Abstract
Agriculture is the backbone of Indian economy. Most of the population of the country is directly or indirectly dependent on agriculture. Technology can improve agricultural outcomes. In this modern era, there is a major drift in agricultural methods from traditional approaches. Recent advancements in technology have had a great impact on agriculture and it has been established that IoT can be used in farming to enhance quality of agriculture. Evolution of Machine Learning (ML), Deep Learning (DL) and Internet of Things (IoT) has gathered attention of researchers to apply these techniques in fields like agriculture. It helps farmers to increase the productivity of their land so the worldwide demand for food can be fulfilled. This paper highlights various farming problems that can be solved using the synergistic application of deep learning and IoT. In this paper, previous work done with these technologies is discussed. Moreover, we have presented a comparison between Deep Learning and Machine Learning, with specific focus on the complete process of applying Deep Learning on agriculture data to make predictions for agricultural applications.
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Garg, D., Khan, S., Alam, M. (2020). Integrative Use of IoT and Deep Learning for Agricultural Applications. In: Singh, P., Panigrahi, B., Suryadevara, N., Sharma, S., Singh, A. (eds) Proceedings of ICETIT 2019. Lecture Notes in Electrical Engineering, vol 605. Springer, Cham. https://doi.org/10.1007/978-3-030-30577-2_46
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