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Current IssueEditorial BoardOnline First ArticlesArchive

Research Article

volume 41 issue 3 (september 2020) : 279-284,   Doi: 10.18805/ag.R-151

Mitigation Techniques for Agricultural Pollution by Precision Technologies with a Focus on the Internet of Things (IoTs): A Review

A
A. Narmilan
N
N. Puvanitha
1Department of Biosystems Technology, Faculty of Technology, South Eastern University of Sri Lanka, Sri Lanka.
Cite article:- Narmilan A., Puvanitha N. (2020). Mitigation Techniques for Agricultural Pollution by Precision Technologies with a Focus on the Internet of Things (IoTs): A Review. Agricultural Reviews. 41(3): 279-284. doi: 10.18805/ag.R-151.

ABSTRACT

The widespread of Information and Communication Technology (ICT) in the past decades brought numerous advantages to many individuals and most of the organizations everywhere in the world. In the 21st century, the most significant technology is the Internet of Things (IoTs) which has developed rapidly covering most of applications in the health, civil, military and agriculture sectors also.  Precision Agriculture (PA), as the combination of information, communication and control technologies in agronomic practices, is emerging time by time. Also, precision agriculture is considered a smart farming system on the basis of modern technologies to regulate, examine and manage changes inside an agricultural field for cost-effectiveness, sustainability and optimal protection of environment. Meanwhile, agricultural practices are contributing to environmental pollution due to poor management which is further disturbing food security, health and climate. One of the best strategies to overcome this challenge can be introducing the deployment of precision technologies for the development of agricultural productivity while reducing the environmental degradation. Therefore, the key objective of this review was to discuss the mitigation techniques for agricultural pollution and enhance the agricultural production by smart technologies like IoTs. This paper summarizes the main categories of IoTs, Precision Agriculture, agricultural pollution and finally, mitigation practices on environmental degradation.

