dc.contributor.author | Martikkala, Antti Tapani | |
dc.contributor.author | Mayanti, Bening | |
dc.contributor.author | Helo, Petri | |
dc.contributor.author | Lobov, Andrei | |
dc.contributor.author | Flores Ituarte, Iñigo | |
dc.date.accessioned | 2023-03-08T08:29:37Z | |
dc.date.available | 2023-03-08T08:29:37Z | |
dc.date.created | 2023-03-04T09:17:16Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 0301-4797 | |
dc.identifier.uri | https://hdl.handle.net/11250/3056919 | |
dc.description.abstract | Increasing textile production is associated with an environmental burden which can be decreased with an improved recycling system by digitalization. The collection of textiles is done with so-called curbside bins. Sensor technologies support dynamic-informed decisions during route planning, helping predict waste accumulation in bins, which is often irregular and difficult to predict. Therefore, dynamic route-optimization decreases the costs of textile collection and its environmental load. The existing research on the optimization of waste collection is not based on real-world data and is not carried out in the context of textile waste. The lack of real-world data can be attributed to the limited availability of tools for long-term data collection. Consequently, a system for data collection with flexible, low-cost, and open-source tools is developed. The viability and reliability of such tools are tested in practice to collect real-world data. This research demonstrates how smart bins solution for textile waste collection can be linked to a dynamic route-optimization system to improve overall system performance. The developed Arduino-based low-cost sensors collected actual data in Finnish outdoor conditions for over twelve months. The viability of the smart waste collection system was complemented with a case study evaluating the collection cost of the conventional and dynamic scheme of discarded textiles. The results of this study show how a sensor-enhanced dynamic collection system reduced the cost 7.4% compared with the conventional one. We demonstrate a time efficiency of −7.3% and that a reduction of 10.2% in CO2 emissions is achievable only considering the presented case study. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier B. V. | en_US |
dc.relation.uri | https://doi.org/10.1016/j.jenvman.2023.117548 | |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Smart textile waste collection system – Dynamic route optimization with IoT | en_US |
dc.title.alternative | Smart textile waste collection system – Dynamic route optimization with IoT | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.volume | 335 | en_US |
dc.source.journal | Journal of Environmental Management | en_US |
dc.identifier.doi | 10.1016/j.jenvman.2023.117548 | |
dc.identifier.cristin | 2131145 | |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |