| Title |
Node Assembly for Waste Level Measurement: Embrace the Smart City |
| ID_Doc |
37763 |
| Authors |
Silva, AS; Brito, T; de Tuesta, JLD; Lima, J; Pereira, AI; Silva, AMT; Gomes, HT |
| Title |
Node Assembly for Waste Level Measurement: Embrace the Smart City |
| Year |
2022 |
| Published |
|
| DOI |
10.1007/978-3-031-23236-7_42 |
| Abstract |
Municipal Solid Waste Management Systems (MSWMS) worldwide are currently facing pressure due to the rapid growth of the population in cities. One of the biggest challenges in this system is the inefficient expenditure of time and fuel in waste collection. In this regard, cities/municipalities in charge of MSWMS could take advantage of information and communication technologies to improve the overall quality of their infrastructure. One particular strategy that has been explored and is showing interesting results is using a Wireless Sensors Network (WSN) to monitor waste levels in real-time and help decision-making regarding the need for collection. The WSN is equipped with sensing devices that should be carefully chosen considering the real scenario in which they will work. Therefore, in this work, three sets of sensors were studied to evaluate which is the best to be used in the future WSN assembled in Braganca, Portugal. Sets tested were HC-SR04 (S1), HC-SR04 + DHT11 (S2), and US-100 (S3). Tests considered for this work were air temperature and several distances. In the first, the performance of each set to measure a fixed target (metal and plastic box) was evaluated under different temperatures (1.7-37 degrees C). From these results, two best sets were further used to assess distance measurement at a fixed temperature. This test revealed low absolute errors measuring the distances of interest in this work, ranging from 0.18% to 1.27%. |
| Author Keywords |
Smart City; Waste management; Ultrasonic sensor; Wireless Sensors Network |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000976814900042 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applications; Operations Research & Management Science |
| Research Area |
Computer Science; Operations Research & Management Science |
| PDF |
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