Abstract
Unlike most industries that are enforced to manage their own waste, the hospitality sector uses municipal waste collection systems, which contributes to their saturation. This may soon come to an end with an ever more restrictive legislation. This paper describes an energy-efficient, high-volume plastic waste recycling management system designed for the hospitality industry. Its main components include a compaction container with an anti-trapping mechanism controlled by a low-power IoT electronic module. This module can send container sensor readings wirelessly to the cloud where they are processed and stored. The system in the container is powered by a battery, which is charged wirelessly. This way there is no need to handle any wires and prevents potential wire-related incidents when manipulating the container. The waste collection company can instantly check the status of all containers at any time, which allows it to efficiently manage its resources according to the filling status of the containers. This paper describes the IoT system architecture, the data cloud storage and the IoT electronic module, including the following modules: container control, anti-trapping, data acquisition, sending and storage, and wireless communications. Finally, the most important conclusions that have emerged during the development and implementation are reported.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
De Paz, J.F., Bajo, J., Rodríguez, S., Villarrubia, G., Corchado, J.M.: Intelligent system for lighting control in smart cities. Information Sciences 372, 241–255 (2016). ISSN 0020–0255, https://doi.org/10.1016/j.ins.2016.08.045
Villarrubia, G., De Paz, J.F., De La Iglesia, D.H., Bajo, J.: Combining multi-agent systems and wireless sensor networks for monitoring crop irrigation. Sensors 17(8), 1775 (2017). https://doi.org/10.3390/s17081775
Silva, B.N., Khan, M., Han, K.: Towards sustainable smart cities: a review of trends, architectures, components, and open challenges in smart cities. Sustainable Cities and Society 38, 697–713 (2018). ISSN 2210–6707. https://doi.org/10.1016/j.scs.2018.01.053
Alvarez-Campana, M., López, G., Vázquez, E., Villagrá, V.A., Berrocal, J.: Smart CEI Moncloa: An IoT-based platform for people flow and environmental monitoring on a smart University Campus. Sensors 17(12), 2856 (2017). https://doi.org/10.3390/s17122856
Lozano, Á., Caridad, J., De Paz, J.F., Villarrubia González, G., Bajo, J.: Smart waste collection system with low consumption LoRaWAN nodes and route optimization. Sensors 18(5), 1465 (2018). https://doi.org/10.3390/s18051465
Gutierrez, J.M., Jensen, M., Henius, M., Riaz, T.: Smart waste collection system based on location intelligence. Procedia Computer Science 61, 120–127 (2015), ISSN 1877–0509. https://doi.org/10.1016/j.procs.2015.09.170
Hong, I., Park, S., Lee, B., Lee, J., Jeong, D., Park, S.: 2014/08/28. IoT-Based Smart Garbage System for Efficient Food Waste Management, 2014 (2014). https://doi.org/10.1155/2014/646953
Khattab, A., Youssry, N.: Machine learning for IoT Systems. In: Alam, M., Shakil, K.A., Khan, S. (eds.) Internet of Things (IoT), pp. 105–127. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-37468-6_6
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Beteta, M.A., Maestre, R., Abbenante, S.E., Bleda, A.L., Leal, J.L. (2023). A Predictive Waste Collection Management System: IoT Device for Smart Containers and System Architecture. In: Bravo, J., Ochoa, S., Favela, J. (eds) Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022). UCAmI 2022. Lecture Notes in Networks and Systems, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-031-21333-5_60
Download citation
DOI: https://doi.org/10.1007/978-3-031-21333-5_60
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-21332-8
Online ISBN: 978-3-031-21333-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)