REFERENCES

  1. Ashton, K. (2009). That ‘internet of things’ thing. RFID Journal. 22(7): 97-114.
  2. Awati, J.S. and Patil, V.S. (2012). Automatic Irrigation Control by using wireless sensor networks. Journal of Exclusive Management Science. 1(6): 1-7.
  3. Balamurugan, C.R. and Satheesh, R. (2017). Development of Raspberry pi and IoT Based Monitoring and Controlling Devices for Agriculture. Journal of Social, Technological and Environmental Science. 6(2): 207-215.
  4. Barkunan, S.R., Bhanumathi, V. and Sethuram, J. (2019). Smart sensor for automatic drip irrigation system for paddy cultivation. Computers and Electrical Engineering. 73: 180-193.
  5. Dissanayake, S.A.D.A.N., Pasqual, H. and Athapattu, B.C.L. (2017). Economical colorimetric smart sensor to measure water quality of drinking water in CKDu prevalence areas. IEEE Sensors Journal. 17(18): 5885-5891.
  6. Dursun, M. and Ozden, S. (2011). A wireless application of drip irrigation automation supported by soil moisture sensors. Scientific Research and Essays. 6(7): 1573-1582.
  7. FAO. Org. (2019). Agriculture: cause and victim of water pollution, but change is possible | Land and Water | Food and Agriculture Organization of the United Nations | Land and Water | Food and Agriculture Organization of the United Nations. [Online] Available at: http://www.fao.org/land-water/news-archive/news-detail/en/c/1032702/ [Accessed 24 Sep. 2019].
  8. Fourati, M.A., Chebbi, W., Kamoun, A. (2014). Development of a web-based weather station for irrigation scheduling. In: Information Science and Technology (CIST), 2014 Third IEEE International Colloquium in IEEE, pp. 37–42.
  9. Goap, A., Sharma, D., Shukla, A.K. and Krishna, C.R. (2018). An IoT based smart irrigation management system using Machine learning and open source technologies. Computers and Electronics in Agriculture 155(May): 41-49. https://doi.org/10.1016/j.compag.2018.09.040.
  10. Godfray, H.C.J., Garnett, T. (2014). Food security and sustainable intensification. Phil. Trans. R. Soc. B 369, 1639.
  11. Hashim, N., Mazlan, S., Aziz, M.A., Salleh, A., Jaafar, A., Mohamad, N. (2015). Agriculture monitoring system: a study. J. Teknologi. 77: 53-59. https://doi.org/10.11113/jt.v77. 4099.
  12. Hosseini, M., Chizari, M., Bordbar, M. (2010). Evaluation of the possibility of precision agriculture from the view point of Agricultural experts in Fars Province. Iranian Agric. Exten. Edu. 6(2): 35-47. 
  13. Jaguey, J.G., Villa-Medina, J.F., Lopez-Guzman, A., Porta-Gandara, M.A. (2015). Smartphone irrigation sensor. IEEE Sens. J. 15: 5122-5127. https://doi.org/10.1109/JSEN.2015. 2435516.
  14. Joseph Haule, Kisangiri Michael. (2014). Deployment of wireless sensor networks (WSN) in automated irrigation management and scheduling systems: a review, Science, Computing and Telecommunications (PACT), Pan African Conference.
  15. Kale, A.P. and Sonavane, S.P. (2018). IoT based Smart Farming: Feature subset selection for optimized high- dimensional data using improved GA based approach for ELM. Computers and Electronics in Agriculture, (October 2017), 0–1. https://doi.org/10.1016/j.compag.2018.04.027.
  16. Kisan, W.S., Dadabhau, A.S. and Singh, K. (2013). Factors affecting the sustainability of ICT intervention for agricultural development -A review. Agricultural Reviews. 34(3): p. 198. doi: 10.5958/j.0976-0741.34.3.004.
  17. Krishnan, M., Foster, C.A., Strosser, R.P., Glancey, J.L. and Sun, J.Q. (2006). Adaptive modeling and control of a manure spreader for precision agriculture. Computers and Electronics in Agriculture. 52(1-2): 1-10.
  18. Kumar, R. (2012). Organic Farming as a Basis for Sustainable Farming Sustainable Agriculture-a Review. 33(1): 27-36.
  19. Kumar, V. and Sagwal, O. (2000). Recent studies on soil and water pollution in some parts of India: A review. Agricultural Reviews. 21(3): 186-192.
  20. Lashgarara, F., Mirdamadi, S.M. and Hosseini, S.J.F. (2010). Role of ICTs in improving food security of Iranian rural households. Biosciences Biotechnology Research Asia. 7(1): 127-132.
  21. Lavanya, G., Rani, C. and Ganeshkumar, P. (2019). An Automated Low Cost IoT based Fertilizer Intimation System for Smart Agriculture, Sustainable Computing: Informatics and Systems, https://doi.org/10.1016/j.suscom.2019.01.002
  22. Lee, M., Hwang, J. and Yoe, H. (2013). Agricultural production system based on IoT. In 2013 December IEEE 16th International Conference on Computational Science and Engineering pp. 833-837.
  23. Malek-Saeidi H. and Rezaei-Moghaddam K. (2008). Application of ecological knowledge system towards precision agriculture. Human and Environment, pp. 76-91.
  24. Maohua W. (2001). Possible adoption of precision agriculture for developing countries at the threshold of the new millennium. Com Ele in Agric. 30: 45-50.
  25. Mateo-Sagasta J, Marjani S, Turral H. (2018). More people, more food, worse water? A global review of water pollution from agriculture. Rome: FAO and IWMI.
