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The article discusses the use of LoRa wireless technology for continuous monitoring of water quality using water quality sensors such as a conductivity meter and a pH sensor with a common data exchange gateway. The article presents the primary measurement indicators, the control board diagram, the system operation algorithm and further work prospects.The results of the work dealing with the issue of integrating the wireless technology and its operation using the wireless transceiver LoRa Ra-02 on an SX1278 chip with Atmega 328 microprocessor to water purification devices for creating a remote monitoring and decision-making system are presented on the experimental stand.

  • Web Address
  • DOI
  • Date of creation in the UzSCI system25-03-2021
  • Read count188
  • Date of publication19-11-2020
  • Main LanguageIngliz
  • Pages47-53
English

The article discusses the use of LoRa wireless technology for continuous monitoring of water quality using water quality sensors such as a conductivity meter and a pH sensor with a common data exchange gateway. The article presents the primary measurement indicators, the control board diagram, the system operation algorithm and further work prospects.The results of the work dealing with the issue of integrating the wireless technology and its operation using the wireless transceiver LoRa Ra-02 on an SX1278 chip with Atmega 328 microprocessor to water purification devices for creating a remote monitoring and decision-making system are presented on the experimental stand.

Name of reference
1 Mateo-Sagasta, and Javier & Burke, Jacob, “Agriculture and water quality interactions: a global overview.,” 2010, [Online]. Available: https://www.researchgate.net/publication/329239981_Agriculture_and_water_quality_interactions_a_global_overview.
2 2. “WHO | Water-related diseases,” WHO. ttp://www.who.int/water_sanitation_health/diseases-risks/diseases/diarrhoea/en/ (accessed May 31, 2020).
3 3. S. Randhawa, S. S. Sandha, and B. Srivastava, “A Multi-sensor Process for In-Situ Monitoring of Water Pollution in Rivers or Lakes for High-Resolution Quantitative and Qualitative Water Quality Data,” presented at the Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016, 2017, pp. 122–129, doi: 10.1109/CSE-EUC-DCABES.2016.171
4 4. D. W. Hallema, F.-N. Robinne, and S. G. McNulty, “Pandemic spotlight on urban water quality,” Ecological Processes, vol. 9, no. 1, 2020, doi: 10.1186/s13717-020-00231-y.
5 5. N. Markert, S. Rhiem, M. Trimborn, and B. Guhl, “Mixture toxicity in the Erft River: assessment of ecological risks and toxicity drivers,” Environmental Sciences Europe, vol. 32, no. 1, 2020, doi: 10.1186/s12302-020-00326-5.
6 6. D. Babitsch and A. Sundermann, “Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances,” Environmental Sciences Europe, vol. 32, no. 1, 2020, doi: 10.1186/s12302-019-0285-y.
7 7. M. D. Ramadhona and D. L. Hakim, “System of Water Quality Monitoring and Feeding on Freshwater Fish Cultivation,” presented at the IOP Conference Series: Materials Science and Engineering, 2018, vol. 384, no. 1, doi: 10.1088/1757-899X/384/1/012034.
8 8. M. Chiani and A. Elzanaty, “On the LoRa Modulation for IoT: Waveform Properties and Spectral Analysis,” IEEE Internet of Things Journal, vol. 6, no. 5, pp. 8463–8470, 2019, doi: 10.1109/JIOT.2019.2919151.
9 9. A. Raychowdhury and A. Pramanik, “Survey on LoRa Technology: Solution for Internet of Things,” Advances in Intelligent Systems and Computing, vol. 1148, pp. 259–271, 2020, doi: 10.1007/978-981-15-3914-5_20.
10 10. J. Elliott et al., “Constraints and potentials of future irrigation water availability on agricultural production under climate change,” Proceedings of the National Academy of Sciences of the United States of America, vol. 111, no. 9, pp. 3239–3244, 2014, doi: 10.1073/pnas.1222474110.
