Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/3338
Title: A Smart Waste Disposal System: To Encourage Proper Waste Disposal
Authors: Alwis, D
Munasinghe, P
Rajapaksha, S
Ranawaka, B
Krishara, J
Tissera, W
Keywords: Smart Waste Disposal System
Encourage Proper Waste
Proper Waste Disposal
Issue Date: 9-Dec-2022
Publisher: IEEE
Citation: D. Alwis, P. Munasinghe, S. Rajapaksha, B. Ranawaka, J. Krishara and W. Tissera, "A Smart Waste Disposal System: To Encourage Proper Waste Disposal," 2022 4th International Conference on Advancements in Computing (ICAC), Colombo, Sri Lanka, 2022, pp. 441-446, doi: 10.1109/ICAC57685.2022.10025307.
Series/Report no.: 2022 4th International Conference on Advancements in Computing (ICAC);
Abstract: Waste disposal is one of the most important industries in the world. If not maintained properly it would lead to the destruction of the environment. Improper waste disposal is becoming a critical issue in Sri Lanka and the lack of waste segregation, inadequate waste collection methods, the lack of support for waste management from the public are among the root causes of the problem. As a solution we propose an IoT-based solid waste management system that allows garbage bin monitoring, routing of garbage collector trucks, a prediction model and a point rewarding system. As the end result of this research the following prototypes was built; a prototype model of a smart bin with the capabilities of opening and closing by itself and detecting the waste level of the bin, a prototype mobile application for garbage collectors which delivers analysed data on truck position and ensures timeliness, a prototype mobile application for the public which receives the weight and type of solid waste discarded as an input and calculate reward points to encourage the public in proper waste disposal, a prototype web application which delivers statistical data for detailed reports and a prediction model which predicts the amount of waste to be collected in the coming month using machine learning. This is a low-cost IoT-based solution that uses existing resources to handle the massive amounts of garbage collected each day.
URI: https://rda.sliit.lk/handle/123456789/3338
ISBN: 979-8-3503-9809-0
Appears in Collections:4th International Conference on Advancements in Computing (ICAC) | 2022
Department of Information Technology
Research Papers - IEEE
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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