Feasibility Report of the Automatic Recyclable Garbage Classification
This is my senior design project that base on the density differences to detect and classify differentmaterial. This design is for recycling company in Philadelphia where will produce huge amount of the recyclablegarbage.
In this design, firstI will use statistical method to obtainthe recyclable garbage distribute in different area in Philadelphia. Base on the data, we can know that what is the most recyclable garbage that produce in Philadelphia. Then, we can establish a database that contain all the density of those recyclable garbage.After the database set up, connect those data into the density senior and install it in recyclable machine once all the garbage delivery into the garbage station all the garbage will scan by the machine that installed with the senior. After the scanning, the nonrecyclablegarbage and recyclable garbage willseparate. The recyclable garbage will go through the scanning again to classify by different material.
Classify all the recyclablegarbage before process the recycling can reduce the time and people to separatethat garbage. And, the derivative will produce better quality so if the reuse to public or house will release longer.
This design can start use in differentarea on Philadelphia once it become more optimal then we can start collect more data in neighboring city because different location will produce different garbage so if we need to use this in another city we need to update the density database server.
Recycling saves energy because the manufacturer doesn't have to produce something new from raw natural resources. By using recyclable materials, we save on energy consumption, which keeps production costs down. We classify different material before they recycling can reduce energy waste and labor waste during the recycling. The automatic separate can let recycling more efficient and pure recyclable derivative.