IOT and Agriculture Data Analysis for Smart Farm

Authors

  • Sowmyashree S Dept. of Computer Science, East West institute Of Technology, Bangalore,India
  • Arun Biradar Dept. of Computer Science and Technology, East West Institute ofTechnology, Bangalore,India

Keywords:

Smart farming, IOT(Internet Of Things), wireless sensor network, wisekar, Smartphone

Abstract

IOT plays a important role in agriculture. IOT uses sensors which are capable of providing information about agriculture field. Smart farming is managing farms using technologies like IOT to increase the quantity and quality of products by improving yields of crops. Wireless sensor network are being proposed for watering of crops to increase the productivity and gives the new direction for research in agriculture and farming through a mobile application in a smartphone. Wisekar is used to detect the disease in crops and report the type of crop disease to the farmer. As Farmer is the backbone of our country this work help the farmers handle various operation wirelessly through mobile applications and providing smart agriculture to farmers.

References

[1] Muangprathub,J.,Boonnam,N.,Kajornkasirat,S.,Nillaor,p.,2018.IOT and agriculture data analysis for smart farm. Comput. Electron. Agric.156,467-474.https://doi.org/10.1016/j.compag.2018.12.011.

[2] Kamilaris, A., Kartakoullis, A., Prenafeta-Bold, F.X., 2017. A review on the practice of big dataanalysis in agriculture. Comput. Electron. Agric. 143, 23–37.

[3]Xian, K., 2017. Internet of things online monitoring system based on cloud computing. Int. Jo. Online Eng. (iJOE) 13 (9), 123–131. https://doi.org/10.3991/ijoe.v13i09.7591.

[4] Capello, F., Toja, M., Trapani, N., 2016. A real-time monitoring service based on industrialinternet of things to manage agrifood logistics. In: 6th International Conference onInformation Systems, Logistics and Supply Chain, pp. 1–8

[5]Sarangi, S., Umadikar, J., Kar, S., 2016. Automation of agriculture support systems using Wisekar: case study of a crop-disease advisory service. Comput. Electron. Agric. 122, 200–210. https://doi.org/10.1016/j.compag.2016.01.009

[6] Ojha, T., Misra, S., Raghuwanshi, N.S., 2015. Wireless sensor networks for agriculture: the state-of-the-art in practice and future challenges. Comput. Electron. Agric. 118, 66–84.

[7]Luan, Q., Fang, X., Ye, C., Liu, Y., 2015. An integrated service system for agricultural droughtmonitoring and forecasting and irrigation amount forecasting. In: 23rd InternationalConference on Geoinformatics. IEEE, pp. 1–7.

[8] Lukas, Tanumihardja, W.A., Gunawan, E., 2015. On the application of IoT: monitoring of troughs water level using WSN. In: Conference on Wireless Sensors (ICWiSe). IEEE, pp. 58–62. https://doi.org/10.1109/ICWISE.2015.738035.

[9] Kanoun, O., Khriji, S., El Houssaini, D., Viehweger, C., Jmal, M.W., Abid, M., 2014. Precision irrigation based on wireless sensor network. IET Sci. Meas. Technol. 8, 98–106. https://doi.org/10.1049/iet-smt.2013.0137

[10] Pang, Z., Chen, Q., Han, W., Zheng, L., 2015. Value-centric design of the internet-of things solution for food supply Chain: value creation, sensor portfolio and information fusion. Inform. Syst. Front. 17, 289–319. https://doi.org/10.1007/s10796-012-9374-9.

[11] UCI Machine Learning Repository, 2015. (last visited: 09.09.15).

[12] Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M., 2015. Internet of things: a survey on enabling technologies, protocols and applications. IEEE Commun. Surv. Tutorials. http://dx.doi.org/10.1109/COMST.2015.2444095.

[13] Chen, K.T., Zhang, H.H., Wu, T.T., Hu, J., Zhai, C.Y., Wang, D., 2014. Design of monitoring system for multilayer soil temperature and moisture based on WSN. In: International Conference on Wireless Communication and Sensor Network (WCSN). IEEE, Wuhan, pp. 425–430. https://doi.org/10.1109/WCSN.2014.9.

