Design and Implementation of an Intelligent Primary Sorting System for Municipal Solid Waste Using QR Codes and Artificial Intelligence in the Context of Kazakhstan

Abstract

This paper examines contemporary approaches to municipal solid waste (MSW) management, focusing on the transition from traditional collection and landfilling practices to intelligent and environmentally sustainable recycling systems. In light of the growing volume of waste generated in urban areas worldwide, including Kazakhstan, the integration of innovative technologies that enhance the efficiency of primary waste sorting and foster public participation in environmental responsibility has become increasingly significant. The study explores the development and implementation of a smart container system based on QR codes and artificial intelligence (AI), designed to automate waste identification and tracking at the initial collection stage. The main objective is to assess the potential for integrating digital technologies into the waste management framework and to propose a model that improves the recycling rate of secondary resources. The research presents the use of AI for waste type recognition, QR codes for user identification and reward distribution within the “EcoCoin” ecosystem, and a data collection mechanism for ESG reporting. The scientific novelty lies in the proposed integrated approach to waste management, combining digital identification technologies with intelligent sorting and advanced processing methods such as fermentative and plasma treatment. The practical significance of the study is determined by the scalability of the proposed system both within Kazakhstan and internationally, contributing to the reduction of landfill volumes, the strengthening of environmental sustainability, job creation, and increased public engagement in the digital green economy.