Abstract
The management and collection of household waste often represents a demanding task for elderly or impaired people. In particular, the increasing generation of plastic waste at home may pose a problem for these groups, as this type of waste accumulates very rapidly and occupies a considerable amount of space. This paper proposes a collaborative infrastructure to monitor household plastic waste. It consists of simple smart bins using a weight scale and a smart application that forecasts the amount of plastic generated for each bin at different time horizons out of the data provided by the smart bins. The application generates optimal routes for the waste-pickers collaborating in the system through a route-planning algorithm. This algorithm takes into account the predicted amount of plastic of each bin and the waste-picker’s location and means of transport. This proposal has been evaluated by means of a simulated scenario in Quezon City, Philippines, where severe problems with plastic waste have been identified. A set of 176 experiments have been performed to collect data that allow representing different user behaviors when generating plastic waste. The results show that our proposal enables waste-pickers to collect more than the 80% of the household plastic-waste bins before they are completely full.
Highlights
Plastic production has significantly increased during the COVID-19 pandemic
Citizens with disabilities, seniors and those in COVID-19 quarantine may have difficulties throwing the plastic waste in a daily basis
This paper proposes a collaborative solution for household plastic-waste collection focused on the aforementioned groups
Summary
With the United Nations announcing plastic pollution as a global crisis, many countries have banned single-use plastics and started to urge people to help minimize their plastic usage. Many manufacturers and producers have started changing their entire production industry to help in their own ways to reduce plastics [2,3]. In this context, an efficient collection of plastic waste is being perceived as a fundamental public service [4]. Some studies focus on digitization of solid waste bin maps while trying to minimize the route length of the collecting vehicles [6]. Current studies rely on the use of devices such as weight sensors to measure the bin levels of a municipality in real time [7]
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