  26. Medela, A., Cendón, B., González, L., Crespo, R., Nevares, I. (2013). IoT Multiplatform networking to monitor and control wineries and vineyards. In: Future Network and Mobile Summit. IEEE, pp. 1–10.
  27. Min-ShengLiao, Shih-Fang Chen, Cheng-Ying Chou, Hsun-Yi Chen, Shih-Hao Yeh, Yu-Chi Chang, Joe-Air Jiang. (2017). On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system. Computers and Electronics in Agriculture, p. 125-139.
  28. Mondal, P. and Basu, M. (2009). Adoption of precision agriculture technologies in India and in some developing countries: Scope, present status and strategies. Progress in Natural Science. 19(6): 659-666.
  29. Mulla, D.J. (2013). Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps. Biosystems Engineering. 114(4): 358-371.
  30. Nandurkar, S.R., Thool, V.R. and Thool, R.C. (2014). Design and development of precision agriculture system using wireless sensor network. In February 2014 First International Conference on Automation, Control, Energy and Systems (ACES), pp. 1-6.
  31. Nayyar, A. and Puri, E.V. (2016). Smart Farming: IoT Based Smart Sensors Agriculture Stick for Live Temprature and Moisture Monitoring using Arduino Cloud Computing and Solar Technology. In Conference: The International Conference on Communication and Computing Systems (ICCCS-2016, November).
  32. Nisha, G., Megala, J. (2014). Wireless Sensor Network Based Automated Irrigation and Crop Field Monitoring System, Sixth International Conference on Advanced Computing (IcoAC).
  33. Pang, Z., Chen, Q., Han, W., Zheng, L. (2015). Value-centric design of the internet-of things solution for food supply Chain: value creation, sensor portfolio and information fusion. Inform. Syst. Front. 17: 289–319. http://dx.doi.org/10.1007/ s10796-012-9374-9.
  34. Payero, J.O., Mirzakhani-Nafchi, A., Khalilian, A., Qiao, X. and Davis, R. (2017). Development of a Low-Cost Internet-of Things (IoT) System for Monitoring Soil Water Potential Using Watermark 200SS Sensors. Advances in Internet of Things. 7(3): 71-86.
  35. Pierce, F.J. and Elliott, T.V. (2008). Regional and on-farm wireless sensor networks for agricultural systems in Eastern Washington. Computers and Electronics in Agriculture. 61(1): 32-43.
  36. Rad, C.R., Hancu, O., Takacs, I.A. and Olteanu, G. (2015). Smart monitoring of potato crop: a cyber-physical system architecture model in the field of precision agriculture. Agriculture and Agricultural Science Procedia, 6, pp.73-79.
  37. Salehi, S. (2007). Factors affecting attitude and intention to use of agricultural specialists of Jihad-e-Keshavarzi Organization of Fars and Khuzestan Provinces toward precision agriculture technologies. Master thesis. Ahvaz University, Iran.
  38. Saville, R., Hatanaka, K., Wada, M. (2015). ICT application of real-time monitoring and estimation system for set-net fishery. In: OCEANS, pp. 1-5.
  39. Schindler, S.B., (2014). Unpermitted urban agriculture: transgressive actions, changing norms and the local food movement, Wis. L. Rev. (2014) 369.
  40. Sharma, D., Shukla, A.K., Bhondekar, A.P., Ghanshyam, C., Ojha, A. (2016). A technical assessment of IOT for Indian agriculture sector. In: IJCA Proc. Natl. Symp. Mod. Inf. Commun. Technol Digit. India, pp.1-5.
  41. Shi Y., Wang Z., Wang X., Zhang S. (2015). Internet of Things Application to Monitoring Plant Disease and Insect Pests. International Conference on Applied Science and Engineering Innovation, pp. 31-34.
  42. Srinivasan, A. (2006). Hand Book of Precision Agriculture: Principles and Applications. New York: Food Products Press.
  43. Sutton, M.A.B., Howard, C.M., Bekunda, M., Grizzetti, B., de Vries, W., et al. (2013). Our nutrient world: the challenge to produce more food and energy with less pollution. Centre for Ecology and Hydrology (Edinburgh) UK, on behalf of the Global Partnership on Nutrient Management and the International Nitrogen Initiative pp. 1-128.
  44. Talavera, J.M., Tobón, L.E., Gómez, J.A., Culman, M.A., Aranda, J.M., Parra, D.T., Garreta, L.E. (2017). Review of IoT applications in agro-industrial and environmental fields. Comput. Electron. Agric. 142: 283-297.
  45. Vallejo-Hernández, L.H., Rodriguez, G.B., Elghandour, M.M.Y, Greiner, R., Salem, A.Z.M., Adegbeye, M.J. (2019). Influence of phytase enzyme on ruminal biogas production and fermentative digestion towards reducing environmental contamination. Environ. Sci. Pollut. Res. 26: 9992-9999. https://doi.org/10.1007/s11356-019-04400-1.
  46. Vijayakumar, S., Nelson Rosario, J. (2011). Preliminary Design for Crop Monitoring Involving Water and Fertilizer Conservation Using Wireless Sensor Networks, Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference.
  47. Weber, R.H. (2010). Internet of Things–New security and privacy challenges. Computer Law and Security Review. 26(1): 23-30.
  48. Zhang N, Wang M, Wang N. (2002). Precision agriculture- a worldwide overview. Comp Ele Agric. 36: 113-132.
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    Research Article

