Node assembly for waste level measurement: embrace the smart city
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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 Bragança, 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 ℃). 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%.
This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/05757/2020, UIDB/00690/2020, LA/P/0045/2020, UIDB/50020/2020, and UIDP/50020/2020. Adriano Silva was supported by FCT-MIT Portugal PhD grant SFRH/BD/151346/2021, and Thadeu Brito was supported by FCT PhD grant SFRH/BD/08598 /2020. Jose L. Diaz de Tuesta acknowledges the finantial support through the program of Atraccion de Talento of Atraccion al Talento of the Comunidad de Madrid (Spain) for the individual research grant 2020-T2/AMB-19836.
