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Forecasting Chronic Pesticide Poisoning using Pesticide Residues in Agriculture

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dc.contributor.author Amunugama, Malmee
dc.date.accessioned 2023-01-12T08:51:32Z
dc.date.available 2023-01-12T08:51:32Z
dc.date.issued 2022
dc.identifier.citation Amunugama, Malmee (2022) Forecasting Chronic Pesticide Poisoning using Pesticide Residues in Agriculture. MSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 20191222
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1397
dc.description.abstract "Chronic pesticide poisoning is becoming a common threat to humans as food is one of the main basic human necessities regardless of gender, country, race, or ethnicity. Records of the World Health Organization states that usage of pesticides increasing day by day due to two primary reasons; to increase the productivity of the harvest and minimizing the agricultural losses. A lot of people are unable to see the downside and after-effects of this harmful activity as it boosts the productivity of the harvest. In fact, with the increase in pesticide usage, the pesticide residue is brushed and sedimented in the surface of the agricultural harvest. When people consume those products, they will insert them into their bodies, and when that frequently happens, it results in chronic pesticide poisoning. This problem is becoming a huge issue day by day, regardless of the country we live in, turning into a global crisis. Necessary safety precautions must be taken to avoid producing unhealthy next generation and making the current generation unwell. A lot of industrial companies are deterred to find alternative eco-friendly pesticides due to the uncertainty of the demand as it could result in losses. This dissertation discusses a system that forecasts pesticide usage in Sri Lanka, so that the public and authorities can keep track of the variation in pesticide usage, banned pesticide usage, environmental pollution caused due to pesticide over usage and keep track of the time to exceed the maximum residue limit of pesticides according to the current usage. " en_US
dc.language.iso en en_US
dc.subject Software Development Life Cycle en_US
dc.subject Machine Learning en_US
dc.subject Pesticide residue analysis en_US
dc.title Forecasting Chronic Pesticide Poisoning using Pesticide Residues in Agriculture en_US
dc.type Thesis en_US


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