    volume 41 issue 3 (september 2020) : 279-284,   Doi: 10.18805/ag.R-151

    Mitigation Techniques for Agricultural Pollution by Precision Technologies with a Focus on the Internet of Things (IoTs): A Review

    A
    A. Narmilan
    N
    N. Puvanitha
    1Department of Biosystems Technology, Faculty of Technology, South Eastern University of Sri Lanka, Sri Lanka.
    Cite article:- Narmilan A., Puvanitha N. (2020). Mitigation Techniques for Agricultural Pollution by Precision Technologies with a Focus on the Internet of Things (IoTs): A Review. Agricultural Reviews. 41(3): 279-284. doi: 10.18805/ag.R-151.

    ABSTRACT

    The widespread of Information and Communication Technology (ICT) in the past decades brought numerous advantages to many individuals and most of the organizations everywhere in the world. In the 21st century, the most significant technology is the Internet of Things (IoTs) which has developed rapidly covering most of applications in the health, civil, military and agriculture sectors also.  Precision Agriculture (PA), as the combination of information, communication and control technologies in agronomic practices, is emerging time by time. Also, precision agriculture is considered a smart farming system on the basis of modern technologies to regulate, examine and manage changes inside an agricultural field for cost-effectiveness, sustainability and optimal protection of environment. Meanwhile, agricultural practices are contributing to environmental pollution due to poor management which is further disturbing food security, health and climate. One of the best strategies to overcome this challenge can be introducing the deployment of precision technologies for the development of agricultural productivity while reducing the environmental degradation. Therefore, the key objective of this review was to discuss the mitigation techniques for agricultural pollution and enhance the agricultural production by smart technologies like IoTs. This paper summarizes the main categories of IoTs, Precision Agriculture, agricultural pollution and finally, mitigation practices on environmental degradation.

