Demo Abstract: No Time to Waste, with SWAM!
Authors
S. Faye, F. Melakessou, P. Gautier, and D. Khadraoui
Reference
in proceedings of the 6th ACM international conference on systems for energy-efficient buildings, cities, and transportation, Columbia Univ, New York, 13-14 november, ISBN:978-1-4503-7005-9, p. 342-343, 2019
Description
anaging waste from professional customers (e.g. restaurants, shops) has an impressive number of requirements that must be met to ensure a high quality of service and environmental compliance. Existing decision support systems generally rely on a limited flow of information and offer an often static or statistically based approach. With SWAM, we aim to create a smart waste collection system relying on data generated by new fill -level sensor technologies integrated into waste bins. Through this demonstration, we intend to show how artificial intelligence and new sensing technologies can be of benefit to this sector. The project concept will be showcased through a small-scale interactive demonstration where the audience will be responsible for the proper execution of the waste collection processes. A video of the demo is available online(1) - It shows the interaction between the audience, our decision-making systems, waste collection robot and miniature bins equipped with ultrasonic sensors.
