Energy Efficient Wireless Sensor Network for Precision Agriculture
DOI:
https://doi.org/10.32628/IJSRSET196220Keywords:
Agricultural environment monitoring, Association Rule Mining (ARM), Data mining, Ranking of association rules.Abstract
Wireless Sensor Network (WSN) is the latest technology which provides the best and cheaper solution for a broad range of computer programs from healthcare to agriculture to (related to surrounding conditions or the health of the Earth) and military operations. India is basically a country with (good) enough valuable things from nature and focussed on farming adding/giving to its (process of people making, selling, and buying things) and (the social level people are at based on how much money they have). In the farming-based (surrounding conditions) watching/supervising area, WSN plays a big part because of its (producing a lot for a given amount of money) and comfortable use/military service of WSN. WSN is in need to (make something as small as possible/treat something important as unimportant) the energy use through (not operating or working now, but able to), transmission, etc. It needs/demands added/more energy (producing a lot with very little waste) way of doing things with data (quality of being very close to the truth or true number) leads to long life for watching/supervising farm-related field. A powerful tool that can create huge and (many different kinds of people or things) data including farming-based datasets is Association Rule Mining (ARM). A topic that is of attention in data mining of late is ranking of association rules. This work deals with farming-based sensor network which measures temperature, soil moisture, humidity and ARM based on ranking.
References
- Kodali, R. K., Rawat, N., &Boppana, L. (2014). WSN sensors for precision agriculture. In Region 10 Symposium, 2014 IEEE (pp. 651-656). IEEE.
- Ramesh D, Vishnu Vardhan B.(2013). Data Mining Techniques and Applications to Agricultural Yield Data. IJARCCE, Vol. 2, Issue 9.
- Khan, F., & Singh, D. (2014). Association rule mining in the field of agriculture: a survey. International Journal of Scientific and Research Publications, 329.
- Geetha., M, C, S. (2015). Implementation of Association Rule Mining for different soil types in Agriculture. International Journal of Advanced Research in Computer and Communication Engineering, Vol. 4, Issue 4, pp. (520-522).
- Yu, C. (2016). Low Cost Locating Method of Wireless Sensor Network in Precision Agriculture. Cybernetics and Information Technologies, 16(6), 123-132.
- Kassim, M. R. M., Mat, I., & Harun, A. N. (2014). Wireless Sensor Network in precision agriculture application. In Computer, Information and Telecommunication Systems (CITS), 2014 International Conference on (pp. 1-5). IEEE.
- Mallik, S., Mukhopadhyay, A., &Maulik, U. (2015). RANWAR: rank-based weighted association rule mining from gene expression and methylation data. IEEE transactions on nanobioscience, 14(1), 59-66.
- Premalatha, S., & Nandhini, C. U. (2015). Efficiently Generating The Rank Based Weighted Association Rule Mining Using Apriori Algorithm In High Biological Database.
- Solanki, S. K., & Patel, J. T. (2015). A survey on association rule mining. In Advanced Computing & Communication Technologies (ACCT), 2015 Fifth IEEE International Conference, pp. 212-216.
- Farah Khan and Dr. Divakar Singh (2014). Knowledge Discovery on Agricultural Dataset Using Association Rule Mining. International Journal of Emerging Technology and Advanced Engineering, pp. 925 – 930.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRSET
This work is licensed under a Creative Commons Attribution 4.0 International License.