Development of Smart Waste Bin Segregation using Image Processing
Froilan N. Jimeno, Briely Jay A. Briz, Marvin Roy P. Artiaga, Randy E. Angelia, Noel B. Limsangan
Abstract
In the Philippines, solid waste management is still a significant problem. Improper waste disposal causes serious health problems and environmental risks such as contamination of the water systems, floods, ground and air pollution, and diseases. Unfortunately, most people mistakenly believe that not segregating waste is acceptable. This study aims to develop and design a Smart Waste Bin Segregation using Image Processing and assist waste segregation through waste identification and segregation built on machine learning capable of navigating the one-time path set by the user. In particular, create an intelligent waste bin segregation prototype using image processing with three classifications. These classifications are the biodegradable, non-bio-degradable, and unknown intended to segregate solid waste into its respective bins and conduct accuracy tests using appropriate statistical tools. This device is designed for school use and may also be used in other establishments if more waste is trained, alleviate the waste segregation problem and help build an eco-friendlier society without compromising health and hygiene. The proponents successfully materialized the device, and function tests yielded an overall result of 97.33% accuracy.