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ECOSORT IOT WASTE SEGREGATION AND MONITORING SYSTEM

Syeda Benazir Khan, Shweta Patil, Sindhuja Patil, Uzba ., Dr. Anuradha Patil

Abstract


Waste production has been rising as a result of urbanization and population growth. The overflowing trash can in urban areas contributes to an unsanitary atmosphere. As a result, the environment deteriorates. To combat this, the "ECOSORT IOT Waste Segregation and Monitoring System" was created to lessen the amount of labor required of rag pickers, who separate waste by hand, posing health risks to themselves. Wet, dry, and metallic waste are the three categories into which the suggested system divides the garbage. In addition to being economical, this system's development makes trash management more effective. The appropriate sensors identify each garbage and separate it within the designated bins; the server is updated on a regular basis with the amount of waste that has been disposed of. With a rapid increase in population, many problems arise in relation to waste dumps. These emits hazardous gases, which have negative effects on human health. The main issue is the domestic solid waste collection, management and classification. According to studies, in America, nearly 75% of waste can be recycled, but there is a lack of a proper real time waste segregating mechanism, due to which only 30% of waste is being recycled at present. To maintain a clean and green environment, we need a smart waste management and classification system. To tackle the above highlighted issue, we propose a real time Smart waste management and classification mechanism.


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References


Amrutha Chandramohan, Joyal Mendonca, Nikjil Ravi Shankar, Nikhil U. Baheti, Nitin Kumar Krishnan, M.S. Suma, “Automated Waste Segregator”, Texas Instruments India Educators’ Conference(TIIEC), 4-5 April 2017, Bangalore, Pp. 1-6.

Prof B S Malapur, Vanir, Puttanshetti, “IOT Based Waste Management: An Application to Smart City”, Ieee 2017.

Sharanya, A. U. Harika, N. Sriya, Sreeja Kochwila, “Automatic Waste Segregator”, IEEE 2017.


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