Abstract
The agricultural industry must adapt to todays market by using resources efficiently and respecting the environment. This paper presents the analysis of data and the application of the Internet of Things (IoT) and advanced computing technologies in a real-world scenario. The proposed model monitors environmental conditions on a farm through a series of deployed sensors and the most outstanding feature of this model is the robust data transmission it offers. The analysis of information collected by the sensors is measured using state-of-the-art computing technology that helps reduce data traffic between the IoT layers and the cloud. The designed methodology integrates sensors and a state-of-the-art computing platform for data mining. This small study forms the basis for a future test with several operations at the same time.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
European Commission Horizon 2050 (2019). https://ec.europa.eu/commission/presscorner/detail/en/IP_19_6691
Agrawal, H., Prieto, J., Ramos, C., Corchado, J.M.: Smart feeding in farming through IoT in silos. In: ISTA 2016. AISC, vol. 530, pp. 355–366. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47952-1_28
Ai, Y., Peng, M., Zhang, K.: Edge computing technologies for Internet of Things: a primer. Digital Commun. Netwo 4(2), 77–86 (2018). https://www.sciencedirect.com/science/article/pii/S2352864817301335
Alonso, R.S., Sittón-Candanedo, I., Casado-Vara, R., Prieto, J., Corchado, J.M.: Deep reinforcement learning for the management of software-defined networks and network function virtualization in an edge-IoT architecture. Sustainability 12(14), 5706 (2020)
Alonso, R.S., Sittón-Candanedo, I., García, Ó., Prieto, J., Rodríguez-González, S.: An intelligent edge-IOT platform for monitoring livestock and crops in a dairy farming scenario. Ad Hoc Netw. 98, 102047 (2020)
Alonso, R.S., Sittón-Candanedo, I., Rodríguez-González, S., García, Ó., Prieto, J.: A survey on software-defined networks and edge computing over IoT. In: De la Prieta, F., et al. (eds.) PAAMS 2019. CCIS, vol. 1047, pp. 289–301. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-24299-2_25
Balafoutis, A.T.: Smart farming technologies – description, taxonomy and economic impact. In: Pedersen, S.M., Lind, K.M. (eds.) Precision Agriculture: Technology and Economic Perspectives. PPA, pp. 21–77. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68715-5_2
Cambra, C., Sendra, S., Lloret, J., Lacuesta, R.: Smart system for bicarbonate control in irrigation for hydroponic precision farming. Sensors 18(5), 1333 (2018)
Cao, Q., Banerjee, R., Gupta, S., Li, J., Zhou, W., Jeyachandra, B., et al.: Data driven production forecasting using machine learning. In: SPE Argentina Exploration and Production of Unconventional Resources Symposium. Society of Petroleum Engineers (2016)
Casado-Vara, R., Martin-del Rey, A., Affes, S., Prieto, J., Corchado, J.M.: IoT network slicing on virtual layers of homogeneous data for improved algorithm operation in smart buildings. Future Gener. Comput. Syst. 102, 965–977 (2020)
Chamoso, P., González-Briones, A., De La Prieta, F., Venyagamoorthy, G.K., Corchado, J.M.: Smart city as a distributed platform: toward a system for citizen-oriented management. Comput. Commun. 152, 323–332 (2020)
Chien, Y.R., Chen, Y.X.: An RFID-based smart nest box: an experimental study of laying performance and behavior of individual hens. Sensors 18(3), 859 (2018)
Corchado, J.M., et al.: Deepint.net: a rapid deployment platform for smart territories. Sensors 21(1), 236 (2021)
Edge Computing Consortium, Alliance of industrial internet: edge computing reference architecture 2.0. Technical report, Edge Computing Consortium, November 2017. http://en.ecconsortium.net/Uploads/file/20180328/1522232376480704.pdf
