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​​Hydroponics Checking and Control Framework: An IoT based Methodology: A Review

DOI: 10.18805/BKAP353    | Article Id: BKAP353 | Page : 293-298
Citation :- ​​Hydroponics Checking and Control Framework: An IoT based Methodology: A Review.Bhartiya Krishi Anusandhan Patrika.2021.(36):293-298
S.R. Balaji, K. Santhosh santhosh.ag19@bitsathy.ac.in
Address : Bannari Amman Institute of Technology, Sathyamangalam, Erode-638 401, Tamil Nadu, India.
Submitted Date : 11-08-2021
Accepted Date : 28-08-2021

Abstract

Web of Things (IoT) is the quickly creating fields for giving social and monetary focal points for rising and making an economy of the country. IoT field is prospering in regions like clinical, horticulture, transportation, preparing and So forth This is of maximum importance because hydroponics is a retrogressive locale of carried out science. Diverged from different zones like agribusiness, thus, it’s fundamental to decide the issues that are around here with the help of innovation. Water quality may be an essential issue, it fundamentally relies on various boundaries like broke up oxygen, carbonates, turbidity, alkali, nitrates, salt, pH, temperature and so forth. The proposed framework consistently screens the water superb boundary the usage of sensors, the incredible information is exceeded immediately to the water rancher bendy via the cloud. Among the issues, the sluggish dormant period inside the consideration of water quality and along these lines the wastage of assets like water, in development are the important issues that must be tended to. It is used to utilizations the wastewater from the aquarium to develop the plants, thus, the pH and alkali killed water from hydrogen dust pellets in broaden mattress is looked after lower back to the aquarium.

Keywords

​Hydroponics Machine to machine (M2M) connectivity Round trip time (RTT)

References

  1. Chandanapalli, S.B., Reddy, E.S. and Lakshmi, D.R. (2014). Design and deployment of aqua monitoring system using wireless sensor networks and IAR-Kick. Journal of Aquaculture Research and Development. 5(7). 
  2. Chavan, M.S., Patil, M.V.P., Chavan, S., Sana, S. and Shinde, C. (2018). Design and implementation of IOT based real time monitoring system for aquaculture using raspberry pi. International Journal on Recent and Innovation Trends in Computing and Communication. 6(3): 159-161. 
  3. Chen, J.H., Sung, W.T. and Lin, G.Y. (2015). October. Automated monitoring system for the fish farm aquaculture environment. In 2015 IEEE International Conference on Systems, Man and Cybernetics IEEE. (pp. 1161-1166).
  4. Deng, C., Gao, Y., Gu, J., Miao, X. and Li, S. (2010). Research on the Growth Model of Aquaculture Organisms Based on Neural Network Expert System. In: 2010 Sixth International Conference on Natural Computation. IEEE. 4: 1812-1815. 
  5. Encinas, C., Ruiz, E., Cortez, J. and Espinoza, A. (2017). April. Design and implementation of a distributed IoT system for the monitoring of water quality in aquaculture. In: 2017 Wireless Telecommunications Symposium (WTS) IEEE. (pp. 1-7).
  6. Haron, N.S., Mahamad, M.K.B., Aziz, I.A. and Mehat, M. (2008). August. A System Architecture for Water Quality Monitoring System Using Wired Sensors. In: 2008 International Symposium on Information Technology IEEE. 4: 1-7.
  7. Hongpin, L., Guanglin, L., Weifeng, P., Jie, S. and Qiuwei, B. (2015). Real-time remote monitoring system for aquaculture water quality. International Journal of Agricultural and Biological Engineering. 8(6): 136-143. 
  8. Israni, Sheetal., Harshal Meharkure. and Parag Yelore. (2015). Application of IoT based system for advance agriculture in India. International Journal of Innovative Research in Computer and Communication Engineering 3.11: 10831- 10837. 
  9. Nocheski, S. and Naumoski, A. (2018). Water monitoring IoT system for fish farming ponds. Industry 4.0, 3(2): 77-79. 
  10. Preetham, K., Mallikarjun, B.C., Umesha, K., Mahesh, F.M. and Neethan, S. (2019). Aquaculture monitoring and control system: An IoT based approach. International Journal of Advance Research, Ideas and Innovations in Technology.  5(2). 
  11. Raju, K.R.S.R. and Varma, G.H.K. (2017). January. Knowledge Based Real Time Monitoring System for Aquaculture using IoT. In: 2017 IEEE 7th International Advance Computing Conference (IACC) IEEE. (pp. 318-321).
  12. Simbeye, D.S. and Yang, S.F. (2014). Water quality monitoring and control for aquaculture based on wireless sensor networks.  Journal of Networks. 9(4): 840. 

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