DIGITAL SOLUTIONS IN ELECTRONIC WASTE MANAGEMENT
Bibliographic record
Abstract
The article is devoted to the actual problem of substantiating directions for the use of innovative digital solutions in the management of waste electrical and electronic equipment. The structure of e-waste in developed countries in 2022, which includes IT and telecommunications devices, consumer devices and solar panels, power tools and medical devices, was analyzed and it was found that the largest share is household large-sized appliances (52.7%). Analysis of the dynamics of electronic waste generation per capita in industrialized countries in 2013–2022 showed that in 2022, each resident of Australia – 22.42 kg, Canada – 20.58 kg, Israel – 14.56 kg of electronic waste was generated, Japan – 20.55 kg, Korea – 16.80 kg, Great Britain – 24.63 kg, USA – 21.50 kg, EU – 28.54 kg. Considered the practice of waste management in industrially developed countries. For example, Japan (18–25%) is most actively involved in the processing of electronic waste. The EU has developed a strategy - an action plan for the closed cycle economy, in which the reduction of electrical and electronic waste is a key priority, and a number of proposals have been submitted to promote the repair of goods. The well-founded role of digitalization in the management of electronic waste, which consists in increasing the speed of waste processing and increasing its economic efficiency. The areas of use of innovative digital solutions in electronic waste management are defined, such as: robotics, artificial intelligence and neural networks, the Internet of Things, cloud solutions and data analytics. The advantages of digitization in waste management are disclosed, which includes: automation in waste disposal; improvement of the recycling process; ensuring waste minimization and saving natural resources; creating opportunities to identify problem areas and assess the efficiency of electronic waste disposal; helps to save money, energy and time for waste collection and disposal. The directions for handling electrical and electronic equipment waste have been defined, which consist in preventing the generation of waste, its collection, separation, processing, extraction of secondary raw materials through reuse, recycling and other forms of recovery, which will contribute to the realization of the goals of sustainable production and consumption and the improvement of environmental indicators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".