    REFERENCES

    1. Ashton, K. (2009). That ‘internet of things’ thing. RFID Journal. 22(7): 97-114.
    2. Awati, J.S. and Patil, V.S. (2012). Automatic Irrigation Control by using wireless sensor networks. Journal of Exclusive Management Science. 1(6): 1-7.
    3. Balamurugan, C.R. and Satheesh, R. (2017). Development of Raspberry pi and IoT Based Monitoring and Controlling Devices for Agriculture. Journal of Social, Technological and Environmental Science. 6(2): 207-215.
    4. Barkunan, S.R., Bhanumathi, V. and Sethuram, J. (2019). Smart sensor for automatic drip irrigation system for paddy cultivation. Computers and Electrical Engineering. 73: 180-193.
    5. Dissanayake, S.A.D.A.N., Pasqual, H. and Athapattu, B.C.L. (2017). Economical colorimetric smart sensor to measure water quality of drinking water in CKDu prevalence areas. IEEE Sensors Journal. 17(18): 5885-5891.
    6. Dursun, M. and Ozden, S. (2011). A wireless application of drip irrigation automation supported by soil moisture sensors. Scientific Research and Essays. 6(7): 1573-1582.
    7. FAO. Org. (2019). Agriculture: cause and victim of water pollution, but change is possible | Land and Water | Food and Agriculture Organization of the United Nations | Land and Water | Food and Agriculture Organization of the United Nations. [Online] Available at: http://www.fao.org/land-water/news-archive/news-detail/en/c/1032702/ [Accessed 24 Sep. 2019].
    8. Fourati, M.A., Chebbi, W., Kamoun, A. (2014). Development of a web-based weather station for irrigation scheduling. In: Information Science and Technology (CIST), 2014 Third IEEE International Colloquium in IEEE, pp. 37–42.
    9. Goap, A., Sharma, D., Shukla, A.K. and Krishna, C.R. (2018). An IoT based smart irrigation management system using Machine learning and open source technologies. Computers and Electronics in Agriculture 155(May): 41-49. https://doi.org/10.1016/j.compag.2018.09.040.
    10. Godfray, H.C.J., Garnett, T. (2014). Food security and sustainable intensification. Phil. Trans. R. Soc. B 369, 1639.
    11. Hashim, N., Mazlan, S., Aziz, M.A., Salleh, A., Jaafar, A., Mohamad, N. (2015). Agriculture monitoring system: a study. J. Teknologi. 77: 53-59. https://doi.org/10.11113/jt.v77. 4099.
    12. Hosseini, M., Chizari, M., Bordbar, M. (2010). Evaluation of the possibility of precision agriculture from the view point of Agricultural experts in Fars Province. Iranian Agric. Exten. Edu. 6(2): 35-47. 
    13. Jaguey, J.G., Villa-Medina, J.F., Lopez-Guzman, A., Porta-Gandara, M.A. (2015). Smartphone irrigation sensor. IEEE Sens. J. 15: 5122-5127. https://doi.org/10.1109/JSEN.2015. 2435516.
    14. Joseph Haule, Kisangiri Michael. (2014). Deployment of wireless sensor networks (WSN) in automated irrigation management and scheduling systems: a review, Science, Computing and Telecommunications (PACT), Pan African Conference.
    15. Kale, A.P. and Sonavane, S.P. (2018). IoT based Smart Farming: Feature subset selection for optimized high- dimensional data using improved GA based approach for ELM. Computers and Electronics in Agriculture, (October 2017), 0–1. https://doi.org/10.1016/j.compag.2018.04.027.
    16. Kisan, W.S., Dadabhau, A.S. and Singh, K. (2013). Factors affecting the sustainability of ICT intervention for agricultural development -A review. Agricultural Reviews. 34(3): p. 198. doi: 10.5958/j.0976-0741.34.3.004.
    17. Krishnan, M., Foster, C.A., Strosser, R.P., Glancey, J.L. and Sun, J.Q. (2006). Adaptive modeling and control of a manure spreader for precision agriculture. Computers and Electronics in Agriculture. 52(1-2): 1-10.
    18. Kumar, R. (2012). Organic Farming as a Basis for Sustainable Farming Sustainable Agriculture-a Review. 33(1): 27-36.
    19. Kumar, V. and Sagwal, O. (2000). Recent studies on soil and water pollution in some parts of India: A review. Agricultural Reviews. 21(3): 186-192.
    20. Lashgarara, F., Mirdamadi, S.M. and Hosseini, S.J.F. (2010). Role of ICTs in improving food security of Iranian rural households. Biosciences Biotechnology Research Asia. 7(1): 127-132.
    21. Lavanya, G., Rani, C. and Ganeshkumar, P. (2019). An Automated Low Cost IoT based Fertilizer Intimation System for Smart Agriculture, Sustainable Computing: Informatics and Systems, https://doi.org/10.1016/j.suscom.2019.01.002
    22. Lee, M., Hwang, J. and Yoe, H. (2013). Agricultural production system based on IoT. In 2013 December IEEE 16th International Conference on Computational Science and Engineering pp. 833-837.
    23. Malek-Saeidi H. and Rezaei-Moghaddam K. (2008). Application of ecological knowledge system towards precision agriculture. Human and Environment, pp. 76-91.
    24. Maohua W. (2001). Possible adoption of precision agriculture for developing countries at the threshold of the new millennium. Com Ele in Agric. 30: 45-50.
    25. Mateo-Sagasta J, Marjani S, Turral H. (2018). More people, more food, worse water? A global review of water pollution from agriculture. Rome: FAO and IWMI.