11 11. S. Rezwan et al., “A Minimalist Model of IoT based Sensor System for Sewage Treatment Plant Monitoring,” presented at the 2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2019, 2019, pp. 939–945, doi: 10.1109/IEMCON.2019.8936182.
12 12. A. Raychowdhury and A. Pramanik, “Survey on LoRa Technology: Solution for Internet of Things,” Advances in Intelligent Systems and Computing, vol. 1148, pp. 259–271, 2020, doi: 10.1007/978-981-15-3914-5_20.
13 Mateo-Sagasta, and Javier & Burke, Jacob, “Agriculture and water quality interactions: a global overview.,” 2010, [Online]. Available: https://www.researchgate.net/publication/329239981_Agriculture_and_water_quality_interactions_a_global_overview. 2. “WHO | Water-related diseases,” WHO. ttp://www.who.int/water_sanitation_health/diseases-risks/diseases/diarrhoea/en/ (accessed May 31, 2020). 3. S. Randhawa, S. S. Sandha, and B. Srivastava, “A Multi-sensor Process for In-Situ Monitoring of Water Pollution in Rivers or Lakes for High-Resolution Quantitative and Qualitative Water Quality Data,” presented at the Proceedings - 19th IEEE International Conference on Computational Science and Engineering, 14th IEEE International Conference on Embedded and Ubiquitous Computing and 15th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, CSE-EUC-DCABES 2016, 2017, pp. 122–129, doi: 10.1109/CSE-EUC-DCABES.2016.171. 4. D. W. Hallema, F.-N. Robinne, and S. G. McNulty, “Pandemic spotlight on urban water quality,” Ecological Processes, vol. 9, no. 1, 2020, doi: 10.1186/s13717-020-00231-y. 5. N. Markert, S. Rhiem, M. Trimborn, and B. Guhl, “Mixture toxicity in the Erft River: assessment of ecological risks and toxicity drivers,” Environmental Sciences Europe, vol. 32, no. 1, 2020, doi: 10.1186/s12302-020-00326-5. 6. D. Babitsch and A. Sundermann, “Chemical surveillance in freshwaters: small sample sizes underestimate true pollutant loads and fail to detect environmental quality standard exceedances,” Environmental Sciences Europe, vol. 32, no. 1, 2020, doi: 10.1186/s12302-019-0285-y. 7. M. D. Ramadhona and D. L. Hakim, “System of Water Quality Monitoring and Feeding on Freshwater Fish Cultivation,” presented at the IOP Conference Series: Materials Science and Engineering, 2018, vol. 384, no. 1, doi: 10.1088/1757-899X/384/1/012034. 8. M. Chiani and A. Elzanaty, “On the LoRa Modulation for IoT: Waveform Properties and Spectral Analysis,” IEEE Internet of Things Journal, vol. 6, no. 5, pp. 8463–8470, 2019, doi: 10.1109/JIOT.2019.2919151. 9. A. Raychowdhury and A. Pramanik, “Survey on LoRa Technology: Solution for Internet of Things,” Advances in Intelligent Systems and Computing, vol. 1148, pp. 259–271, 2020, doi: 10.1007/978-981-15-3914-5_20. 10. J. Elliott et al., “Constraints and potentials of future irrigation water availability on agricultural production under climate change,” Proceedings of the National Academy of Sciences of the United States of America, vol. 111, no. 9, pp. 3239–3244, 2014, doi: 10.1073/pnas.1222474110. 11. S. Rezwan et al., “A Minimalist Model of IoT based Sensor System for Sewage Treatment Plant Monitoring,” presented at the 2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference, IEMCON 2019, 2019, pp. 939–945, doi: 10.1109/IEMCON.2019.8936182. 12. A. Raychowdhury and A. Pramanik, “Survey on LoRa Technology: Solution for Internet of Things,” Advances in Intelligent Systems and Computing, vol. 1148, pp. 259–271, 2020, doi: 10.1007/978-981-15-3914-5_20. 13. R. Gazieva and E. Ozodov, “Automatic diffusion mixing system for watering in regions with high water sales,” presented at the International Conference on Information Science and Communications Technologies: Applications, Trends and Opportunities, ICISCT 2019, 2019, doi: 10.1109/ICISCT47635.2019.9011841.
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