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IoT based Smart System to Support Agricultural Parameters: A Case Study
BGC Trust University Bangladesh, Chandanaish, Chittagong-4381, Bangladesh.
BGC Trust University Bangladesh, Chandanaish, Chittagong-4381, Bangladesh.
BGC Trust University Bangladesh, Chandanaish, Chittagong-4381, Bangladesh.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-0244-3561
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2019 (English)In: Proceedings of the 6th International Symposium on Emerging Inter-networks, Communication and Mobility (EICM), Elsevier, 2019, p. 648-653Conference paper, Published paper (Refereed)
Abstract [en]

Now-a-days, the natural irrigation system is under pressure due to the growing water shortages, which are mainly caused by population growth and climate change. Therefore, the control of water resources to increase the allocation of retained water is very important. It has been observed in the last two decades, especially in the Indian sub-continent, the change of climate affects the agricultural crops production significantly. However, the prediction of good harvests before harvesting, enables the farmers as well as the government officials to take appropriate measures of marketing and storage of crops. Some strategies for predicting and modelling crop yields have been developed, although they do not take into account the characteristics of climate, and they are empirical in nature. In the proposed system, a Cuckoo Search Algorithm has been developed, allowing the allocation of water for farming under any conditions. The various parameters such as temperature, turbidity, pH., moisture have been collected by using Internet of Things (IoT) platform, equipped with related sensors and wireless communication systems. In this IoT platform the sensor data have been displayed in the cloud environment by using ThingSpeak. The data received in the ThingSpeak used in the proposed Cuckoo Search Algorithm, allowing the selection of appropriate crops for particular soil

Place, publisher, year, edition, pages
Elsevier, 2019. p. 648-653
Series
Procedia Computer Science, ISSN 1877-0509
Keywords [en]
Irrigation System, Data monitoring System, Farming land quality analysis, IoT, ThingSpeak, Cloud Platform, Agriculture System, Real-time, Prediction
National Category
Computer Sciences
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-76004DOI: 10.1016/j.procs.2019.08.092OAI: oai:DiVA.org:ltu-76004DiVA, id: diva2:1351345
Conference
The 6th International Symposium on Emerging Inter-networks, Communication and Mobility (EICM)
Available from: 2019-09-14 Created: 2019-09-14 Last updated: 2019-10-22

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Andersson, Karl

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