Abstract
India has larger agricultural lands but it does not cross the world’s standard in plant productivity. There are many reasons for low plant yield. To improve the productivity, technological support system for agriculture is essential. This paper presents an integrated farm monitoring system by using Smartphone application and Internet of Things. Using this system, farmers can remotely monitor farm for soil moisture, leaf wetness duration, pH level in the soil, temperature and humidity in the environment. The system quickly analyses the weather and soil conditions in a particular area where the plant is present and gives new insights to manipulate the decision making. The system is deployed and tested in fields of Islampur, Maharashtra. The proposed tool is cost effective and productive system for farmers.
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Rao BS, Rao DKS, Ome MN (2016) Internet of Things (IoT) based weather monitoring system. Int J Adv Res Comput Commun Eng 5(9), pp 312–319
Keswani B, Mohapatra AG, Mohanty A, Khanna A, Rodrigues JJ, Gupta D, de Albuquerque VHC (2018) Adapting weather conditions based IoT enabled smart irrigation technique in precision agriculture mechanisms. Neural Comput Applic 31:1–16
Ananthi N, Divya J, Divya M, Janani V (2017) IoT based smart soil monitoring system for agricultural production. In: Technological innovations in ICT for agriculture and rural development. IEEE, Chennai, India, pp 209–214
Rao RN, Sridhar B (2018) IoT based smart crop-field monitoring and automation irrigation system. In: 2018 2nd International Conference on inventive systems and control. IEEE, Coimbatore, India, pp 478–483
Chan SK, Bindlish R, O’Neill PE, Njoku E, Jackson T, Colliander A et al (2016) Assessment of the SMAP passive soil moisture product. IEEE Trans Geosci Remote Sens 54(8):4994–5007
Gultom JH, Harsono M, Khameswara TD, Santoso H (2017) Smart IoT water sprinkle and monitoring system for chili plant. In: Electrical engineering and computer science. IEEE, Palembang, pp 212–216
Amrutha A, Lekha R, Sreedevi A (2016) Automatic soil nutrient detection and fertilizer dispensary system. In: Robotics: current trends and future challenges (RCTFC). IEEE, Thanjavur, India, pp 1–5
Singh V, Misra AK (2017) Detection of plant leaf diseases using image segmentation and soft computing techniques. Inf Process Agric 4(1):41–49
Francis J, Anoop BK (2016) Identification of leaf diseases in pepper plants using soft computing techniques. In: Emerging devices and smart systems. IEEE, Namakkal, pp 168–173
Mwebaze E, Owomugisha G (2016) Machine learning for plant disease incidence and severity measurements from leaf images. In: Machine learning and applications (ICMLA), 15th IEEE international conference. IEEE, Anaheim, pp 158–163
Thorat A, Kumari S, Valakunde ND (2017) An IoT based smart solution for leaf disease detection. In: Big data, IoT and data science. IEEE, Pune, India, pp 193–198
Zhang S, Chen X, Wang S (2014) Research on the monitoring system of wheat diseases, pests and weeds based on IoT. In: Computer Science & Education (ICCSE), 9th international conference. IEEE, Vancouver, BC, pp 981–985
Prathibha SR, Hongal A, Jyothi MP (2017) IoT based monitoring system in smart agriculture. In: Recent advances in electronics and communication technology. IEEE, Bangalore, India, pp 81–84
Patil SS, Thorat SA (2016) Early detection of grapes diseases using machine learning and IoT. In: Cognitive Computing and Information Processing (CCIP). IEEE, Mysore, India, pp 1–5
Bing F (2016) The research of IoT of agriculture based on three layers architecture. In: Cloud Computing and Internet of Things (CCIoT). IEEE, Dalian, pp 162–165
Venkatesan R, Tamilvanan A (2017) A sustainable agricultural system using IoT. In: Communication and Signal Processing (ICCSP). IEEE, Chennai, India, pp 0763–0767
Santos EA, Sentelhas PC, Gillespie TJ, Lulu J (2008) Performance of cylindrical leaf wetness duration sensors in a tropical climate condition. Sci Agric 65(SPE):1–9
Kurniawan AP, Jati AN, Azmi F (2017) Weather prediction based on fuzzy logic algorithm for supporting general farming automation system. In: Instrumentation, Control, and Automation (ICA). IEEE, Yogyakarta, pp 152–157
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Patil, M.A., Adamuthe, A.C., Umbarkar, A.J. (2020). Smartphone and IoT Based System for Integrated Farm Monitoring. In: Pawar, P., Ronge, B., Balasubramaniam, R., Vibhute, A., Apte, S. (eds) Techno-Societal 2018 . Springer, Cham. https://doi.org/10.1007/978-3-030-16848-3_43
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DOI: https://doi.org/10.1007/978-3-030-16848-3_43
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