ElMasry, G., Mandour, N., Al-Rejaie, S., Belin, E., Rousseau, D.: Recent applications of multispectral imaging in seed phenotyping and quality monitoring–an overview. Sensors 19(5), 1090 (2019)
FAR-EDGE Project: FAR-EDGE Project H2020, November 2017. http://far-edge.eu/
Fleming, K., Waweru, P., Wambua, M., Ondula, E., Samuel, L.: Toward quantified small-scale farms in Africa. IEEE Internet Comput. 20(3), 63–67 (2016)
Gardner, B.: European Agriculture: Policies, Production, and Trade. Psychology Press, Routledge (1996)
González Bedia, M., Corchado Rodríguez, J.M., et al.: A planning strategy based on variational calculus for deliberative agents. Comput. Inf. Syst. 9, 2–13 (2002)
Gupta, M.C.: Environmental management and its impact on the operations function. Int. J. Oper. Prod. Manage. 15(8) (1995)
Handfield, R.B., Walton, S.V., Seegers, L.K., Melnyk, S.A.: ‘Green’ value chain practices in the furniture industry. J. Oper. Manage. 15(4), 293–315 (1997)
Humphreys, P., McIvor, R., Chan, F.: Using case-based reasoning to evaluate supplier environmental management performance. Expert Syst. Appl. 25(2), 141–153 (2003)
Ichimura, M., et al.: Eco-efficiency indicators: measuring resource-use efficiency and the impact of economic activities on the environment. ESCAP, Bangkok (2009)
INTEL-SAP: IoT joint reference architecture from Intel and SAP. Technical report, INTEL-SAP, November 2018. https://www.intel.com/content/dam/www/public/us/en/documents/reference-architectures/sap-iot-reference-architecture.pdf
Jia, W., Liang, G., Tian, H., Sun, J., Wan, C.: Electronic nose-based technique for rapid detection and recognition of moldy apples. Sensors 19(7), 1526 (2019)
Jones, J.W., et al.: Toward a new generation of agricultural system data, models, and knowledge products: state of agricultural systems science. Agric. Syst. 155, 269–288 (2017)
Khan, R., Khan, S.U., Zaheer, R., Khan, S.: Future internet: the internet of things architecture, possible applications and key challenges. In: 2012 10th International Conference on Frontiers of Information Technology, pp. 257–260. IEEE (2012)
Machek, O., Špička, J.: Productivity and profitability of the Czech agricultural sector after the economic crisis. WSEAS Trans. Bus. Econ. 11, 700–706 (2014)
McBratney, A., Whelan, B., Ancev, T., Bouma, J.: Future directions of precision agriculture. Precis. Agric. 6(1), 7–23 (2005)
Park, J., Choi, J.H., Lee, Y.J., Min, O.: A layered features analysis in smart farm environments. In: Proceedings of the International Conference on Big Data and Internet of Thing, pp. 169–173, BDIOT 2017. ACM, New York (2017)
Pedersen, S.M., Lind, K.M. (eds.): Precision Agriculture: Technology and Economic Perspectives. PPA, Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68715-5
Pérez-Pons, M.E., González-Briones, A., Corchado, J.M.: Towards financial valuation in data-driven companies. Orient. J. Comput. Sci. Technol. 12(2), 28–33 (2019)
Pérez-Pons, M.E., Plaza-Hernández, M., Alonso, R.S., Parra-Domínguez, J., Prieto, J.: Increasing profitability and monitoring environmental performance: a case study in the agri-food industry through an edge-IoT platform. Sustainability 13(1), 283 (2021)
Pérez-Pons, M.E., Parra-Domínguez, J., Chamoso, P., Plaza, M., Alonso, R.: Efficiency, profitability and productivity: technological applications in the agricultural sector. ADCAIJ: Adv. Distrib. Comput. Artif. Intell. J. 9(4) (2020)
Popović, T., Latinović, N., Pešić, A., Zečević, Ž, Krstajić, B., Djukanović, S.: Architecting an IoT-enabled platform for precision agriculture and ecological monitoring: a case study. Comput. Electron. Agric. 140, 255–265 (2017)
