, X.: Density clustering method based on complex learning classification system. J. Comput. Appl. 37(11), 3207–3211 (2017)
Ji, Y., Li, Y., Shi, C.: Aspect rating prediction based on heterogeneous network and topic model. J. Comput. Appl. 37(11), 3201–3206 (2017)
Xiao, K., Du, Z., Yang, L.: An embedded wireless sensor system for multi-service agricultural information acquisition. Sens. Lett. 15(11), 907–914 (2017)
Blanco, A.C., Tamondong, A., Perez, A.M., et al.: Nationwide natural resource inventory of the Philippines using LiDAR: strategies, progress, and challenges. ISPRS J. Photogram. Remote Sens. XL I(B6), 105–109 (2018)
Slimeni, F., Scheers, B., Nir, V.L., et al.: Learning multi-channel power allocation against smart jammer in cognitive radio networks. In: Proceedings of the 2016 International Conference on Military Communications and Information Systems, Piscataway, NJ, pp. 1–7. IEEE (2016)
Eski, İ., Kuş, Z.A.: Control of unmanned agricultural vehicles using neural network-based control system. Neural Comput. Appl. 31, 583–595 (2019). https://doi.org/10.1007/s00521-017-3026-4
Han, B., Li, Y.: Optimization method for reducing network loss of dc distribution system with distributed resource. Photon. Netw. Commun. 37(2), 233–242 (2018). https://doi.org/10.1007/s11107-018-0805-5
Mougin, C., et al.: BRC4Env, a network of Biological Resource Centres for research in environmental and agricultural sciences. Environ. Sci. Pollut. Res. 25(34), 33849–33857 (2018). https://doi.org/10.1007/s11356-018-1973-7
Shi, J., Feng, Z., Liu, J.: Design and experiment of high precision forest resource investigation system based on UAV remote sensing images. Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agric. Eng. 33(11), 82–90 (2017)
Xing, X., Shang, Y., Zhao, R., Li, Z.: Pheromone updating strategy of ant colony algorithm for multi-objective test case prioritization. J. Comput. Appl. 36(9), 2497–2502 (2016)
Zhang, H., Shao, Z., Zhang, Z., et al.: Regulation system of CO2 in facilities based on wireless sensor network. Nongye Jixie Xuebao/Trans. Chin. Soc. Agric. Mach. 48(3), 325–331, 360 (2017)
Parsley, S.: Accessing good health information and resources. Commun. Eye Health 30(97), 15–17 (2017)
Zhang, X.-B., Li, M., Wang, H., et al.: Location information acquisition and sharing application design in national census of Chinese medicine resources. Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China J. Chin. Materia Medica, 42(22), 4271–4276 (2017)
Wang, L.: Optimization process of compiling and researching archives in universities under the background of information sharing. Int. Technol. Manag. 6, 36–38 (2017)
Wang, Y., Li, C., Cui, Y., et al.: Construction of PaaS platform based on Docker. Comput. Syst. Appl. 5(3), 72–77 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Wang, K. (2020). Design of Agricultural Network Information Resource Sharing System Based on Internet of Things. In: Zhang, YD., Wang, SH., Liu, S. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-030-51100-5_25
Download citation
DOI: https://doi.org/10.1007/978-3-030-51100-5_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-51099-2
Online ISBN: 978-3-030-51100-5
eBook Packages: Computer ScienceComputer Science (R0)