[14] Hashmi, N., Mazlan, S., Aziz, M.A., Salleh, A., Jaafar, A., Mohamad,N 2015. Agriculture monitoring system: a study. J. Teknologi 77, 53–59. https://doi.org/10.11113/jt.v77.

[15] Kaewmard, N., Saiyod, S., 2014. Sensor data collection and irrigation control on vegetable cropusing smart phone and wireless sensor networks for smart farm. In: Conference on WirelessSensors (ICWiSE). IEEE, pp. 106–112.

[16]Surendrababu, V., Sumathi, C., Umapathy, E., 2014. Detection of rice leaf diseasesusing chaos and fractal dimension in image processing. Int. J. Comput. Sci. Eng.(IJCSE) 6 (1), 69–74.

[17]Adamala, S., Raghuwanshi, N.S., Mishra, A., 2014. Development of surface irrigationsystems design and evaluation software (SIDES). Comput. Electron. Agric. 100,100–109.

[18] Anandaraja, N., Sankri, S., Sriram, N., Venkatachalam, R., 2013. TNAU agri techportal: content design and validation. CSI Commun., 21–25.

[19] Surendrababu, V., Sumathi, C., Umapathy, E., 2014. Detection of rice leaf diseasesusing chaos and fractal dimension in image processing. Int. J. Comput. Sci. Eng.(IJCSE) 6 (1), 69–74.

[20] Sarangi, S., Kar, S., 2013. Wireless sensor knowledge archive. In: IEEE International Conference on Electronics, Computing and Communication Technology (CONECCT), pp. 1–6.

[21] Amaral, J.P., Oliveira, L.M.L., Rodrigues, J.J.P.C., Han, G., Shu, L., 2014. Policy and network-based intrusion detection system for IPv6-enabled wireless sensor networks. In: Proceedings of International Communication on Communications, Sydney, Australia, pp. 1796–1801.

[22] Barcelo-Ordinas, J.M., Chanet, J.P., Hou, K.M., García-Vidal, J., 2013. A survey ofwireless sensor technologies applied to precision agriculture. In: Stafford, J.(Ed.), Precision Agriculture’13. Wageningen Academic Publishers, pp. 801–808.

[23] Bhargava, K., Kashyap, A., Gonsalves, T.A., 2014. Wireless sensor network based advisory system for apple scab prevention. In: Proceedings of National Conference on Communications, Kanpur, India, pp. 1–6.

[24] Bhave, A.G., Mishra, A., Raghuwanshi, N.S., 2013. A combined bottom-up and top-down approach for assessment of climate change adaptation options. J. Hydrol. http://dx.doi.org/10.1016/j.jhydrol.2013.08.039.

[25] Goumopoulos, C., O’Flynn, B., Kameas, A., 2014. Automated zone-specific irrigationwith wireless sensor/actuator network and adaptable decision support.Comput. Electron. Agric. 105, 20–33

[26] Dong, X., Vuran, M.C., Irmak, S., 2013. Autonomous precision agriculture throughintegration of wireless underground sensor networks with center pivotirrigation systems. Ad Hoc Netw. 11 (7), 1975–1987.

[27] Bhattacharjee, S., Roy, P., Ghosh, S., Misra, S., Obaidat, M.S., 2012. Wireless sensornetwork-based fire detection, alarming, monitoring and prevention system forBord-and-Pillar coal mines. J. Syst. Softw. 85 (3), 571–581.

[28] Misra, S., Jain, A., 2011. Policy controlled self-configuration in unattended wirelesssensor networks. J. Netw. Comput. Appl. 34 (5), 1530–1544.

[29] Fukatsu, T., Kiura, T., Hirafuji, M., 2011. A web-based sensor network system withdistributed data processing approach via web application. Comput. Stand.Interfaces 33 (6), 565–573

[30]Greenwood, D.J., Zhang, K., Hilton, H.W., Thompson, A.J., 2010. Opportunities forimproving irrigation efficiency with quantitative models, soil water sensors andwireless technology. J. Agric. Sci. 148, 1–16

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Published

2025-11-26

How to Cite

[1]
S. S and A. Biradar, “IOT and Agriculture Data Analysis for Smart Farm”, Int. J. Comp. Sci. Eng., vol. 7, no. 15, pp. 344–348, Nov. 2025.

Issue

Vol. 7 No. 15 (2019): IJCSE Special Issue May Edition

Section

Research Article

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