Potamitis, I., Rigakis, I., Tatlas, N.A., Potirakis, S.: In-vivo vibroacoustic surveillance of trees in the context of the IoT. Sensors 19(6), 1366 (2019)
Reardon, T., Barrett, C.B., Berdegué, J.A., Swinnen, J.F.: Agrifood industry transformation and small farmers in developing countries. World Dev. 37(11), 1717–1727 (2009)
Ryu, M., Yun, J., Miao, T., Ahn, I.Y., Choi, S.C., Kim, J.: Design and implementation of a connected farm for smart farming system. In: 2015 IEEE SENSORS, pp. 1–4. IEEE (2015)
Sánchez-Iborra, R., Sánchez-Gómez, J., Skarmeta, A.: Evolving IoT networks by the confluence of MEC and LP-WAN paradigms. Future Gener. Comput. Syst. 88, 199–208 (2018)
Schmidheiny, S., Timberlake, L.: Changing Course: A Global Business Perspective on Development and the Environment, vol. 1. MIT Press, Cambridge (1992)
Sisinni, E., Saifullah, A., Han, S., Jennehag, U., Gidlund, M.: Industrial internet of things: challenges, opportunities, and directions. IEEE Trans. Ind. Inform. 14(11), 4724–4734 (2018)
Sittón-Candanedo, I., Alonso, R.S., Corchado, J.M., Rodríguez-González, S., Casado-Vara, R.: A review of edge computing reference architectures and a new global edge proposal. Future Gener. Comput. Syst. 99, 278–294 (2019)
Sittón-Candanedo, I., Alonso, R.S., García, Ó., Gil, A.B., Rodríguez-González, S.: A review on edge computing in smart energy by means of a systematic mapping study. Electronics 9(1), 48 (2020)
Suma, N., Samson, S.R., Saranya, S., Shanmugapriya, G., Subhashri, R.: IoT based smart agriculture monitoring system. Int. J. Recent Innov. Trends Comput. Commun. 5(2), 177–181 (2017)
Tseng, M., Canaran, T.E., Canaran, L.: Introduction to edge computing in IIoT. Technical report, Industrial Internet Consortium, November 2018. https://www.iiconsortium.org/IISF.htm
Wolfert, S., Ge, L., Verdouw, C., Bogaardt, M.J.: Big data in smart farming-a review. Agric. Syst. 153, 69–80 (2017)
Wu, C., Toosi, A.N., Buyya, R., Ramamohanarao, K.: Hedonic pricing of cloud computing services. IEEE Trans. Cloud Comput. 9(1), 182–196 (2018)
Yigitcanlar, T., Butler, L., Windle, E., Desouza, K.C., Mehmood, R., Corchado, J.M.: Can building “artificially intelligent cities” safeguard humanity from natural disasters, pandemics, and other catastrophes? An urban scholar’s perspective. Sensors 20(10), 2988 (2020)
Yu, W., et al.: A survey on the edge computing for the internet of things. IEEE Access 6, 6900–6919 (2017)
Acknowledgments
This research was partially Supported by the project “Computación cuántica, virtualización de red, edge computing y registro distribuido para la inteligencia artificial del futuro”, Reference: CCTT3/20/SA/0001, financed by Institute for Business Competitiveness of Castilla y León, and the European Regional Development Fund (FEDER). Authors would like to give a special thanks to Rancho Guareña Hermanos Olea Losa, S.L. (Castrillo de la Guareña, Zamora, Spain) for their collaboration during the implementation and testing of the platform.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Pérez-Pons, M.E., Alonso, R.S., Parra-Domínguez, J., Plaza-Hernández, M., Trabelsi, S. (2022). RETRACTED CHAPTER: An Edge-IoT Architecture and Regression Techniques Applied to an Agriculture Industry Scenario. In: Corchado, J.M., Trabelsi, S. (eds) Sustainable Smart Cities and Territories. SSCTIC 2021. Lecture Notes in Networks and Systems, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-030-78901-5_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-78901-5_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-78900-8
Online ISBN: 978-3-030-78901-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)