    26. Medela, A., Cendón, B., González, L., Crespo, R., Nevares, I. (2013). IoT Multiplatform networking to monitor and control wineries and vineyards. In: Future Network and Mobile Summit. IEEE, pp. 1–10.
    27. Min-ShengLiao, Shih-Fang Chen, Cheng-Ying Chou, Hsun-Yi Chen, Shih-Hao Yeh, Yu-Chi Chang, Joe-Air Jiang. (2017). On precisely relating the growth of Phalaenopsis leaves to greenhouse environmental factors by using an IoT-based monitoring system. Computers and Electronics in Agriculture, p. 125-139.
    28. Mondal, P. and Basu, M. (2009). Adoption of precision agriculture technologies in India and in some developing countries: Scope, present status and strategies. Progress in Natural Science. 19(6): 659-666.
    29. Mulla, D.J. (2013). Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps. Biosystems Engineering. 114(4): 358-371.
    30. Nandurkar, S.R., Thool, V.R. and Thool, R.C. (2014). Design and development of precision agriculture system using wireless sensor network. In February 2014 First International Conference on Automation, Control, Energy and Systems (ACES), pp. 1-6.
    31. Nayyar, A. and Puri, E.V. (2016). Smart Farming: IoT Based Smart Sensors Agriculture Stick for Live Temprature and Moisture Monitoring using Arduino Cloud Computing and Solar Technology. In Conference: The International Conference on Communication and Computing Systems (ICCCS-2016, November).
    32. Nisha, G., Megala, J. (2014). Wireless Sensor Network Based Automated Irrigation and Crop Field Monitoring System, Sixth International Conference on Advanced Computing (IcoAC).
    33. Pang, Z., Chen, Q., Han, W., Zheng, L. (2015). Value-centric design of the internet-of things solution for food supply Chain: value creation, sensor portfolio and information fusion. Inform. Syst. Front. 17: 289–319. http://dx.doi.org/10.1007/ s10796-012-9374-9.
    34. Payero, J.O., Mirzakhani-Nafchi, A., Khalilian, A., Qiao, X. and Davis, R. (2017). Development of a Low-Cost Internet-of Things (IoT) System for Monitoring Soil Water Potential Using Watermark 200SS Sensors. Advances in Internet of Things. 7(3): 71-86.
    35. Pierce, F.J. and Elliott, T.V. (2008). Regional and on-farm wireless sensor networks for agricultural systems in Eastern Washington. Computers and Electronics in Agriculture. 61(1): 32-43.
    36. Rad, C.R., Hancu, O., Takacs, I.A. and Olteanu, G. (2015). Smart monitoring of potato crop: a cyber-physical system architecture model in the field of precision agriculture. Agriculture and Agricultural Science Procedia, 6, pp.73-79.
    37. Salehi, S. (2007). Factors affecting attitude and intention to use of agricultural specialists of Jihad-e-Keshavarzi Organization of Fars and Khuzestan Provinces toward precision agriculture technologies. Master thesis. Ahvaz University, Iran.
    38. Saville, R., Hatanaka, K., Wada, M. (2015). ICT application of real-time monitoring and estimation system for set-net fishery. In: OCEANS, pp. 1-5.
    39. Schindler, S.B., (2014). Unpermitted urban agriculture: transgressive actions, changing norms and the local food movement, Wis. L. Rev. (2014) 369.
    40. Sharma, D., Shukla, A.K., Bhondekar, A.P., Ghanshyam, C., Ojha, A. (2016). A technical assessment of IOT for Indian agriculture sector. In: IJCA Proc. Natl. Symp. Mod. Inf. Commun. Technol Digit. India, pp.1-5.
    41. Shi Y., Wang Z., Wang X., Zhang S. (2015). Internet of Things Application to Monitoring Plant Disease and Insect Pests. International Conference on Applied Science and Engineering Innovation, pp. 31-34.
    42. Srinivasan, A. (2006). Hand Book of Precision Agriculture: Principles and Applications. New York: Food Products Press.
    43. Sutton, M.A.B., Howard, C.M., Bekunda, M., Grizzetti, B., de Vries, W., et al. (2013). Our nutrient world: the challenge to produce more food and energy with less pollution. Centre for Ecology and Hydrology (Edinburgh) UK, on behalf of the Global Partnership on Nutrient Management and the International Nitrogen Initiative pp. 1-128.
    44. Talavera, J.M., Tobón, L.E., Gómez, J.A., Culman, M.A., Aranda, J.M., Parra, D.T., Garreta, L.E. (2017). Review of IoT applications in agro-industrial and environmental fields. Comput. Electron. Agric. 142: 283-297.
    45. Vallejo-Hernández, L.H., Rodriguez, G.B., Elghandour, M.M.Y, Greiner, R., Salem, A.Z.M., Adegbeye, M.J. (2019). Influence of phytase enzyme on ruminal biogas production and fermentative digestion towards reducing environmental contamination. Environ. Sci. Pollut. Res. 26: 9992-9999. https://doi.org/10.1007/s11356-019-04400-1.
    46. Vijayakumar, S., Nelson Rosario, J. (2011). Preliminary Design for Crop Monitoring Involving Water and Fertilizer Conservation Using Wireless Sensor Networks, Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference.
    47. Weber, R.H. (2010). Internet of Things–New security and privacy challenges. Computer Law and Security Review. 26(1): 23-30.
    48. Zhang N, Wang M, Wang N. (2002). Precision agriculture- a worldwide overview. Comp Ele Agric. 36: 113-132.
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