Abstract
The agriculture sector is facing major challenges to enhance production in a situation of dwindling natural resources. The growing demand for agricultural products, however, also offers opportunities for producers to sustain, improve productivity and reduce waste in the supply chain. Recent advancements in information and communication technologies (ICT) show promise in addressing these challenges. This paper proposes food security architecture for agricultural supply chain efficiency using ICT tools such as Internet of Things and Big Data analytics. To avoid loss in agriculture, a food security architecture is developed through Smart Agribusiness Supply Chain Management System is developed in this paper. This can result in uplifting the livelihoods of the rural poor through the enhancement of agribusiness.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Savvas, A.: Farming industry must embrace the Internet of Things to “grow enough food”. http://www.techworld.com/news/big-data/farming-industry-must-embrace-internet-of-things-3596905/ (2015)
Ashford, W.: IoT could be key to farming, says Beecham Research. http://www.computerweekly.com/news/2240239484/IoT-could-be-key-to-farming-says-Beecham-Research (2015)
Sørensen, C.G., Fountas, S., Nash, E., Pesonen, L., Bochtis, D., Pedersen, S.M., Basso, B., Blackmore, S.B.: Conceptual model of a future farm management information system. Comput. Electron. Agric. 72(1), 37–47 (2010)
Thessler, S., Kooistra, L., Teye, F., Huitu, H., Bregt, A.: Geosensors to support crop production: current applications and user requirements. Sensors. 11, 6656–6684 (2011)
Grosicki, E., Abed-Meraim, K., Hua, K.Y.: A weighted linear prediction method for near-field source localization. IEEE Trans. Signal Process. 53(10), 3651–3660 (2005)
Lavate, T.B., Kokate, V.K., Sapkal, A.M.: Performance analysis of MUSIC and ESPRIT DOA estimation algorithms for adaptive array smart antenna in mobile communication. Int. J. Comput. Netw. 2(3), 152–158 (2010)
Laurikkala, J., Juhola, M., Kentala, E.: Informal identification of outliers in medical data. In: The Fifth International Workshop on Intelligent Data Analysis in Medicine and Pharmacolog (2000)
Guha, S., Rastogi, R., Shim, K.: CURE: an efficient clustering algorithm for large databases. In: Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data, vol. 27, issue: 2, pp. 73–84 (1998)
Öhgren, A.: Ontology development and evolution: selected approaches for small-scale _application contexts. Tech. Rep. 2004, 7 (2004). School of Engineering, Jönköping University, _JTH, Computer and Electrical Engineering
Jenny, G., Christel, C., Sonesson, U., van Robert, O., Alexandre, M.: Global food losses and food waste. Food and Agriculture Organization of the United Nations Rome (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Parvin, S. et al. (2019). Smart Food Security System Using IoT and Big Data Analytics. In: Latifi, S. (eds) 16th International Conference on Information Technology-New Generations (ITNG 2019). Advances in Intelligent Systems and Computing, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-030-14070-0_35
Download citation
DOI: https://doi.org/10.1007/978-3-030-14070-0_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-14069-4
Online ISBN: 978-3-030-14070-0
eBook Packages: EngineeringEngineering (R0)